Conference Papers on "Web-University & MOOCs " at the Chair of Prof. Dr. Christoph Meinel

2021 [ to top ]

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  Serth, S., Staubitz, T., Teusner, R., Meinel, C.: CodeOcean and CodeHarbor: Auto-Grader and Code Repository. In: Shaffer, C., Brusilovsky, P., Koedinger, K., and Edwards, S. (eds.) SPLICE 2021 Workshop CS Education Infrastructure for All III: From Ideas to Practice. p. 5. 52nd ACM Technical Symposium on Computer Science Education, Virtual Event (2021).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  The Hasso Plattner Institute (HPI) successfully operates a MOOC (Massive Open Online Course) platform since 2012. Since 2013, global enterprises, international organizations, governments, and research projects funded by the German ministry of education are partnering with us to operate their own instances of the platform. The focus of our platform instance is on IT topics, which includes programming courses in different programming languages. An important element of these courses are graded hands-on programming assignments. MOOCs, even more than traditional classroom situations, depend on automated solutions to assess programming exercises. Manual evaluation is not an option due to the massive amount of users that participate in these courses. The paper at hand presents two of the tools developed in this context at the HPI: CodeOceantextemdash an auto-grader for a variety of programming languages, and CodeHarbor, a tool to share auto-gradable programming exercises between various online platforms.
  @inproceedings{serthCodeOceanCodeHarborAutoGrader2021, abstract = {The Hasso Plattner Institute (HPI) successfully operates a MOOC (Massive Open Online Course) platform since 2012. Since 2013, global enterprises, international organizations, governments, and research projects funded by the German ministry of education are partnering with us to operate their own instances of the platform. The focus of our platform instance is on IT topics, which includes programming courses in different programming languages. An important element of these courses are graded hands-on programming assignments. MOOCs, even more than traditional classroom situations, depend on automated solutions to assess programming exercises. Manual evaluation is not an option due to the massive amount of users that participate in these courses. The paper at hand presents two of the tools developed in this context at the HPI: CodeOcean\textemdash an auto-grader for a variety of programming languages, and CodeHarbor, a tool to share auto-gradable programming exercises between various online platforms.}, address = {Virtual Event}, author = {Serth, Sebastian and Staubitz, Thomas and Teusner, Ralf and Meinel, Christoph}, booktitle = {SPLICE 2021 Workshop CS Education Infrastructure for All III: From Ideas to Practice}, editor = {Shaffer, Cliff and Brusilovsky, Peter and Koedinger, Ken and Edwards, Steve}, keywords = {myown webuniversity its}, month = {mar}, organization = {SPLICE}, pages = 5, publisher = {52nd ACM Technical Symposium on Computer Science Education}, title = {CodeOcean and CodeHarbor: Auto-Grader and Code Repository}, year = 2021 }
  Further Information

  Editor(s)Shaffer, Cliff and Brusilovsky, Peter and Koedinger, Ken and Edwards, Steve

  AbstractThe Hasso Plattner Institute (HPI) successfully operates a MOOC (Massive Open Online Course) platform since 2012. Since 2013, global enterprises, international organizations, governments, and research projects funded by the German ministry of education are partnering with us to operate their own instances of the platform. The focus of our platform instance is on IT topics, which includes programming courses in different programming languages. An important element of these courses are graded hands-on programming assignments. MOOCs, even more than traditional classroom situations, depend on automated solutions to assess programming exercises. Manual evaluation is not an option due to the massive amount of users that participate in these courses. The paper at hand presents two of the tools developed in this context at the HPI: CodeOceantextemdash an auto-grader for a variety of programming languages, and CodeHarbor, a tool to share auto-gradable programming exercises between various online platforms.

2020 [ to top ]

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  Staubitz, T., Meinel, C.: A Systematic Quantitative and Qualitative Analysis of Participants’ Opinions on Peer Assessment in Surveys and Course Forum Discussions of MOOCs.2020 IEEE Global Engineering Education Conference (EDUCON). pp. 962-971 (2020).
  [ BibTeX ] [ Details ]
   
  @inproceedings{9125089, author = {Staubitz, Thomas and Meinel, Christoph}, booktitle = {2020 IEEE Global Engineering Education Conference (EDUCON)}, keywords = {e-learning myown assessment mooc assignment}, pages = {962-971}, title = {A Systematic Quantitative and Qualitative Analysis of Participants’ Opinions on Peer Assessment in Surveys and Course Forum Discussions of MOOCs}, year = 2020 }
  Further Information
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  Bothe, M., Meinel, C.: When Do Learners Rewatch Videos in MOOCs?2020 IEEE Learning With MOOCS (LWMOOCS). pp. 148-151 (2020).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Mobile applications for MOOCs (Massive Open Online Courses) offer the possibility to download learning material to enable network independent learning sessions. The management of downloaded content on mobile devices is a manual process for the learner, which has the potential for automation. This includes the deletion of learning material that is likely to be no longer consumed. In this paper, a metric was defined to quantify learners’ references to previous videos based on the order in which the videos were viewed. In an observational study involving three MOOCs in the field of computer science and IT systems engineering, learners referred to previous video content only a single time on average. Outliers made use of earlier content up to 44 times during a course. Referenced videos belonged in most cases to the current or previous course section. The learners referred more often to previous videos during the course period compared to when participating in self-paced mode, while learners who earned a record of achievement referred to previous videos significantly more frequently than those who did not.
  @inproceedings{9234368, abstract = {Mobile applications for MOOCs (Massive Open Online Courses) offer the possibility to download learning material to enable network independent learning sessions. The management of downloaded content on mobile devices is a manual process for the learner, which has the potential for automation. This includes the deletion of learning material that is likely to be no longer consumed. In this paper, a metric was defined to quantify learners’ references to previous videos based on the order in which the videos were viewed. In an observational study involving three MOOCs in the field of computer science and IT systems engineering, learners referred to previous video content only a single time on average. Outliers made use of earlier content up to 44 times during a course. Referenced videos belonged in most cases to the current or previous course section. The learners referred more often to previous videos during the course period compared to when participating in self-paced mode, while learners who earned a record of achievement referred to previous videos significantly more frequently than those who did not.}, author = {{Bothe}, M. and {Meinel}, C.}, booktitle = {2020 IEEE Learning With MOOCS (LWMOOCS)}, keywords = {MobileSeamlessLearning myown MobileLearning eLearning MOOCs}, pages = {148-151}, title = {When Do Learners Rewatch Videos in MOOCs?}, year = 2020 }
  Further Information

  URNhttp://dx.doi.org/10.1109/LWMOOCS50143.2020.9234368

  AbstractMobile applications for MOOCs (Massive Open Online Courses) offer the possibility to download learning material to enable network independent learning sessions. The management of downloaded content on mobile devices is a manual process for the learner, which has the potential for automation. This includes the deletion of learning material that is likely to be no longer consumed. In this paper, a metric was defined to quantify learners’ references to previous videos based on the order in which the videos were viewed. In an observational study involving three MOOCs in the field of computer science and IT systems engineering, learners referred to previous video content only a single time on average. Outliers made use of earlier content up to 44 times during a course. Referenced videos belonged in most cases to the current or previous course section. The learners referred more often to previous videos during the course period compared to when participating in self-paced mode, while learners who earned a record of achievement referred to previous videos significantly more frequently than those who did not.
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  Bothe, M., Renz, J., Meinel, C.: On the Acceptance and Effects of Recapping Self-Test Questions in MOOCs.2020 IEEE Global Engineering Education Conference (EDUCON). pp. 264-272 (2020).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Learners in Massive Open Online Courses (MOOCs) are reiterating over the provided course material - especially self-tests - to consolidate their knowledge. This is a manual and often cumbersome process as MOOC platforms do not provide personalized revision opportunities. This paper introduces the design and concept of a flashcard-like recap tool based on spaced repetition learning techniques. The recap material is derived from existing self-test questions. The usage rates of the recap tool were observed in three courses and peaked before graded assignments, primarily before the final exam. When choosing the question quantity, learners preferred either the smallest option or wanted to revise all of the available questions, whereas the average number of questions per recap session increases over time. Recap tool users who completed a recap session showed smaller error rates than those who stopped a recap session abruptly, while learners who skipped questions performed worst. Course participants who used the recap tool throughout the course achieved on average more of the available points. Statistically highly significant differences were detected for all observed courses. An additional survey (N=79) gathered qualitative feedback and impressions from the learning community.
  @inproceedings{9125145, abstract = {Learners in Massive Open Online Courses (MOOCs) are reiterating over the provided course material - especially self-tests - to consolidate their knowledge. This is a manual and often cumbersome process as MOOC platforms do not provide personalized revision opportunities. This paper introduces the design and concept of a flashcard-like recap tool based on spaced repetition learning techniques. The recap material is derived from existing self-test questions. The usage rates of the recap tool were observed in three courses and peaked before graded assignments, primarily before the final exam. When choosing the question quantity, learners preferred either the smallest option or wanted to revise all of the available questions, whereas the average number of questions per recap session increases over time. Recap tool users who completed a recap session showed smaller error rates than those who stopped a recap session abruptly, while learners who skipped questions performed worst. Course participants who used the recap tool throughout the course achieved on average more of the available points. Statistically highly significant differences were detected for all observed courses. An additional survey (N=79) gathered qualitative feedback and impressions from the learning community.}, author = {Bothe, Max and Renz, Jan and Meinel, Christoph}, booktitle = {2020 IEEE Global Engineering Education Conference (EDUCON)}, keywords = {spacedlearning selfregulatedlearning moocs}, month = {April}, pages = {264-272}, title = {On the Acceptance and Effects of Recapping Self-Test Questions in MOOCs}, year = 2020 }
  Further Information

  URNhttp://dx.doi.org/10.1109/EDUCON45650.2020.9125145

  AbstractLearners in Massive Open Online Courses (MOOCs) are reiterating over the provided course material - especially self-tests - to consolidate their knowledge. This is a manual and often cumbersome process as MOOC platforms do not provide personalized revision opportunities. This paper introduces the design and concept of a flashcard-like recap tool based on spaced repetition learning techniques. The recap material is derived from existing self-test questions. The usage rates of the recap tool were observed in three courses and peaked before graded assignments, primarily before the final exam. When choosing the question quantity, learners preferred either the smallest option or wanted to revise all of the available questions, whereas the average number of questions per recap session increases over time. Recap tool users who completed a recap session showed smaller error rates than those who stopped a recap session abruptly, while learners who skipped questions performed worst. Course participants who used the recap tool throughout the course achieved on average more of the available points. Statistically highly significant differences were detected for all observed courses. An additional survey (N=79) gathered qualitative feedback and impressions from the learning community.
• 
  Rohloff, T., Schwerer, F., Schenk, N., Meinel, C.: openSAP: Learner Behavior and Activity in Self-Paced Enterprise MOOCs.Proceedings of the 13th International Conference on E-Learning in the Workplace (ICELW 2020). ICELW (2020).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Massive Open Online Courses (MOOCs) have been a subject of research since 2012, especially in the context of professional development and workplace learning due to their flexible schedule and format, which is a prerequisite for on the job learning. But MOOCs often do not fulfill the promise of flexible learning as it is only possible to achieve a certificate during the course runtime. An unpredictable workload and thus a lack of time often results in not showing up to a course or dropping out during the course runtime. Therefore, some platform content remains accessible even after the course runtime in self-paced mode. These courses differ from live courses as participants still can access all of the content and the discussion forum in read-only mode, but are not able to take the graded assignments and exams which are a prerequisite to achieving a certificate at the end of a course. Even though it is only possible by paying a fee to earn a graded certificate for these self-paced courses, we identified a high share of additional enrollments after the course end that suggests there is still interest from participants. Nevertheless, learning behavior in self-paced courses has not been a major subject of research, yet. This work contributes to closing this research gap by exploring the learner behavior in self-paced courses. The results show tendencies of more time-efficiency and engagement of self-paced learners under certain conditions and pave the way for further research and practical applications.
  @inproceedings{Rohloff2020LearnerBehaviorEnterprise, abstract = {Massive Open Online Courses (MOOCs) have been a subject of research since 2012, especially in the context of professional development and workplace learning due to their flexible schedule and format, which is a prerequisite for on the job learning. But MOOCs often do not fulfill the promise of flexible learning as it is only possible to achieve a certificate during the course runtime. An unpredictable workload and thus a lack of time often results in not showing up to a course or dropping out during the course runtime. Therefore, some platform content remains accessible even after the course runtime in self-paced mode. These courses differ from live courses as participants still can access all of the content and the discussion forum in read-only mode, but are not able to take the graded assignments and exams which are a prerequisite to achieving a certificate at the end of a course. Even though it is only possible by paying a fee to earn a graded certificate for these self-paced courses, we identified a high share of additional enrollments after the course end that suggests there is still interest from participants. Nevertheless, learning behavior in self-paced courses has not been a major subject of research, yet. This work contributes to closing this research gap by exploring the learner behavior in self-paced courses. The results show tendencies of more time-efficiency and engagement of self-paced learners under certain conditions and pave the way for further research and practical applications.}, author = {Rohloff, Tobias and Schwerer, Florian and Schenk, Nathanael and Meinel, Christoph}, booktitle = {Proceedings of the 13th International Conference on E-Learning in the Workplace (ICELW 2020)}, keywords = {moocs learninganalytics}, publisher = {ICELW}, title = {openSAP: Learner Behavior and Activity in Self-Paced Enterprise MOOCs}, year = 2020 }
  Further Information

  URNhttp://dx.doi.org/10.3991/ijac.v13i2.16531

  AbstractMassive Open Online Courses (MOOCs) have been a subject of research since 2012, especially in the context of professional development and workplace learning due to their flexible schedule and format, which is a prerequisite for on the job learning. But MOOCs often do not fulfill the promise of flexible learning as it is only possible to achieve a certificate during the course runtime. An unpredictable workload and thus a lack of time often results in not showing up to a course or dropping out during the course runtime. Therefore, some platform content remains accessible even after the course runtime in self-paced mode. These courses differ from live courses as participants still can access all of the content and the discussion forum in read-only mode, but are not able to take the graded assignments and exams which are a prerequisite to achieving a certificate at the end of a course. Even though it is only possible by paying a fee to earn a graded certificate for these self-paced courses, we identified a high share of additional enrollments after the course end that suggests there is still interest from participants. Nevertheless, learning behavior in self-paced courses has not been a major subject of research, yet. This work contributes to closing this research gap by exploring the learner behavior in self-paced courses. The results show tendencies of more time-efficiency and engagement of self-paced learners under certain conditions and pave the way for further research and practical applications.
• 
  Rohloff, T., Sauer, D., Meinel, C.: Students’ Achievement of Personalized Learning Objectives in MOOCs.Proceedings of the Seventh ACM Conference on Learning at Scale (L@S 2020). p. 147--156. Association for Computing Machinery (2020).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Massive Open Online Courses (MOOCs) provide the opportunity to offer free and open education at scale. Thousands of students with different social and cultural backgrounds from all over the world can enroll for a course. This diverse audience comes with varying motivations and intentions from their personal or professional life. However, course instructors cannot offer individual support and guidance at this scale and therefore usually provide a one-size-fits-all approach. Students have to follow weekly-structured courses and their success is measured with the achievement of a certificate at the end. To better address the varying learning needs, technical support for goal-oriented and self-regulated learning is desired but very limited to date. Both learning strategies are proven to be key factors for students' achievement in large-scale online learning environments. Therefore, this paper presents a continuative study of personalized learning objectives in MOOCs to encourage goal-oriented and self-regulated learning. Based on the previously well-perceived acceptance and usefulness of the concept of personalized learning objectives, this study examines which learners select an objective and how successful they complete objectives. Concerning the learners' socio-demographic and geographical background, we could not identify any practical significant difference between students with selected learning objectives and the total course population. However, we have identified promising objective achievement rates, and we have observed a practical significant improvement of the certification rates comparing the total course population and students who selected an objective that included a graded certificate. This has also demonstrated a method for calculating more reasonable completion rates in MOOCs.
  @inproceedings{Rohloff2020LearningObjectivesAchievement, abstract = {Massive Open Online Courses (MOOCs) provide the opportunity to offer free and open education at scale. Thousands of students with different social and cultural backgrounds from all over the world can enroll for a course. This diverse audience comes with varying motivations and intentions from their personal or professional life. However, course instructors cannot offer individual support and guidance at this scale and therefore usually provide a one-size-fits-all approach. Students have to follow weekly-structured courses and their success is measured with the achievement of a certificate at the end. To better address the varying learning needs, technical support for goal-oriented and self-regulated learning is desired but very limited to date. Both learning strategies are proven to be key factors for students' achievement in large-scale online learning environments. Therefore, this paper presents a continuative study of personalized learning objectives in MOOCs to encourage goal-oriented and self-regulated learning. Based on the previously well-perceived acceptance and usefulness of the concept of personalized learning objectives, this study examines which learners select an objective and how successful they complete objectives. Concerning the learners' socio-demographic and geographical background, we could not identify any practical significant difference between students with selected learning objectives and the total course population. However, we have identified promising objective achievement rates, and we have observed a practical significant improvement of the certification rates comparing the total course population and students who selected an objective that included a graded certificate. This has also demonstrated a method for calculating more reasonable completion rates in MOOCs.}, author = {Rohloff, Tobias and Sauer, Dominic and Meinel, Christoph}, booktitle = {Proceedings of the Seventh ACM Conference on Learning at Scale (L@S 2020)}, keywords = {moocs learningobjectives}, pages = {147–156}, publisher = {Association for Computing Machinery}, title = {Students’ Achievement of Personalized Learning Objectives in MOOCs}, year = 2020 }
  Further Information

  URNhttp://dx.doi.org/10.1145/3386527.3405918

  AbstractMassive Open Online Courses (MOOCs) provide the opportunity to offer free and open education at scale. Thousands of students with different social and cultural backgrounds from all over the world can enroll for a course. This diverse audience comes with varying motivations and intentions from their personal or professional life. However, course instructors cannot offer individual support and guidance at this scale and therefore usually provide a one-size-fits-all approach. Students have to follow weekly-structured courses and their success is measured with the achievement of a certificate at the end. To better address the varying learning needs, technical support for goal-oriented and self-regulated learning is desired but very limited to date. Both learning strategies are proven to be key factors for students' achievement in large-scale online learning environments. Therefore, this paper presents a continuative study of personalized learning objectives in MOOCs to encourage goal-oriented and self-regulated learning. Based on the previously well-perceived acceptance and usefulness of the concept of personalized learning objectives, this study examines which learners select an objective and how successful they complete objectives. Concerning the learners' socio-demographic and geographical background, we could not identify any practical significant difference between students with selected learning objectives and the total course population. However, we have identified promising objective achievement rates, and we have observed a practical significant improvement of the certification rates comparing the total course population and students who selected an objective that included a graded certificate. This has also demonstrated a method for calculating more reasonable completion rates in MOOCs.
• 
  Staubitz, T., Traifeh, H., Chujfi, S., Meinel, C.: Have Your Tickets Ready! Impede Free Riding in Large Scale Team Assignments.Proceedings of the Seventh ACM Conference on Learning @ Scale. pp. 349–352. Association for Computing Machinery, Virtual Event, USA (2020).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  Teamwork and graded team assignments in MOOCs are still largely under-researched. Nevertheless, the topic is enormously important as the ability to work and solve problems in teams is becoming increasingly common in modern work environments. The paper at hand discusses the reliability of a system to detect free-riders in peer assessed team tasks.
  @inproceedings{10.1145/3386527.3406744, abstract = {Teamwork and graded team assignments in MOOCs are still largely under-researched. Nevertheless, the topic is enormously important as the ability to work and solve problems in teams is becoming increasingly common in modern work environments. The paper at hand discusses the reliability of a system to detect free-riders in peer assessed team tasks.}, address = {New York, NY, USA}, author = {Staubitz, Thomas and Traifeh, Hanadi and Chujfi, Salim and Meinel, Christoph}, booktitle = {Proceedings of the Seventh ACM Conference on Learning @ Scale}, keywords = {e-learning myown assessment mooc teamwork}, pages = {349–352}, publisher = {Association for Computing Machinery}, series = {L@S '20}, title = {Have Your Tickets Ready! Impede Free Riding in Large Scale Team Assignments}, year = 2020 }
  Further Information

  URNhttp://dx.doi.org/10.1145/3386527.3406744

  AbstractTeamwork and graded team assignments in MOOCs are still largely under-researched. Nevertheless, the topic is enormously important as the ability to work and solve problems in teams is becoming increasingly common in modern work environments. The paper at hand discusses the reliability of a system to detect free-riders in peer assessed team tasks.
• 
  Serth, S., Teusner, R., Meinel, C.: Digitale Arbeitsblätter mit interaktiven Programmieraufgaben im Informatik-Unterricht. In: Zender, R., Ifenthaler, D., Leonhardt, T., and Schumacher, C. (eds.) Lecture Notes in Informatics (LNI) - Proceedings: DELFI 2020 – Die 18. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V. pp. 235-246. Gesellschaft für Informatik e.V. (GI), Bonn, Germany (2020).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Moderner Informatikunterricht umfasst das Erlernen von Grundlagen des Programmierens. Dabei verwenden Lehrer häufig bereits vorhandene Videos, Quizfragen und praktische Programmieraufgaben aus Massive Open Online Courses (MOOCs), obwohl derzeit die Möglichkeiten zur Anpassung der Inhalte und dem Hinzufügen eigener Materialien für Lehrer begrenzt sind. Unsere Software ermöglicht es Lehrern, ihre eigenen interaktiven Arbeitsblätter mit angepassten und eigenen Übungen zu erstellen. Im Rahmen einer praktischen Evaluierung wurde das Konzept von Schülern und Lehrern gleichermaßen gut angenommen: Lehrer hatten mehr Zeit für die Beantwortung individueller Fragen und Schüler konnten in ihrem eigenen Tempo mithilfe automatisierter Rückmeldungen lernen. Für die Vorbereitung zukünftiger Unterrichtsstunden schätzten Lehrer die Möglichkeit, häufige Fehler auszuwerten, um so zuvor unerkannte Probleme besprechen zu können. Interaktive Arbeitsblätter fördern individualisierte Lernprozesse, unterstützen Lehrer in der Unterrichtsgestaltung und sind somit ein wichtiger Bestandteil digitaler Bildung an Schulen.
  @inproceedings{serthDigitaleArbeitsblaetterMit2020, abstract = {Moderner Informatikunterricht umfasst das Erlernen von Grundlagen des Programmierens. Dabei verwenden Lehrer häufig bereits vorhandene Videos, Quizfragen und praktische Programmieraufgaben aus Massive Open Online Courses (MOOCs), obwohl derzeit die Möglichkeiten zur Anpassung der Inhalte und dem Hinzufügen eigener Materialien für Lehrer begrenzt sind. Unsere Software ermöglicht es Lehrern, ihre eigenen interaktiven Arbeitsblätter mit angepassten und eigenen Übungen zu erstellen. Im Rahmen einer praktischen Evaluierung wurde das Konzept von Schülern und Lehrern gleichermaßen gut angenommen: Lehrer hatten mehr Zeit für die Beantwortung individueller Fragen und Schüler konnten in ihrem eigenen Tempo mithilfe automatisierter Rückmeldungen lernen. Für die Vorbereitung zukünftiger Unterrichtsstunden schätzten Lehrer die Möglichkeit, häufige Fehler auszuwerten, um so zuvor unerkannte Probleme besprechen zu können. Interaktive Arbeitsblätter fördern individualisierte Lernprozesse, unterstützen Lehrer in der Unterrichtsgestaltung und sind somit ein wichtiger Bestandteil digitaler Bildung an Schulen.}, address = {Bonn, Germany}, author = {Serth, Sebastian and Teusner, Ralf and Meinel, Christoph}, booktitle = {Lecture Notes in Informatics (LNI) - Proceedings: DELFI 2020 – Die 18. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V.}, editor = {Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara}, keywords = {myown webuniversity its}, month = {09}, organization = {Gesellschaft für Informatik e.V. (GI)}, pages = {235-246}, publisher = {Gesellschaft für Informatik e.V. (GI)}, series = {Lecture Notes in Informatics}, title = {Digitale Arbeitsblätter mit interaktiven Programmieraufgaben im Informatik-Unterricht}, volume = {P-308}, year = 2020 }
  Further Information

  Editor(s)Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara

  AbstractModerner Informatikunterricht umfasst das Erlernen von Grundlagen des Programmierens. Dabei verwenden Lehrer häufig bereits vorhandene Videos, Quizfragen und praktische Programmieraufgaben aus Massive Open Online Courses (MOOCs), obwohl derzeit die Möglichkeiten zur Anpassung der Inhalte und dem Hinzufügen eigener Materialien für Lehrer begrenzt sind. Unsere Software ermöglicht es Lehrern, ihre eigenen interaktiven Arbeitsblätter mit angepassten und eigenen Übungen zu erstellen. Im Rahmen einer praktischen Evaluierung wurde das Konzept von Schülern und Lehrern gleichermaßen gut angenommen: Lehrer hatten mehr Zeit für die Beantwortung individueller Fragen und Schüler konnten in ihrem eigenen Tempo mithilfe automatisierter Rückmeldungen lernen. Für die Vorbereitung zukünftiger Unterrichtsstunden schätzten Lehrer die Möglichkeit, häufige Fehler auszuwerten, um so zuvor unerkannte Probleme besprechen zu können. Interaktive Arbeitsblätter fördern individualisierte Lernprozesse, unterstützen Lehrer in der Unterrichtsgestaltung und sind somit ein wichtiger Bestandteil digitaler Bildung an Schulen.
• 
  Rohloff, T., von Schmieden, K., Meinel, C.: Students’ Satisfaction of a Design Thinking MOOC with Personalized Learning Objectives.IEEE Learning With MOOCs (LWMOOCS 2020). p. 37--41. IEEE (2020).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Due to their openness and low barriers to enroll, most Massive Open Online Courses (MOOCs) offer free access to knowledge for almost everyone. This attracts a large number of learners, each with their own individual intentions and motivations to join a course. However, personal support and guidance can almost never be provided at this scale. All learners have to follow the same usually weekly structured content and the learning success is only measured by the achievement of a certificate. To overcome this one-size-fits-all approach with technical means, we introduced a tool for Personalized Learning Objectives. This enables learners to achieve more individual objectives in courses, follow different learning paths, and link their motivations and intentions to the definition of learning success. Previous studies have already examined, among other aspects, the usefulness, acceptance, and achievement rates of learning objectives in MOOCs. In this complimentary research, the satisfaction of students with and without a selected learning objective is compared in a course on topics from the field of Design Thinking.
  @inproceedings{Rohloff2020LearningObjectivesSatisfaction, abstract = {Due to their openness and low barriers to enroll, most Massive Open Online Courses (MOOCs) offer free access to knowledge for almost everyone. This attracts a large number of learners, each with their own individual intentions and motivations to join a course. However, personal support and guidance can almost never be provided at this scale. All learners have to follow the same usually weekly structured content and the learning success is only measured by the achievement of a certificate. To overcome this one-size-fits-all approach with technical means, we introduced a tool for Personalized Learning Objectives. This enables learners to achieve more individual objectives in courses, follow different learning paths, and link their motivations and intentions to the definition of learning success. Previous studies have already examined, among other aspects, the usefulness, acceptance, and achievement rates of learning objectives in MOOCs. In this complimentary research, the satisfaction of students with and without a selected learning objective is compared in a course on topics from the field of Design Thinking.}, author = {Rohloff, Tobias and von Schmieden, Karen and Meinel, Christoph}, booktitle = {IEEE Learning With MOOCs (LWMOOCS 2020)}, keywords = {moocs learningobjectives}, pages = {37–41}, publisher = {IEEE}, title = {Students’ Satisfaction of a Design Thinking MOOC with Personalized Learning Objectives}, year = 2020 }
  Further Information

  URNhttp://dx.doi.org/10.1109/LWMOOCS50143.2020.9234349

  AbstractDue to their openness and low barriers to enroll, most Massive Open Online Courses (MOOCs) offer free access to knowledge for almost everyone. This attracts a large number of learners, each with their own individual intentions and motivations to join a course. However, personal support and guidance can almost never be provided at this scale. All learners have to follow the same usually weekly structured content and the learning success is only measured by the achievement of a certificate. To overcome this one-size-fits-all approach with technical means, we introduced a tool for Personalized Learning Objectives. This enables learners to achieve more individual objectives in courses, follow different learning paths, and link their motivations and intentions to the definition of learning success. Previous studies have already examined, among other aspects, the usefulness, acceptance, and achievement rates of learning objectives in MOOCs. In this complimentary research, the satisfaction of students with and without a selected learning objective is compared in a course on topics from the field of Design Thinking.
• 
  Bothe, M., Meinel, C.: On the Potential of Automated Downloads for MOOC Content on Mobile Devices.2020 IEEE Learning With MOOCS (LWMOOCS). pp. 58-63 (2020).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Mobile applications for MOOC platforms often can download learning material—namely videos—for later usage without the need for an Internet connection. As learners want to perform such data-intensive tasks with a WiFi connection, manual planning is required. By automating the download management, learners can be supported by always having video material available independent of the current Internet connection. This work examines the current download behavior shown in three MOOC courses. Hereby, influencing factors like the dependence on time and date, as well as the network state were analyzed. The results show that learners are already aware of data-intensive learning activities. They mostly download videos when connected to a WiFi network and consume pre-downloaded video content when using a cellular connection. An estimate of the potential for automated downloads using a simplified approach revealed the possibility of making an additional 19% of the video consumption network independent. The download behavior in the three courses examined differed noticeably so that automated downloads should be seen as an additional feature that can be activated per course.
  @inproceedings{9234338, abstract = {Mobile applications for MOOC platforms often can download learning material—namely videos—for later usage without the need for an Internet connection. As learners want to perform such data-intensive tasks with a WiFi connection, manual planning is required. By automating the download management, learners can be supported by always having video material available independent of the current Internet connection. This work examines the current download behavior shown in three MOOC courses. Hereby, influencing factors like the dependence on time and date, as well as the network state were analyzed. The results show that learners are already aware of data-intensive learning activities. They mostly download videos when connected to a WiFi network and consume pre-downloaded video content when using a cellular connection. An estimate of the potential for automated downloads using a simplified approach revealed the possibility of making an additional 19% of the video consumption network independent. The download behavior in the three courses examined differed noticeably so that automated downloads should be seen as an additional feature that can be activated per course.}, author = {{Bothe}, M. and {Meinel}, C.}, booktitle = {2020 IEEE Learning With MOOCS (LWMOOCS)}, keywords = {MobileSeamlessLearning myown MobileLearning eLearning MOOCs}, pages = {58-63}, title = {On the Potential of Automated Downloads for MOOC Content on Mobile Devices}, year = 2020 }
  Further Information

  URNhttp://dx.doi.org/10.1109/LWMOOCS50143.2020.9234338

  AbstractMobile applications for MOOC platforms often can download learning material—namely videos—for later usage without the need for an Internet connection. As learners want to perform such data-intensive tasks with a WiFi connection, manual planning is required. By automating the download management, learners can be supported by always having video material available independent of the current Internet connection. This work examines the current download behavior shown in three MOOC courses. Hereby, influencing factors like the dependence on time and date, as well as the network state were analyzed. The results show that learners are already aware of data-intensive learning activities. They mostly download videos when connected to a WiFi network and consume pre-downloaded video content when using a cellular connection. An estimate of the potential for automated downloads using a simplified approach revealed the possibility of making an additional 19% of the video consumption network independent. The download behavior in the three courses examined differed noticeably so that automated downloads should be seen as an additional feature that can be activated per course.

2019 [ to top ]

• 
  Staubitz, T., Teusner, R., Meinel, C.: MOOCs in Secondary Education - Experiments and Observations from German Classrooms.2019 IEEE Global Engineering Education Conference (EDUCON). pp. 173-182 (2019).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  Computer science education in German schools is often less than optimal. It is only mandatory in a few of the federal states and there is a lack of qualified teachers. As a MOOC (Massive Open Online Course) provider with a German background, we developed the idea to implement a MOOC addressing pupils in secondary schools to fill this gap. The course targeted high school pupils and enabled them to learn the Python programming language. In 2014, we successfully conducted the first iteration of this MOOC with more than 7000 participants. However, the share of pupils in the course was not quite satisfactory. So we conducted several workshops with teachers to find out why they had not used the course to the extent that we had imagined. The paper at hand explores and discusses the steps we have taken in the following years as a result of these workshops.
  @inproceedings{8725138, abstract = {Computer science education in German schools is often less than optimal. It is only mandatory in a few of the federal states and there is a lack of qualified teachers. As a MOOC (Massive Open Online Course) provider with a German background, we developed the idea to implement a MOOC addressing pupils in secondary schools to fill this gap. The course targeted high school pupils and enabled them to learn the Python programming language. In 2014, we successfully conducted the first iteration of this MOOC with more than 7000 participants. However, the share of pupils in the course was not quite satisfactory. So we conducted several workshops with teachers to find out why they had not used the course to the extent that we had imagined. The paper at hand explores and discusses the steps we have taken in the following years as a result of these workshops.}, author = {Staubitz, Thomas and Teusner, Ralf and Meinel, Christoph}, booktitle = {2019 IEEE Global Engineering Education Conference (EDUCON)}, keywords = {K-12 e-learning myown assessment autograder School mooc assignment Teamwork Programming Education}, month = {April}, pages = {173-182}, title = {MOOCs in Secondary Education - Experiments and Observations from German Classrooms}, year = 2019 }
  Further Information

  URNhttp://dx.doi.org/10.1109/EDUCON.2019.8725138

  AbstractComputer science education in German schools is often less than optimal. It is only mandatory in a few of the federal states and there is a lack of qualified teachers. As a MOOC (Massive Open Online Course) provider with a German background, we developed the idea to implement a MOOC addressing pupils in secondary schools to fill this gap. The course targeted high school pupils and enabled them to learn the Python programming language. In 2014, we successfully conducted the first iteration of this MOOC with more than 7000 participants. However, the share of pupils in the course was not quite satisfactory. So we conducted several workshops with teachers to find out why they had not used the course to the extent that we had imagined. The paper at hand explores and discusses the steps we have taken in the following years as a result of these workshops.
• 
  Rohloff, T., Bothe, M., Meinel, C.: Visualizing Content Exploration Traces of MOOC Students.Companion Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK 2019). p. 754--758. SoLAR (2019).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  This workshop paper introduces a novel approach to visualize content exploration traces of students who navigate through the learning material of Massive Open Online Courses (MOOCs). This can help teachers to identify trends and anomalies in their provided learning material in order to improve the learning experience. The difficulty lies in the complexity of data: MOOCs are structured into multiple sections consisting of different learning items and students can navigate freely between them. Therefore, it is challenging to find a meaningful and comprehensible visualization that provides a complete overview for teachers. We utilized a Sankey diagram which shows the students' transitions between course sections by grouping them into different buckets, based on the percentage of visited items in the corresponding section. Three preceding data processing steps are explained as well as the data visualization with an example course. This is followed by pedagogical considerations how MOOC teachers can utilize and interpret the visualization, to gain meaningful insights and execute informed actions. At last, an evaluation concept is outlined.
  @inproceedings{Rohloff2019ExplorationTraces, abstract = {This workshop paper introduces a novel approach to visualize content exploration traces of students who navigate through the learning material of Massive Open Online Courses (MOOCs). This can help teachers to identify trends and anomalies in their provided learning material in order to improve the learning experience. The difficulty lies in the complexity of data: MOOCs are structured into multiple sections consisting of different learning items and students can navigate freely between them. Therefore, it is challenging to find a meaningful and comprehensible visualization that provides a complete overview for teachers. We utilized a Sankey diagram which shows the students' transitions between course sections by grouping them into different buckets, based on the percentage of visited items in the corresponding section. Three preceding data processing steps are explained as well as the data visualization with an example course. This is followed by pedagogical considerations how MOOC teachers can utilize and interpret the visualization, to gain meaningful insights and execute informed actions. At last, an evaluation concept is outlined.}, author = {Rohloff, Tobias and Bothe, Max and Meinel, Christoph}, booktitle = {Companion Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK 2019)}, keywords = {moocs learninganalytics}, pages = {754–758}, publisher = {SoLAR}, title = {Visualizing Content Exploration Traces of MOOC Students}, year = 2019 }
  Further Information

  AbstractThis workshop paper introduces a novel approach to visualize content exploration traces of students who navigate through the learning material of Massive Open Online Courses (MOOCs). This can help teachers to identify trends and anomalies in their provided learning material in order to improve the learning experience. The difficulty lies in the complexity of data: MOOCs are structured into multiple sections consisting of different learning items and students can navigate freely between them. Therefore, it is challenging to find a meaningful and comprehensible visualization that provides a complete overview for teachers. We utilized a Sankey diagram which shows the students' transitions between course sections by grouping them into different buckets, based on the percentage of visited items in the corresponding section. Three preceding data processing steps are explained as well as the data visualization with an example course. This is followed by pedagogical considerations how MOOC teachers can utilize and interpret the visualization, to gain meaningful insights and execute informed actions. At last, an evaluation concept is outlined.
• 
  Rohloff, T., Renz, J., Suarez, G.N., Meinel, C.: A Ubiquitous Learning Analytics Architecture for a Service-Oriented MOOC Platform. In: Calise, M., Delgado Kloos, C., Reich, J., Ruiperez-Valiente, J.A., and Wirsing, M. (eds.) Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge (EMOOCs 2019). p. 162--171. Springer International Publishing (2019).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  As Massive Open Online Courses (MOOCs) generate a huge amount of learning activity data through its thousands of users, great potential is provided to use this data to understand and optimize the learning experience and outcome, which is the goal of Learning Analytics. But first, the data needs to be collected, processed, analyzed and reported in order to gain actionable insights. Technical concepts and implementations are rarely accessible and therefore this work presents an architecture how Learning Analytics can be implemented in a service-oriented MOOC platform. To achieve that, a service based on extensible schema-agnostic processing pipelines is introduced for the HPI MOOC platform. The approach was evaluated regarding its scalability, extensibility, and versatility with real-world use cases. Also, data privacy was taken into account. Based on five years of running the service in production on several platform deployments, six design recommendations are presented which can be utilized as best practices for platform vendors and researchers when implementing Learning Analytics in MOOCs.
  @inproceedings{Rohloff2019LearningAnalyticsArchitecture, abstract = {As Massive Open Online Courses (MOOCs) generate a huge amount of learning activity data through its thousands of users, great potential is provided to use this data to understand and optimize the learning experience and outcome, which is the goal of Learning Analytics. But first, the data needs to be collected, processed, analyzed and reported in order to gain actionable insights. Technical concepts and implementations are rarely accessible and therefore this work presents an architecture how Learning Analytics can be implemented in a service-oriented MOOC platform. To achieve that, a service based on extensible schema-agnostic processing pipelines is introduced for the HPI MOOC platform. The approach was evaluated regarding its scalability, extensibility, and versatility with real-world use cases. Also, data privacy was taken into account. Based on five years of running the service in production on several platform deployments, six design recommendations are presented which can be utilized as best practices for platform vendors and researchers when implementing Learning Analytics in MOOCs.}, author = {Rohloff, Tobias and Renz, Jan and Suarez, Gerardo Navarro and Meinel, Christoph}, booktitle = {Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge (EMOOCs 2019)}, editor = {Calise, Mauro and Delgado Kloos, Carlos and Reich, Justin and Ruiperez-Valiente, Jose A. and Wirsing, Martin}, keywords = {moocs learninganalytics}, pages = {162–171}, publisher = {Springer International Publishing}, title = {A Ubiquitous Learning Analytics Architecture for a Service-Oriented MOOC Platform}, year = 2019 }
  Further Information

  Editor(s)Calise, Mauro and Delgado Kloos, Carlos and Reich, Justin and Ruiperez-Valiente, Jose A. and Wirsing, Martin

  URNhttp://dx.doi.org/10.1007/978-3-030-19875-6_19

  AbstractAs Massive Open Online Courses (MOOCs) generate a huge amount of learning activity data through its thousands of users, great potential is provided to use this data to understand and optimize the learning experience and outcome, which is the goal of Learning Analytics. But first, the data needs to be collected, processed, analyzed and reported in order to gain actionable insights. Technical concepts and implementations are rarely accessible and therefore this work presents an architecture how Learning Analytics can be implemented in a service-oriented MOOC platform. To achieve that, a service based on extensible schema-agnostic processing pipelines is introduced for the HPI MOOC platform. The approach was evaluated regarding its scalability, extensibility, and versatility with real-world use cases. Also, data privacy was taken into account. Based on five years of running the service in production on several platform deployments, six design recommendations are presented which can be utilized as best practices for platform vendors and researchers when implementing Learning Analytics in MOOCs.
• 
  Bothe, M., Meinel, C.: Applied Mobile-Assisted Seamless Learning Techniques in MOOCs. In: Calise, M., Delgado Kloos, C., Reich, J., Ruiperez-Valiente, J.A., and Wirsing, M. (eds.) Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge. p. 21--30. Springer International Publishing, Cham (2019).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  As Massive Open Online Courses (MOOCs) are nowadays used in an increasingly ubiquitous manner, the learning process gets disrupted every time learners change context. Mobile-Assisted Seamless Learning (MSL) techniques have been identified to reduce unwanted overhead for learners and streamline their learning process. However, technical implementations vary across the industry. This paper examines existing MSL research and applied techniques in the context of MOOCs. Therefore, we discussed related MSL research topics. Afterward, eleven characteristic MSL features were selected and compared their implementations across five major MOOC platforms. While web applications provide a bigger feature set, mobile clients offer advanced offline capabilities. Based on the findings, a concept outlines how MSL features can enhance the learning experience on MOOC platforms while considering the technical feasibility.
  @inproceedings{10.1007/978-3-030-19875-6_3, abstract = {As Massive Open Online Courses (MOOCs) are nowadays used in an increasingly ubiquitous manner, the learning process gets disrupted every time learners change context. Mobile-Assisted Seamless Learning (MSL) techniques have been identified to reduce unwanted overhead for learners and streamline their learning process. However, technical implementations vary across the industry. This paper examines existing MSL research and applied techniques in the context of MOOCs. Therefore, we discussed related MSL research topics. Afterward, eleven characteristic MSL features were selected and compared their implementations across five major MOOC platforms. While web applications provide a bigger feature set, mobile clients offer advanced offline capabilities. Based on the findings, a concept outlines how MSL features can enhance the learning experience on MOOC platforms while considering the technical feasibility.}, address = {Cham}, author = {Bothe, Max and Meinel, Christoph}, booktitle = {Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge}, editor = {Calise, Mauro and Delgado Kloos, Carlos and Reich, Justin and Ruiperez-Valiente, Jose A. and Wirsing, Martin}, keywords = {SeamlessLearning myown MobileLearning MOOCs}, pages = {21–30}, publisher = {Springer International Publishing}, title = {Applied Mobile-Assisted Seamless Learning Techniques in MOOCs}, year = 2019 }
  Further Information

  Editor(s)Calise, Mauro and Delgado Kloos, Carlos and Reich, Justin and Ruiperez-Valiente, Jose A. and Wirsing, Martin

  URNhttp://dx.doi.org/10.1007/978-3-030-19875-6_3

  AbstractAs Massive Open Online Courses (MOOCs) are nowadays used in an increasingly ubiquitous manner, the learning process gets disrupted every time learners change context. Mobile-Assisted Seamless Learning (MSL) techniques have been identified to reduce unwanted overhead for learners and streamline their learning process. However, technical implementations vary across the industry. This paper examines existing MSL research and applied techniques in the context of MOOCs. Therefore, we discussed related MSL research topics. Afterward, eleven characteristic MSL features were selected and compared their implementations across five major MOOC platforms. While web applications provide a bigger feature set, mobile clients offer advanced offline capabilities. Based on the findings, a concept outlines how MSL features can enhance the learning experience on MOOC platforms while considering the technical feasibility.
• 
  Bothe, M., Renz, J., Rohloff, T., Meinel, C.: From MOOCs to Micro Learning Activities.2019 IEEE Global Engineering Education Conference (EDUCON). pp. 280-288 (2019).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Mobile devices are omnipresent in our daily lives. They are utilized for a variety of tasks and used multiple times for short periods throughout the day. MOOC providers optimized their platforms for these devices in order to support ubiquitous learning. While a combination of desktop and mobile learning yields improved course performances, standalone learning on mobile devices does not perform in the same manner. One indicator for this is the mismatch between the average usage pattern of mobile devices and the time to consume one content item in a MOOC. Micro learning builds on bite-sized learning material and focusses on short-term learning sessions. This work examines the potential of micro learning activities in the context of MOOCs. Therefore, a framework for video-based micro learning is presented, which features a personalized curriculum. Videos are suggested to the user in a non-linear order that is determined by content dependencies, users’ preferences and watched videos, as well as explicit and implicit user feedback. A mobile application was implemented to test the approach with restructured MOOC content resulting in 58 connected short videos about engineering education – e.g. web technologies and programming languages. The usage data indicates initial curiosity by the users. To improve retention rates, more user motivation will be required for future studies. A survey gathered additional qualitative feedback. While the content suggestions were seen as a vital feature for such an approach, the results showed good interest and acceptance rates to create a better learning experience for MOOCs on mobile devices.
  @inproceedings{8725043, abstract = {Mobile devices are omnipresent in our daily lives. They are utilized for a variety of tasks and used multiple times for short periods throughout the day. MOOC providers optimized their platforms for these devices in order to support ubiquitous learning. While a combination of desktop and mobile learning yields improved course performances, standalone learning on mobile devices does not perform in the same manner. One indicator for this is the mismatch between the average usage pattern of mobile devices and the time to consume one content item in a MOOC. Micro learning builds on bite-sized learning material and focusses on short-term learning sessions. This work examines the potential of micro learning activities in the context of MOOCs. Therefore, a framework for video-based micro learning is presented, which features a personalized curriculum. Videos are suggested to the user in a non-linear order that is determined by content dependencies, users’ preferences and watched videos, as well as explicit and implicit user feedback. A mobile application was implemented to test the approach with restructured MOOC content resulting in 58 connected short videos about engineering education – e.g. web technologies and programming languages. The usage data indicates initial curiosity by the users. To improve retention rates, more user motivation will be required for future studies. A survey gathered additional qualitative feedback. While the content suggestions were seen as a vital feature for such an approach, the results showed good interest and acceptance rates to create a better learning experience for MOOCs on mobile devices.}, author = {Bothe, Max and Renz, Jan and Rohloff, Tobias and Meinel, Christoph}, booktitle = {2019 IEEE Global Engineering Education Conference (EDUCON)}, keywords = {myown MobileLearning MicroLearning eLearning MOOCs}, month = {April}, pages = {280-288}, title = {From MOOCs to Micro Learning Activities}, year = 2019 }
  Further Information

  URNhttp://dx.doi.org/10.1109/EDUCON.2019.8725043

  AbstractMobile devices are omnipresent in our daily lives. They are utilized for a variety of tasks and used multiple times for short periods throughout the day. MOOC providers optimized their platforms for these devices in order to support ubiquitous learning. While a combination of desktop and mobile learning yields improved course performances, standalone learning on mobile devices does not perform in the same manner. One indicator for this is the mismatch between the average usage pattern of mobile devices and the time to consume one content item in a MOOC. Micro learning builds on bite-sized learning material and focusses on short-term learning sessions. This work examines the potential of micro learning activities in the context of MOOCs. Therefore, a framework for video-based micro learning is presented, which features a personalized curriculum. Videos are suggested to the user in a non-linear order that is determined by content dependencies, users’ preferences and watched videos, as well as explicit and implicit user feedback. A mobile application was implemented to test the approach with restructured MOOC content resulting in 58 connected short videos about engineering education – e.g. web technologies and programming languages. The usage data indicates initial curiosity by the users. To improve retention rates, more user motivation will be required for future studies. A survey gathered additional qualitative feedback. While the content suggestions were seen as a vital feature for such an approach, the results showed good interest and acceptance rates to create a better learning experience for MOOCs on mobile devices.
• 
  Rohloff, T., Oldag, S., Renz, J., Meinel, C.: Utilizing Web Analytics in the Context of Learning Analytics for Large-Scale Online Learning.IEEE Global Engineering Education Conference (EDUCON 2019). p. 296--305. IEEE (2019).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Today, Web Analytics (WA) is commonly used to obtain key information about users and their behavior on websites. Besides, with the rise of online learning, Learning Analytics (LA) emerged as a separate research field for collecting and analyzing learners’ interactions on online learning platforms. Although the foundation of both methods is similar, WA has not been profoundly used for LA purposes. However, especially large-scale online learning environments may benefit from WA as it is more sophisticated and well-established in comparison to LA. Therefore, this paper aims to examine to what extent WA can be utilized in this context, without compromising the learners’ data privacy. For this purpose, Google Analytics was integrated into the Massive Open Online Course platform of the Hasso Plattner Institute as a proof of concept. It was tested with two deployments of the platform: openHPI and openSAP, where thousands of learners gain academic and industry knowledge about engineering education. Besides capturing behavioral data, the platforms’ existing LA dashboards were extended by WA metrics. The evaluation of the integration showed that WA covers a large part of the relevant metrics and is particularly suitable for obtaining an overview of the platform’s global activity, but reaches its limitations when it comes to learner-specific metrics.
  @inproceedings{Rohloff2019WebAnalytics, abstract = {Today, Web Analytics (WA) is commonly used to obtain key information about users and their behavior on websites. Besides, with the rise of online learning, Learning Analytics (LA) emerged as a separate research field for collecting and analyzing learners’ interactions on online learning platforms. Although the foundation of both methods is similar, WA has not been profoundly used for LA purposes. However, especially large-scale online learning environments may benefit from WA as it is more sophisticated and well-established in comparison to LA. Therefore, this paper aims to examine to what extent WA can be utilized in this context, without compromising the learners’ data privacy. For this purpose, Google Analytics was integrated into the Massive Open Online Course platform of the Hasso Plattner Institute as a proof of concept. It was tested with two deployments of the platform: openHPI and openSAP, where thousands of learners gain academic and industry knowledge about engineering education. Besides capturing behavioral data, the platforms’ existing LA dashboards were extended by WA metrics. The evaluation of the integration showed that WA covers a large part of the relevant metrics and is particularly suitable for obtaining an overview of the platform’s global activity, but reaches its limitations when it comes to learner-specific metrics.}, author = {Rohloff, Tobias and Oldag, Sören and Renz, Jan and Meinel, Christoph}, booktitle = {IEEE Global Engineering Education Conference (EDUCON 2019)}, keywords = {moocs learninganalytics}, pages = {296–305}, publisher = {IEEE}, title = {Utilizing Web Analytics in the Context of Learning Analytics for Large-Scale Online Learning}, year = 2019 }
  Further Information

  URNhttp://dx.doi.org/10.1109/EDUCON.2019.8725118

  AbstractToday, Web Analytics (WA) is commonly used to obtain key information about users and their behavior on websites. Besides, with the rise of online learning, Learning Analytics (LA) emerged as a separate research field for collecting and analyzing learners’ interactions on online learning platforms. Although the foundation of both methods is similar, WA has not been profoundly used for LA purposes. However, especially large-scale online learning environments may benefit from WA as it is more sophisticated and well-established in comparison to LA. Therefore, this paper aims to examine to what extent WA can be utilized in this context, without compromising the learners’ data privacy. For this purpose, Google Analytics was integrated into the Massive Open Online Course platform of the Hasso Plattner Institute as a proof of concept. It was tested with two deployments of the platform: openHPI and openSAP, where thousands of learners gain academic and industry knowledge about engineering education. Besides capturing behavioral data, the platforms’ existing LA dashboards were extended by WA metrics. The evaluation of the integration showed that WA covers a large part of the relevant metrics and is particularly suitable for obtaining an overview of the platform’s global activity, but reaches its limitations when it comes to learner-specific metrics.
• 
  Rohloff, T., Sauer, D., Meinel, C.: On the Acceptance and Usefulness of Personalized Learning Objectives in MOOCs.Proceedings of the Sixth ACM Conference on Learning at Scale (L@S 2019). p. 4:1--4:10. Association for Computing Machinery (2019).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  With Massive Open Online Courses (MOOCs) the number of people having access to higher education increased rapidly. The intentions to enroll for a specific course vary significantly and depend on one's professional or personal learning needs and interests. All learners have in common that they pursue their individual learning objectives. However, predominant MOOC platforms follow a one-size-fits-all approach and primarily aim for completion with certification. Specifically, technical support for goal-oriented and self-regulated learning to date is very limited in this context although both learning strategies are proven to be key factors for students' achievement in large-scale online learning environments. In this first investigation, a concept for the application and technical integration of personalized learning objectives in a MOOC platform is realized and assessed. It is evaluated with a mixed-method approach. First, the learners' acceptance is examined with a multivariate A/B test in two courses. Second, a survey was conducted to gather further feedback about the perceived usefulness, next to the acceptance. The results show a positive perception by the learners, which paves the way for future research.
  @inproceedings{Rohloff2019LearningObjectivesAcceptance, abstract = {With Massive Open Online Courses (MOOCs) the number of people having access to higher education increased rapidly. The intentions to enroll for a specific course vary significantly and depend on one's professional or personal learning needs and interests. All learners have in common that they pursue their individual learning objectives. However, predominant MOOC platforms follow a one-size-fits-all approach and primarily aim for completion with certification. Specifically, technical support for goal-oriented and self-regulated learning to date is very limited in this context although both learning strategies are proven to be key factors for students' achievement in large-scale online learning environments. In this first investigation, a concept for the application and technical integration of personalized learning objectives in a MOOC platform is realized and assessed. It is evaluated with a mixed-method approach. First, the learners' acceptance is examined with a multivariate A/B test in two courses. Second, a survey was conducted to gather further feedback about the perceived usefulness, next to the acceptance. The results show a positive perception by the learners, which paves the way for future research.}, author = {Rohloff, Tobias and Sauer, Dominic and Meinel, Christoph}, booktitle = {Proceedings of the Sixth ACM Conference on Learning at Scale (L@S 2019)}, keywords = {moocs learningobjectives}, pages = {4:1–4:10}, publisher = {Association for Computing Machinery}, title = {On the Acceptance and Usefulness of Personalized Learning Objectives in MOOCs}, year = 2019 }
  Further Information

  URNhttp://dx.doi.org/10.1145/3330430.3333624

  AbstractWith Massive Open Online Courses (MOOCs) the number of people having access to higher education increased rapidly. The intentions to enroll for a specific course vary significantly and depend on one's professional or personal learning needs and interests. All learners have in common that they pursue their individual learning objectives. However, predominant MOOC platforms follow a one-size-fits-all approach and primarily aim for completion with certification. Specifically, technical support for goal-oriented and self-regulated learning to date is very limited in this context although both learning strategies are proven to be key factors for students' achievement in large-scale online learning environments. In this first investigation, a concept for the application and technical integration of personalized learning objectives in a MOOC platform is realized and assessed. It is evaluated with a mixed-method approach. First, the learners' acceptance is examined with a multivariate A/B test in two courses. Second, a survey was conducted to gather further feedback about the perceived usefulness, next to the acceptance. The results show a positive perception by the learners, which paves the way for future research.
• 
  John, C.T., Staubitz, T., Meinel, C.: Took a MOOC. Got a Certificate. What now?2019 IEEE Frontiers in Education Conference (FIE) (2019).
  [ BibTeX ] [ Details ]
   
  @inproceedings{john_fie_2019, author = {John, Catrina Tamara and Staubitz, Thomas and Meinel, Christoph}, booktitle = {2019 IEEE Frontiers in Education Conference (FIE)}, keywords = {e-learning myown mooc certificate}, month = {oct}, title = {Took a MOOC. Got a Certificate. What now?}, year = 2019 }
  Further Information
• 
  Staubitz, T., Meinel, C.: Graded Team Assignments in MOOCs: Effects of Team Composition and Further Factors on Team Dropout Rates and Performance.Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale. p. 5:1--5:10. ACM, Chicago, IL, USA (2019).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  The ability to work in teams is an important skill in today's work environments. In MOOCs, however, team work, team tasks, and graded team-based assignments play only a marginal role. To close this gap, we have been exploring ways to integrate graded team-based assignments in MOOCs. Some goals of our work are to determine simple criteria to match teams in a volatile environment and to enable a frictionless online collaboration for the participants within our MOOC platform. The high dropout rates in MOOCs pose particular challenges for team work in this context. By now, we have conducted 15 MOOCs containing graded team-based assignments in a variety of topics. The paper at hand presents a study that aims to establish a solid understanding of the participants in the team tasks. Furthermore, we attempt to determine which team compositions are particularly successful. Finally, we examine how several modifications to our platform's collaborative toolset have affected the dropout rates and performance of the teams.
  @inproceedings{Staubitz:2019:GTA:3330430.3333619, abstract = {The ability to work in teams is an important skill in today's work environments. In MOOCs, however, team work, team tasks, and graded team-based assignments play only a marginal role. To close this gap, we have been exploring ways to integrate graded team-based assignments in MOOCs. Some goals of our work are to determine simple criteria to match teams in a volatile environment and to enable a frictionless online collaboration for the participants within our MOOC platform. The high dropout rates in MOOCs pose particular challenges for team work in this context. By now, we have conducted 15 MOOCs containing graded team-based assignments in a variety of topics. The paper at hand presents a study that aims to establish a solid understanding of the participants in the team tasks. Furthermore, we attempt to determine which team compositions are particularly successful. Finally, we examine how several modifications to our platform's collaborative toolset have affected the dropout rates and performance of the teams.}, address = {New York, NY, USA}, author = {Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale}, keywords = {e-learning myown assessment mooc teamwork}, pages = {5:1–5:10}, publisher = {ACM}, series = {L@S '19}, title = {Graded Team Assignments in MOOCs: Effects of Team Composition and Further Factors on Team Dropout Rates and Performance}, year = 2019 }
  Further Information

  URNhttp://dx.doi.org/10.1145/3330430.3333619

  AbstractThe ability to work in teams is an important skill in today's work environments. In MOOCs, however, team work, team tasks, and graded team-based assignments play only a marginal role. To close this gap, we have been exploring ways to integrate graded team-based assignments in MOOCs. Some goals of our work are to determine simple criteria to match teams in a volatile environment and to enable a frictionless online collaboration for the participants within our MOOC platform. The high dropout rates in MOOCs pose particular challenges for team work in this context. By now, we have conducted 15 MOOCs containing graded team-based assignments in a variety of topics. The paper at hand presents a study that aims to establish a solid understanding of the participants in the team tasks. Furthermore, we attempt to determine which team compositions are particularly successful. Finally, we examine how several modifications to our platform's collaborative toolset have affected the dropout rates and performance of the teams.
• 
  Traifeh, H., Staubitz, T., Meinel, C.: Improving learner experience and participation in MOOCs: A design thinking approach.2019 Learning With MOOCS (LWMOOCS) (2019).
  [ BibTeX ] [ Details ]
   
  @inproceedings{traifeh_lwmoocs_2019, author = {Traifeh, Hanadi and Staubitz, Thomas and Meinel, Christoph}, booktitle = {2019 Learning With MOOCS (LWMOOCS)}, keywords = {e-learning myown mooc teamwork}, month = {Oct.}, title = {Improving learner experience and participation in MOOCs: A design thinking approach}, year = 2019 }
  Further Information
• 
  John, C.T., Staubitz, T., Meinel, C.: Performance of Men and Women in Graded Team Assignments in MOOCs.2019 Learning With MOOCS (LWMOOCS) (2019).
  [ BibTeX ] [ Details ]
   
  @inproceedings{john_lwmoocs_2019, author = {John, Catrina Tamara and Staubitz, Thomas and Meinel, Christoph}, booktitle = {2019 Learning With MOOCS (LWMOOCS)}, keywords = {e-learning myown mooc teamwork}, month = {Oct.}, title = {Performance of Men and Women in Graded Team Assignments in MOOCs}, year = 2019 }
  Further Information
• 
  von Schmieden, K., Staubitz, T., Mayer, L., Meinel, C.: Skill Confidence Ratings in a MOOC: Examining the Link between Skill Confidence and Learner Development.CSEDU (2019).
  [ BibTeX ] [ Details ]
   
  @inproceedings{Schmieden2019SkillCR, author = {von Schmieden, Karen and Staubitz, Thomas and Mayer, Lena and Meinel, Christoph}, booktitle = {CSEDU}, keywords = {e-learning myown assessment mooc}, title = {Skill Confidence Ratings in a MOOC: Examining the Link between Skill Confidence and Learner Development}, year = 2019 }
  Further Information
• 
  Rohloff, T., Sauer, D., Meinel, C.: Student Perception of a Learner Dashboard in MOOCs to Encourage Self-Regulated Learning.IEEE International Conference on Engineering, Technology and Education (TALE 2019). IEEE (2019).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In online learning environments like Massive Open Online Courses (MOOCs), where teachers cannot provide individual support and guidance for thousands of students, self-regulated learning (SRL) is a critical metacognitive skillset for students’ achievement. However, not every student intuitively self-regulates its learning and therefore technical solutions can help to apply SRL strategies. Learner dashboards with visualizations about the learner’s progress and behavior are able to create awareness, encourage self-reflection, and perhaps motivate students to plan and adjust their learning behavior to achieve their learning objectives. Hence, such Learning Analytics tools can support the SRL strategies self-evaluation and strategic planning. To examine this potential, a learner dashboard was integrated into the HPI MOOC platform. This work presents the design process, the concept, and an evaluation of the first dashboard iteration. The perceived usefulness and usability are investigated, and in addition, the question will be considered whether the dashboard encourages students to apply self-regulated learning. The positive results pave the way for future research and a next iteration of the learner dashboard.
  @inproceedings{Rohloff2019LearnerDashboard, abstract = {In online learning environments like Massive Open Online Courses (MOOCs), where teachers cannot provide individual support and guidance for thousands of students, self-regulated learning (SRL) is a critical metacognitive skillset for students’ achievement. However, not every student intuitively self-regulates its learning and therefore technical solutions can help to apply SRL strategies. Learner dashboards with visualizations about the learner’s progress and behavior are able to create awareness, encourage self-reflection, and perhaps motivate students to plan and adjust their learning behavior to achieve their learning objectives. Hence, such Learning Analytics tools can support the SRL strategies self-evaluation and strategic planning. To examine this potential, a learner dashboard was integrated into the HPI MOOC platform. This work presents the design process, the concept, and an evaluation of the first dashboard iteration. The perceived usefulness and usability are investigated, and in addition, the question will be considered whether the dashboard encourages students to apply self-regulated learning. The positive results pave the way for future research and a next iteration of the learner dashboard.}, author = {Rohloff, Tobias and Sauer, Dominic and Meinel, Christoph}, booktitle = {IEEE International Conference on Engineering, Technology and Education (TALE 2019)}, keywords = {Technology-EnhancedLearning Self-RegulatedLearning myown LearningAnalytics moocs learninganalyticsLearnerDashboard MOOCs}, publisher = {IEEE}, title = {Student Perception of a Learner Dashboard in MOOCs to Encourage Self-Regulated Learning}, year = 2019 }
  Further Information

  URNhttp://dx.doi.org/10.1109/TALE48000.2019.9225939

  AbstractIn online learning environments like Massive Open Online Courses (MOOCs), where teachers cannot provide individual support and guidance for thousands of students, self-regulated learning (SRL) is a critical metacognitive skillset for students’ achievement. However, not every student intuitively self-regulates its learning and therefore technical solutions can help to apply SRL strategies. Learner dashboards with visualizations about the learner’s progress and behavior are able to create awareness, encourage self-reflection, and perhaps motivate students to plan and adjust their learning behavior to achieve their learning objectives. Hence, such Learning Analytics tools can support the SRL strategies self-evaluation and strategic planning. To examine this potential, a learner dashboard was integrated into the HPI MOOC platform. This work presents the design process, the concept, and an evaluation of the first dashboard iteration. The perceived usefulness and usability are investigated, and in addition, the question will be considered whether the dashboard encourages students to apply self-regulated learning. The positive results pave the way for future research and a next iteration of the learner dashboard.
• 
  Bothe, M., Rohloff, T., Meinel, C.: A Quantitative Study on the Effects of Learning with Mobile Devices in MOOCs.2019 IEEE International Conference on Engineering, Technology and Education (TALE). pp. 1-7 (2019).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Massive Open Online Course (MOOC) platforms were initially designed for a desktop learning experience delivered via the Internet. With the increasing acceptance of mobile devices, learners started accessing the MOOC platforms through the browser application on their smartphones and tablets. However, native mobile applications offer better system integration and enhance the learning experience. As the concept of mobile-assisted seamless learning emphasizes the ubiquitous access to learning material, the relevance of mobile devices in the learning process will increase further. This paper investigates the different learning behaviors when using mobile devices on the HPI MOOC platform. For this, influencing aspects, that can not always be controlled by the learner, are examined for native applications and mobile websites-such as the size of the screen and the current network state of the mobile device. The results of a quantitative study show highly significant differences between the usage of native applications, mobile websites, and the overall average of the HPI MOOC platform. It was proven that the size of the screen has a large practical effect when using native applications. Furthermore, course items and videos are more often consumed when the device is connected to a WiFi network. This study creates the basis for future research to improve the support of mobile-assisted seamless learning methods for MOOCs.
  @inproceedings{9226023, abstract = {Massive Open Online Course (MOOC) platforms were initially designed for a desktop learning experience delivered via the Internet. With the increasing acceptance of mobile devices, learners started accessing the MOOC platforms through the browser application on their smartphones and tablets. However, native mobile applications offer better system integration and enhance the learning experience. As the concept of mobile-assisted seamless learning emphasizes the ubiquitous access to learning material, the relevance of mobile devices in the learning process will increase further. This paper investigates the different learning behaviors when using mobile devices on the HPI MOOC platform. For this, influencing aspects, that can not always be controlled by the learner, are examined for native applications and mobile websites-such as the size of the screen and the current network state of the mobile device. The results of a quantitative study show highly significant differences between the usage of native applications, mobile websites, and the overall average of the HPI MOOC platform. It was proven that the size of the screen has a large practical effect when using native applications. Furthermore, course items and videos are more often consumed when the device is connected to a WiFi network. This study creates the basis for future research to improve the support of mobile-assisted seamless learning methods for MOOCs.}, author = {{Bothe}, M. and {Rohloff}, T. and {Meinel}, C.}, booktitle = {2019 IEEE International Conference on Engineering, Technology and Education (TALE)}, keywords = {myown mobilelearning technologyenhancedlearning moocs mobileassistedseamlesslearning}, pages = {1-7}, title = {A Quantitative Study on the Effects of Learning with Mobile Devices in MOOCs}, year = 2019 }
  Further Information

  URNhttp://dx.doi.org/10.1109/TALE48000.2019.9226023

  AbstractMassive Open Online Course (MOOC) platforms were initially designed for a desktop learning experience delivered via the Internet. With the increasing acceptance of mobile devices, learners started accessing the MOOC platforms through the browser application on their smartphones and tablets. However, native mobile applications offer better system integration and enhance the learning experience. As the concept of mobile-assisted seamless learning emphasizes the ubiquitous access to learning material, the relevance of mobile devices in the learning process will increase further. This paper investigates the different learning behaviors when using mobile devices on the HPI MOOC platform. For this, influencing aspects, that can not always be controlled by the learner, are examined for native applications and mobile websites-such as the size of the screen and the current network state of the mobile device. The results of a quantitative study show highly significant differences between the usage of native applications, mobile websites, and the overall average of the HPI MOOC platform. It was proven that the size of the screen has a large practical effect when using native applications. Furthermore, course items and videos are more often consumed when the device is connected to a WiFi network. This study creates the basis for future research to improve the support of mobile-assisted seamless learning methods for MOOCs.

2018 [ to top ]

• 
  Rohloff, T., Meinel, C.: Towards Personalized Learning Objectives in MOOCs. In: Pammer-Schindler, V., Pérez-Sanagustín, M., Drachsler, H., Elferink, R., and Scheffel, M. (eds.) Lifelong Technology-Enhanced Learning (EC-TEL 2018). p. 202--215. Springer International Publishing (2018).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Instead of measuring success in Massive Open Online Courses (MOOCs) based on certification and completion-rates, researchers started to define success with alternative metrics recently, for example by evaluating the intention-behavior gap and goal achievement. Especially self-regulated and goal-oriented learning have been identified as critical skills to be successful in online learning environments with low guidance like MOOCs, but technical support is rare. Therefore, this paper examines the current technical capabilities and limitations of goal-oriented learning in MOOCs. An observational study to explore how well learners in five MOOCs achieved their initial learning objectives was conducted, and the results are compared with similar studies. Afterwards, a concept with a focus on technical feasibility and automation outlines how personalized learning objectives can be supported and implemented on a MOOC platform.
  @inproceedings{Rohloff2018LearningObjectives, abstract = {Instead of measuring success in Massive Open Online Courses (MOOCs) based on certification and completion-rates, researchers started to define success with alternative metrics recently, for example by evaluating the intention-behavior gap and goal achievement. Especially self-regulated and goal-oriented learning have been identified as critical skills to be successful in online learning environments with low guidance like MOOCs, but technical support is rare. Therefore, this paper examines the current technical capabilities and limitations of goal-oriented learning in MOOCs. An observational study to explore how well learners in five MOOCs achieved their initial learning objectives was conducted, and the results are compared with similar studies. Afterwards, a concept with a focus on technical feasibility and automation outlines how personalized learning objectives can be supported and implemented on a MOOC platform.}, author = {Rohloff, Tobias and Meinel, Christoph}, booktitle = {Lifelong Technology-Enhanced Learning (EC-TEL 2018)}, editor = {Pammer-Schindler, Viktoria and P{é}rez-Sanagust{í}n, Mar and Drachsler, Henrik and Elferink, Raymond and Scheffel, Maren}, keywords = {moocs learningobjectives}, pages = {202–215}, publisher = {Springer International Publishing}, title = {Towards Personalized Learning Objectives in MOOCs}, year = 2018 }
  Further Information

  Editor(s)Pammer-Schindler, Viktoria and Pérez-Sanagustín, Mar and Drachsler, Henrik and Elferink, Raymond and Scheffel, Maren

  URNhttp://dx.doi.org/10.1007/978-3-319-98572-5_16

  AbstractInstead of measuring success in Massive Open Online Courses (MOOCs) based on certification and completion-rates, researchers started to define success with alternative metrics recently, for example by evaluating the intention-behavior gap and goal achievement. Especially self-regulated and goal-oriented learning have been identified as critical skills to be successful in online learning environments with low guidance like MOOCs, but technical support is rare. Therefore, this paper examines the current technical capabilities and limitations of goal-oriented learning in MOOCs. An observational study to explore how well learners in five MOOCs achieved their initial learning objectives was conducted, and the results are compared with similar studies. Afterwards, a concept with a focus on technical feasibility and automation outlines how personalized learning objectives can be supported and implemented on a MOOC platform.
• 
  Rohloff, T., Utunen, H., Renz, J., Zhao, Y., Gamhewage, G., Meinel, C.: OpenWHO: Integrating Online Knowledge Transfer into Health Emergency Response. In: Dimitrova, V., Praharaj, S., Fominykh, M., and Drachsler, H. (eds.) Practitioner Proceedings of the 13th European Conference On Technology Enhanced Learning (EC-TEL 2018). CEUR-WS.org (2018).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  The platform OpenWHO was developed in 2017 in a cooperation between the World Health Organization (WHO) and the Hasso Plattner Institute (HPI). The Department of Infectious Hazard Management, under the WHO Health Emergencies Programme, worked together with the HPI to create a new interactive, web-based, knowledge-transfer platform offering online courses to improve the response to health emergencies. The platform was newly launched as there was an identified need of an open and scalable solution for fast distribution of life-saving content in disease outbreaks for frontline responders. The platform provides adjusted versions of the massive open online learning resources that are self-paced and at ease formats for the frontline and low-bandwidth use. The HPI already developed know-how in previous Massive Open Online Course (MOOC) projects like openHPI and openSAP. OpenWHO is based on the same technology as the aforementioned projects. This paper will provide insights into the practical deployment, the adaption of the MOOC concept, and lessons learnt within the first year of this platform.
  @inproceedings{Rohloff2018OpenWHO, abstract = {The platform OpenWHO was developed in 2017 in a cooperation between the World Health Organization (WHO) and the Hasso Plattner Institute (HPI). The Department of Infectious Hazard Management, under the WHO Health Emergencies Programme, worked together with the HPI to create a new interactive, web-based, knowledge-transfer platform offering online courses to improve the response to health emergencies. The platform was newly launched as there was an identified need of an open and scalable solution for fast distribution of life-saving content in disease outbreaks for frontline responders. The platform provides adjusted versions of the massive open online learning resources that are self-paced and at ease formats for the frontline and low-bandwidth use. The HPI already developed know-how in previous Massive Open Online Course (MOOC) projects like openHPI and openSAP. OpenWHO is based on the same technology as the aforementioned projects. This paper will provide insights into the practical deployment, the adaption of the MOOC concept, and lessons learnt within the first year of this platform.}, author = {Rohloff, Tobias and Utunen, Heini and Renz, Jan and Zhao, Yu and Gamhewage, Gaya and Meinel, Christoph}, booktitle = {Practitioner Proceedings of the 13th European Conference On Technology Enhanced Learning (EC-TEL 2018)}, editor = {Dimitrova, Vania and Praharaj, Sambit and Fominykh, Mikhail and Drachsler, Hendrik}, keywords = {healthemergencies moocs}, publisher = {CEUR-WS.org}, title = {OpenWHO: Integrating Online Knowledge Transfer into Health Emergency Response}, year = 2018 }
  Further Information

  Editor(s)Dimitrova, Vania and Praharaj, Sambit and Fominykh, Mikhail and Drachsler, Hendrik

  AbstractThe platform OpenWHO was developed in 2017 in a cooperation between the World Health Organization (WHO) and the Hasso Plattner Institute (HPI). The Department of Infectious Hazard Management, under the WHO Health Emergencies Programme, worked together with the HPI to create a new interactive, web-based, knowledge-transfer platform offering online courses to improve the response to health emergencies. The platform was newly launched as there was an identified need of an open and scalable solution for fast distribution of life-saving content in disease outbreaks for frontline responders. The platform provides adjusted versions of the massive open online learning resources that are self-paced and at ease formats for the frontline and low-bandwidth use. The HPI already developed know-how in previous Massive Open Online Course (MOOC) projects like openHPI and openSAP. OpenWHO is based on the same technology as the aforementioned projects. This paper will provide insights into the practical deployment, the adaption of the MOOC concept, and lessons learnt within the first year of this platform.
• 
  Rohloff, T., Bothe, M., Renz, J., Meinel, C.: Towards a Better Understanding of Mobile Learning in MOOCs.IEEE Learning with MOOCs Conference (LWMOOCs 2018). IEEE (2018).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  The pervasive presence of mobile devices and growing trends like ubiquitous learning make new demands on Massive Open Online Courses (MOOCs). Users learn increasingly on the go and with multiple devices, instead of being tied to a fixed workstation. However, there is a lack of research how the usage of mobile devices influences the learning behavior and outcome in MOOCs. Thus, this paper presents a first quantitative study to examine this question. To enable a statistical analysis, a proof-of-concept implementation outline is presented, which enhances the Learning Analytics capabilities of the openHPI MOOC platform with contextual data to process various learning behavior metrics. Based on an analysis of four courses, it was found that users who additionally learnt with mobile applications showed a higher engagement with the learning material and completed the course more often. Nevertheless, the reasoning must be addressed with qualitative analyses in future, to better support their learning process and success on mobile and stationary devices.
  @inproceedings{Rohloff2018Mobile, abstract = {The pervasive presence of mobile devices and growing trends like ubiquitous learning make new demands on Massive Open Online Courses (MOOCs). Users learn increasingly on the go and with multiple devices, instead of being tied to a fixed workstation. However, there is a lack of research how the usage of mobile devices influences the learning behavior and outcome in MOOCs. Thus, this paper presents a first quantitative study to examine this question. To enable a statistical analysis, a proof-of-concept implementation outline is presented, which enhances the Learning Analytics capabilities of the openHPI MOOC platform with contextual data to process various learning behavior metrics. Based on an analysis of four courses, it was found that users who additionally learnt with mobile applications showed a higher engagement with the learning material and completed the course more often. Nevertheless, the reasoning must be addressed with qualitative analyses in future, to better support their learning process and success on mobile and stationary devices.}, author = {Rohloff, Tobias and Bothe, Max and Renz, Jan and Meinel, Christoph}, booktitle = {IEEE Learning with MOOCs Conference (LWMOOCs 2018)}, keywords = {mobilelearning moocs learninganalytics}, publisher = {IEEE}, title = {Towards a Better Understanding of Mobile Learning in MOOCs}, year = 2018 }
  Further Information

  URNhttp://dx.doi.org/10.1109/LWMOOCS.2018.8534685

  AbstractThe pervasive presence of mobile devices and growing trends like ubiquitous learning make new demands on Massive Open Online Courses (MOOCs). Users learn increasingly on the go and with multiple devices, instead of being tied to a fixed workstation. However, there is a lack of research how the usage of mobile devices influences the learning behavior and outcome in MOOCs. Thus, this paper presents a first quantitative study to examine this question. To enable a statistical analysis, a proof-of-concept implementation outline is presented, which enhances the Learning Analytics capabilities of the openHPI MOOC platform with contextual data to process various learning behavior metrics. Based on an analysis of four courses, it was found that users who additionally learnt with mobile applications showed a higher engagement with the learning material and completed the course more often. Nevertheless, the reasoning must be addressed with qualitative analyses in future, to better support their learning process and success on mobile and stationary devices.
• 
  Staubitz, T., Meinel, C.: Team based assignments in MOOCs: results and observations.Proceedings of the Fifth Annual ACM Conference on Learning at Scale, London, UK, June 26-28, 2018. p. 47:1--47:4 (2018).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Teamwork and collaborative learning are considered superior to learning individually by many instructors and didactical theories. Particularly, in the context of e-learning and Massive Open Online Courses (MOOCs) we see great benefits but also great challenges for both, learners and instructors. We discuss our experience with six team based assignments on the openHPI and openSAP1 MOOC platforms.
  @inproceedings{DBLP:conf/lats/StaubitzM18, abstract = {Teamwork and collaborative learning are considered superior to learning individually by many instructors and didactical theories. Particularly, in the context of e-learning and Massive Open Online Courses (MOOCs) we see great benefits but also great challenges for both, learners and instructors. We discuss our experience with six team based assignments on the openHPI and openSAP1 MOOC platforms.}, author = {Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proceedings of the Fifth Annual {ACM} Conference on Learning at Scale, London, UK, June 26-28, 2018}, crossref = {DBLP:conf/lats/2018}, keywords = {e-learning myown assessment mooc teamwork assignment collaboration}, pages = {47:1–47:4}, title = {Team based assignments in MOOCs: results and observations}, year = 2018 }
  Further Information

  URNhttp://dx.doi.org/10.1145/3231644.3231705

  AbstractTeamwork and collaborative learning are considered superior to learning individually by many instructors and didactical theories. Particularly, in the context of e-learning and Massive Open Online Courses (MOOCs) we see great benefits but also great challenges for both, learners and instructors. We discuss our experience with six team based assignments on the openHPI and openSAP1 MOOC platforms.
• 
  Staubitz, T., Traifeh, H., Meinel, C.: Team-Based Assignments in MOOCs - User Feedback.2018 Learning With MOOCS (LWMOOCS). pp. 39-42 (2018).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  With the increasing use of graded team-based assignments on our MOOC platforms-openHPI, openSAP, and mooc.house-we see the need to consult the opinion of our course participants about their perception of these tasks and the sufficiency of the platform support. Since we introduced the feature in May 2016, seven courses that included team-based assignments have been conducted on our platforms. In four of these courses, we have conducted qualitative and quantitative surveys among the participants. The paper at hand presents and discusses the results of these surveys.
  @inproceedings{8534607, abstract = {With the increasing use of graded team-based assignments on our MOOC platforms-openHPI, openSAP, and mooc.house-we see the need to consult the opinion of our course participants about their perception of these tasks and the sufficiency of the platform support. Since we introduced the feature in May 2016, seven courses that included team-based assignments have been conducted on our platforms. In four of these courses, we have conducted qualitative and quantitative surveys among the participants. The paper at hand presents and discusses the results of these surveys.}, author = {Staubitz, T. and Traifeh, H. and Meinel, C.}, booktitle = {2018 Learning With MOOCS (LWMOOCS)}, keywords = {e-learning myown mooc teamwork}, month = {Sept}, pages = {39-42}, title = {Team-Based Assignments in MOOCs - User Feedback}, year = 2018 }
  Further Information

  URNhttp://dx.doi.org/10.1109/LWMOOCS.2018.8534607

  AbstractWith the increasing use of graded team-based assignments on our MOOC platforms-openHPI, openSAP, and mooc.house-we see the need to consult the opinion of our course participants about their perception of these tasks and the sufficiency of the platform support. Since we introduced the feature in May 2016, seven courses that included team-based assignments have been conducted on our platforms. In four of these courses, we have conducted qualitative and quantitative surveys among the participants. The paper at hand presents and discusses the results of these surveys.
• 
  Staubitz, T., Meinel, C.: Collaborative Learning in MOOCs - Approaches and Experiments.2018 IEEE Frontiers in Education Conference (FIE). IEEE (2018).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  This Research-to-Practice paper examines the practical application of various forms of collaborative learning in MOOCs. Since 2012, about 60 MOOCs in the wider context of Information Technology and Computer Science have been conducted on our self-developed MOOC platform. The platform is also used by several customers, who either run their own platform instances or use our white label platform. We, as well as some of our partners, have experimented with different approaches in collaborative learning in these courses. Based on the results of early experiments, surveys amongst our participants, and requests by our business partners we have integrated several options to offer forms of collaborative learning to the system. The results of our experiments are directly fed back to the platform development, allowing to fine tune existing and to add new tools where necessary. In the paper at hand, we discuss the benefits and disadvantages of decisions in the design of a MOOC with regard to the various forms of collaborative learning. While the focus of the paper at hand is on forms of large group collaboration, two types of small group collaboration on our platforms are briefly introduced.
  @inproceedings{staubitz2018collaborative, abstract = {This Research-to-Practice paper examines the practical application of various forms of collaborative learning in MOOCs. Since 2012, about 60 MOOCs in the wider context of Information Technology and Computer Science have been conducted on our self-developed MOOC platform. The platform is also used by several customers, who either run their own platform instances or use our white label platform. We, as well as some of our partners, have experimented with different approaches in collaborative learning in these courses. Based on the results of early experiments, surveys amongst our participants, and requests by our business partners we have integrated several options to offer forms of collaborative learning to the system. The results of our experiments are directly fed back to the platform development, allowing to fine tune existing and to add new tools where necessary. In the paper at hand, we discuss the benefits and disadvantages of decisions in the design of a MOOC with regard to the various forms of collaborative learning. While the focus of the paper at hand is on forms of large group collaboration, two types of small group collaboration on our platforms are briefly introduced.}, author = {Staubitz, Thomas and Meinel, Christoph}, booktitle = {2018 IEEE Frontiers in Education Conference (FIE)}, keywords = {e-learning myown mooc collaboration}, month = {October}, publisher = {IEEE}, title = {Collaborative Learning in MOOCs - Approaches and Experiments}, year = 2018 }
  Further Information

  AbstractThis Research-to-Practice paper examines the practical application of various forms of collaborative learning in MOOCs. Since 2012, about 60 MOOCs in the wider context of Information Technology and Computer Science have been conducted on our self-developed MOOC platform. The platform is also used by several customers, who either run their own platform instances or use our white label platform. We, as well as some of our partners, have experimented with different approaches in collaborative learning in these courses. Based on the results of early experiments, surveys amongst our participants, and requests by our business partners we have integrated several options to offer forms of collaborative learning to the system. The results of our experiments are directly fed back to the platform development, allowing to fine tune existing and to add new tools where necessary. In the paper at hand, we discuss the benefits and disadvantages of decisions in the design of a MOOC with regard to the various forms of collaborative learning. While the focus of the paper at hand is on forms of large group collaboration, two types of small group collaboration on our platforms are briefly introduced.

2017 [ to top ]

• 
  Staubitz, T., Teusner, R., Meinel, C.: openHPI's Coding Tool Family: CodeOcean, CodeHarbor, CodePilot.Automatische Bewertung von Programmieraufgaben (ABP) (2017).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  The Hasso Plattner Institute successfully runs a self-developed Massive Open Online Course (MOOC) platform—openHPI—since 2012. MOOCs, even more than classic classroom situations, depend on automated solutions to assess programming exercises. Manual evaluation is not an option due to the massive amount of users that participate in these courses. The paper at hand maps the landscape of tools that are used on openHPI in the context of automated grading of programming exercises. Furthermore, it provides a sneak preview to new features that will be integrated ion the near future. Particularly, we will introduce CodeHarbor, our platform to share auto-gradeable exercises between various online code execution platforms.
  @inproceedings{StaubitzEtAl:ABP2017, abstract = {The Hasso Plattner Institute successfully runs a self-developed Massive Open Online Course (MOOC) platform—openHPI—since 2012. MOOCs, even more than classic classroom situations, depend on automated solutions to assess programming exercises. Manual evaluation is not an option due to the massive amount of users that participate in these courses. The paper at hand maps the landscape of tools that are used on openHPI in the context of automated grading of programming exercises. Furthermore, it provides a sneak preview to new features that will be integrated ion the near future. Particularly, we will introduce CodeHarbor, our platform to share auto-gradeable exercises between various online code execution platforms.}, author = {Staubitz, Thomas and Teusner, Ralf and Meinel, Christoph}, booktitle = {Automatische Bewertung von Programmieraufgaben (ABP)}, crossref = {ABP2017}, keywords = {MOOC Repository myown Sharing Scalability Autograder Programming Code}, title = {openHPI's Coding Tool Family: CodeOcean, CodeHarbor, CodePilot}, year = 2017 }
  Further Information

  AbstractThe Hasso Plattner Institute successfully runs a self-developed Massive Open Online Course (MOOC) platform—openHPI—since 2012. MOOCs, even more than classic classroom situations, depend on automated solutions to assess programming exercises. Manual evaluation is not an option due to the massive amount of users that participate in these courses. The paper at hand maps the landscape of tools that are used on openHPI in the context of automated grading of programming exercises. Furthermore, it provides a sneak preview to new features that will be integrated ion the near future. Particularly, we will introduce CodeHarbor, our platform to share auto-gradeable exercises between various online code execution platforms.
• 
  Staubitz, T., Willems, C., Hagedorn, C., Meinel, C.: The gamification of a MOOC platform.2017 IEEE Global Engineering Education Conference (EDUCON). pp. 883-892 (2017).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Massive Open Online Courses (MOOCs) have left their mark on the face of education during the recent couple of years. At the Hasso Plattner Institute (HPI) in Potsdam, Germany, we are actively developing a MOOC platform, which provides our research with a plethora of e-learning topics, such as learning analytics, automated assessment, peer assessment, team-work, online proctoring, and gamification. We run several instances of this platform. On openHPI, we provide our own courses from within the HPI context. Further instances are openSAP, openWHO, and mooc.HOUSE, which is the smallest of these platforms, targeting customers with a less extensive course portfolio. In 2013, we started to work on the gamification of our platform. By now, we have implemented about two thirds of the features that we initially have evaluated as useful for our purposes. About a year ago we activated the implemented gamification features on mooc.HOUSE. They have been employed actively in the course “Design for Non-Designers”. We plan to activate the features on openHPI in the beginning of 2017. The paper at hand recaps, examines, and re-evaluates our initial recommendations.
  @inproceedings{7942952, abstract = {Massive Open Online Courses (MOOCs) have left their mark on the face of education during the recent couple of years. At the Hasso Plattner Institute (HPI) in Potsdam, Germany, we are actively developing a MOOC platform, which provides our research with a plethora of e-learning topics, such as learning analytics, automated assessment, peer assessment, team-work, online proctoring, and gamification. We run several instances of this platform. On openHPI, we provide our own courses from within the HPI context. Further instances are openSAP, openWHO, and mooc.HOUSE, which is the smallest of these platforms, targeting customers with a less extensive course portfolio. In 2013, we started to work on the gamification of our platform. By now, we have implemented about two thirds of the features that we initially have evaluated as useful for our purposes. About a year ago we activated the implemented gamification features on mooc.HOUSE. They have been employed actively in the course “Design for Non-Designers”. We plan to activate the features on openHPI in the beginning of 2017. The paper at hand recaps, examines, and re-evaluates our initial recommendations.}, author = {Staubitz, T. and Willems, C. and Hagedorn, C. and Meinel, C.}, booktitle = {2017 IEEE Global Engineering Education Conference (EDUCON)}, keywords = {e-learning gamification MOOC myown}, month = {April}, pages = {883-892}, title = {The gamification of a MOOC platform}, year = 2017 }
  Further Information

  URNhttp://dx.doi.org/10.1109/EDUCON.2017.7942952

  AbstractMassive Open Online Courses (MOOCs) have left their mark on the face of education during the recent couple of years. At the Hasso Plattner Institute (HPI) in Potsdam, Germany, we are actively developing a MOOC platform, which provides our research with a plethora of e-learning topics, such as learning analytics, automated assessment, peer assessment, team-work, online proctoring, and gamification. We run several instances of this platform. On openHPI, we provide our own courses from within the HPI context. Further instances are openSAP, openWHO, and mooc.HOUSE, which is the smallest of these platforms, targeting customers with a less extensive course portfolio. In 2013, we started to work on the gamification of our platform. By now, we have implemented about two thirds of the features that we initially have evaluated as useful for our purposes. About a year ago we activated the implemented gamification features on mooc.HOUSE. They have been employed actively in the course “Design for Non-Designers”. We plan to activate the features on openHPI in the beginning of 2017. The paper at hand recaps, examines, and re-evaluates our initial recommendations.
• 
  Staubitz, T., Teusner, R., Meinel, C.: Towards a Repository for Open Auto-Gradable Programming Exercises.2017 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) (2017).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Auto-gradable hands-on programming exercises are a key element for scalable programming courses. A variety of auto-graders already exist, however, creating suitable high- quality exercises in a sufficient amount is a very time-consuming and tedious task. One way to approach this problem is to enable sharing auto-gradable exercises between several interested parties. School-teachers, MOOC1 instructors, workshop providers, and university level teachers need programming exercises to provide their students with hands-on experience. Auto-gradability of these exercises is an important requirement. The paper at hand introduces a tool that enables the sharing of such exercises and addresses the various needs and requirements of the different stakeholders.
  @inproceedings{staubitz_tale_2017, abstract = {Auto-gradable hands-on programming exercises are a key element for scalable programming courses. A variety of auto-graders already exist, however, creating suitable high- quality exercises in a sufficient amount is a very time-consuming and tedious task. One way to approach this problem is to enable sharing auto-gradable exercises between several interested parties. School-teachers, MOOC1 instructors, workshop providers, and university level teachers need programming exercises to provide their students with hands-on experience. Auto-gradability of these exercises is an important requirement. The paper at hand introduces a tool that enables the sharing of such exercises and addresses the various needs and requirements of the different stakeholders.}, author = {Staubitz, Thomas and Teusner, Ralf and Meinel, Christoph}, booktitle = {2017 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE)}, keywords = {e-learning Assignment MOOC myown Auto-Grader Assessment autograder mooc OER}, month = {December}, title = {Towards a Repository for Open Auto-Gradable Programming Exercises}, year = 2017 }
  Further Information

  AbstractAuto-gradable hands-on programming exercises are a key element for scalable programming courses. A variety of auto-graders already exist, however, creating suitable high- quality exercises in a sufficient amount is a very time-consuming and tedious task. One way to approach this problem is to enable sharing auto-gradable exercises between several interested parties. School-teachers, MOOC1 instructors, workshop providers, and university level teachers need programming exercises to provide their students with hands-on experience. Auto-gradability of these exercises is an important requirement. The paper at hand introduces a tool that enables the sharing of such exercises and addresses the various needs and requirements of the different stakeholders.
• 
  Malchow, M., Renz, J., Bauer, M., Meinel, C.: Embedded Smart Home - Remote Lab Grading in a MOOC with over 6000 Participants.2017 Annual IEEE Systems Conference (SysCon). IEEE (2017).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  The popularity of MOOCs has increased considerably in the last years. A typical MOOC course consists of video content, self tests after a video and homework, which is normally in multiple choice format. After solving this homeworks for every week of a MOOC, the final exam certificate can be issued when the student has reached a sufficient score. There are also some attempts to include practical tasks, such as programming, in MOOCs for grading. Nevertheless, until now there is no known possibility to teach embedded system programming in a MOOC course where the programming can be done in a remote lab and where grading of the tasks is additionally possible. This embedded programming includes communication over GPIO pins to control LEDs and measure sensor values. We started a MOOC course called ``Embedded Smart Home'' as a pilot to prove the concept to teach real hardware programming in a MOOC environment under real life MOOC conditions with over 6000 students. Furthermore, also students with real hardware have the possibility to program on their own real hardware and grade their results in the MOOC course. Finally, we evaluate our approach and analyze the student acceptance of this approach to offer a course on embedded programming. We also analyze the hardware usage and working time of students solving tasks to find out if real hardware programming is an advantage and motivating achievement to support students learning success.
  @inproceedings{Martin2017a, abstract = {The popularity of MOOCs has increased considerably in the last years. A typical MOOC course consists of video content, self tests after a video and homework, which is normally in multiple choice format. After solving this homeworks for every week of a MOOC, the final exam certificate can be issued when the student has reached a sufficient score. There are also some attempts to include practical tasks, such as programming, in MOOCs for grading. Nevertheless, until now there is no known possibility to teach embedded system programming in a MOOC course where the programming can be done in a remote lab and where grading of the tasks is additionally possible. This embedded programming includes communication over GPIO pins to control LEDs and measure sensor values. We started a MOOC course called ``Embedded Smart Home'' as a pilot to prove the concept to teach real hardware programming in a MOOC environment under real life MOOC conditions with over 6000 students. Furthermore, also students with real hardware have the possibility to program on their own real hardware and grade their results in the MOOC course. Finally, we evaluate our approach and analyze the student acceptance of this approach to offer a course on embedded programming. We also analyze the hardware usage and working time of students solving tasks to find out if real hardware programming is an advantage and motivating achievement to support students learning success.}, author = {Malchow, Martin and Renz, Jan and Bauer, Matthias and Meinel, Christoph}, booktitle = {2017 Annual IEEE Systems Conference (SysCon)}, keywords = {Video_Lecture Tele-Lecturing E-Learning its Self-Paced_Learning Lecture_Video_Archive Video_Playlist web_university Distance_Learning Teleteaching}, month = 4, publisher = {IEEE}, title = {Embedded Smart Home - Remote Lab Grading in a MOOC with over 6000 Participants}, year = 2017 }
  Further Information

  AbstractThe popularity of MOOCs has increased considerably in the last years. A typical MOOC course consists of video content, self tests after a video and homework, which is normally in multiple choice format. After solving this homeworks for every week of a MOOC, the final exam certificate can be issued when the student has reached a sufficient score. There are also some attempts to include practical tasks, such as programming, in MOOCs for grading. Nevertheless, until now there is no known possibility to teach embedded system programming in a MOOC course where the programming can be done in a remote lab and where grading of the tasks is additionally possible. This embedded programming includes communication over GPIO pins to control LEDs and measure sensor values. We started a MOOC course called ``Embedded Smart Home'' as a pilot to prove the concept to teach real hardware programming in a MOOC environment under real life MOOC conditions with over 6000 students. Furthermore, also students with real hardware have the possibility to program on their own real hardware and grade their results in the MOOC course. Finally, we evaluate our approach and analyze the student acceptance of this approach to offer a course on embedded programming. We also analyze the hardware usage and working time of students solving tasks to find out if real hardware programming is an advantage and motivating achievement to support students learning success.
• 
  Staubitz, T., Meinel, C.: Collaboration and Teamwork on a MOOC Platform: A Toolset.Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale. p. 165--168. ACM, Cambridge, Massachusetts, USA (2017).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Teamwork is an an important topic in education. It fosters deep learning and allows educators to assign interesting tasks, which would be too complex to be solved by single participants due to the time restrictions defined by the context of a course.Furthermore, today's jobs require an increasing amount of team skills. On the other hand, teamwork comes with a variety of issues of its own. Particularly in large scale settings, such as MOOCs, teamwork is challenging. Courses often end with dysfunctional teams due to drop-outs or insufficient matching. The paper at hand presents a set of three tools that we have recently added to our system to enable teamwork in our courses. This toolset consists of the TeamBuilder, a tool to match successful teams based on a variable set of parameters, CollabSpaces, providing teams with a secluded area to communicate and collaborate within the course context, and a TeamPeerAssessment tool, which allows to provide teams with complex tasks and which allows assessment that sufficiently scales for the MOOC context. The presented tools are evaluated in terms of success rates of the created teams and workload reduction for the courses' teaching teams.
  @inproceedings{Staubitz:2017:CTM:3051457.3053975, abstract = {Teamwork is an an important topic in education. It fosters deep learning and allows educators to assign interesting tasks, which would be too complex to be solved by single participants due to the time restrictions defined by the context of a course.Furthermore, today's jobs require an increasing amount of team skills. On the other hand, teamwork comes with a variety of issues of its own. Particularly in large scale settings, such as MOOCs, teamwork is challenging. Courses often end with dysfunctional teams due to drop-outs or insufficient matching. The paper at hand presents a set of three tools that we have recently added to our system to enable teamwork in our courses. This toolset consists of the TeamBuilder, a tool to match successful teams based on a variable set of parameters, CollabSpaces, providing teams with a secluded area to communicate and collaborate within the course context, and a TeamPeerAssessment tool, which allows to provide teams with complex tasks and which allows assessment that sufficiently scales for the MOOC context. The presented tools are evaluated in terms of success rates of the created teams and workload reduction for the courses' teaching teams.}, address = {New York, NY, USA}, author = {Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale}, keywords = {myown mooc teamwork collaboration peerassessment}, pages = {165–168}, publisher = {ACM}, series = {L@S '17}, title = {Collaboration and Teamwork on a MOOC Platform: A Toolset}, year = 2017 }
  Further Information

  URNhttp://dx.doi.org/10.1145/3051457.3053975

  AbstractTeamwork is an an important topic in education. It fosters deep learning and allows educators to assign interesting tasks, which would be too complex to be solved by single participants due to the time restrictions defined by the context of a course.Furthermore, today's jobs require an increasing amount of team skills. On the other hand, teamwork comes with a variety of issues of its own. Particularly in large scale settings, such as MOOCs, teamwork is challenging. Courses often end with dysfunctional teams due to drop-outs or insufficient matching. The paper at hand presents a set of three tools that we have recently added to our system to enable teamwork in our courses. This toolset consists of the TeamBuilder, a tool to match successful teams based on a variable set of parameters, CollabSpaces, providing teams with a secluded area to communicate and collaborate within the course context, and a TeamPeerAssessment tool, which allows to provide teams with complex tasks and which allows assessment that sufficiently scales for the MOOC context. The presented tools are evaluated in terms of success rates of the created teams and workload reduction for the courses' teaching teams.
• 
  Renz, J., Rohloff, T., Meinel, C.: Automatisierte Qualitätssicherung in MOOCs durch Learning Analytics. In: Ullrich, C. and Wessner, M. (eds.) Joint Proceedings of the Pre-Conference Workshops of DeLFI and GMW 2017. CEUR-WS.org (2017).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Dieser Beitrag beschreibt wie mithilfe von Learning Analytics Daten eine automatisierte Qualitätssicherung in MOOCs durchgeführt werden kann. Die Ergebnisse sind auch für andere skalierende E-Learning Systeme anwendbar. Hierfür wird zunächst beschrieben, wie in den untersuchten Systemen (die als verteilte Dienste in einer Microservice-Architektur implementiert sind) Learning Analytics Werkzeuge umgesetzt sind. Darauf aufbauend werden Konzept und Implementierung einer automatisierten Qualitätssicherung beschrieben. In einer ersten Evaluation wird die Nutzung der Funktion auf einer Instanz der am HPI entwickelten MOOC-Plattform untersucht. Anschließend wird ein Ausblick auf Erweiterungen und zukünftige Forschungsfragen gegeben.
  @inproceedings{Renz2017MoocQuality, abstract = {Dieser Beitrag beschreibt wie mithilfe von Learning Analytics Daten eine automatisierte Qualitätssicherung in MOOCs durchgeführt werden kann. Die Ergebnisse sind auch für andere skalierende E-Learning Systeme anwendbar. Hierfür wird zunächst beschrieben, wie in den untersuchten Systemen (die als verteilte Dienste in einer Microservice-Architektur implementiert sind) Learning Analytics Werkzeuge umgesetzt sind. Darauf aufbauend werden Konzept und Implementierung einer automatisierten Qualitätssicherung beschrieben. In einer ersten Evaluation wird die Nutzung der Funktion auf einer Instanz der am HPI entwickelten MOOC-Plattform untersucht. Anschließend wird ein Ausblick auf Erweiterungen und zukünftige Forschungsfragen gegeben.}, author = {Renz, Jan and Rohloff, Tobias and Meinel, Christoph}, booktitle = {Joint Proceedings of the Pre-Conference Workshops of DeLFI and GMW 2017}, editor = {Ullrich, Carsten and Wessner, Martin}, keywords = {moocs learninganalytics}, publisher = {CEUR-WS.org}, title = {Automatisierte Qualitätssicherung in MOOCs durch Learning Analytics}, year = 2017 }
  Further Information

  Editor(s)Ullrich, Carsten and Wessner, Martin

  AbstractDieser Beitrag beschreibt wie mithilfe von Learning Analytics Daten eine automatisierte Qualitätssicherung in MOOCs durchgeführt werden kann. Die Ergebnisse sind auch für andere skalierende E-Learning Systeme anwendbar. Hierfür wird zunächst beschrieben, wie in den untersuchten Systemen (die als verteilte Dienste in einer Microservice-Architektur implementiert sind) Learning Analytics Werkzeuge umgesetzt sind. Darauf aufbauend werden Konzept und Implementierung einer automatisierten Qualitätssicherung beschrieben. In einer ersten Evaluation wird die Nutzung der Funktion auf einer Instanz der am HPI entwickelten MOOC-Plattform untersucht. Anschließend wird ein Ausblick auf Erweiterungen und zukünftige Forschungsfragen gegeben.
• 
  Grella, C.T., Staubitz, T., Teusner, R., Meinel, C.: Can MOOCs Support Secondary Education in Computer Science? In: Auer, M.E., Guralnick, D., and Uhomoibhi, J. (eds.) Interactive Collaborative Learning. p. 478--493. Springer International Publishing, Cham (2017).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  Despite the importance of competencies in computer science for participation in the digital transformation of nearly all sectors, there is still a lack of learning material and technically experienced teachers in German schools. In the paper at hand, we investigate the potential of Massive Open Online Courses (MOOCs) for secondary education. Schools can profit from this learning content and format provided by well-known institutions. However, German schools provide some challenging conditions, which have to be taken into account for a meaningful integration of e-learning elements. Our statistical and qualitative results are based on the representative data of the National Educational Panel Study (NEPS), the learning data of more than 100,000 online learners from over 150 countries, and the outcomes of several workshops with teachers and school administrators.
  @inproceedings{10.1007/978-3-319-50337-0_45, abstract = {Despite the importance of competencies in computer science for participation in the digital transformation of nearly all sectors, there is still a lack of learning material and technically experienced teachers in German schools. In the paper at hand, we investigate the potential of Massive Open Online Courses (MOOCs) for secondary education. Schools can profit from this learning content and format provided by well-known institutions. However, German schools provide some challenging conditions, which have to be taken into account for a meaningful integration of e-learning elements. Our statistical and qualitative results are based on the representative data of the National Educational Panel Study (NEPS), the learning data of more than 100,000 online learners from over 150 countries, and the outcomes of several workshops with teachers and school administrators.}, address = {Cham}, author = {Grella, Catrina Tamara and Staubitz, Thomas and Teusner, Ralf and Meinel, Christoph}, booktitle = {Interactive Collaborative Learning}, editor = {Auer, Michael E. and Guralnick, David and Uhomoibhi, James}, keywords = {e-learning myown mooc}, pages = {478–493}, publisher = {Springer International Publishing}, title = {Can MOOCs Support Secondary Education in Computer Science?}, year = 2017 }
  Further Information

  Editor(s)Auer, Michael E. and Guralnick, David and Uhomoibhi, James

  AbstractDespite the importance of competencies in computer science for participation in the digital transformation of nearly all sectors, there is still a lack of learning material and technically experienced teachers in German schools. In the paper at hand, we investigate the potential of Massive Open Online Courses (MOOCs) for secondary education. Schools can profit from this learning content and format provided by well-known institutions. However, German schools provide some challenging conditions, which have to be taken into account for a meaningful integration of e-learning elements. Our statistical and qualitative results are based on the representative data of the National Educational Panel Study (NEPS), the learning data of more than 100,000 online learners from over 150 countries, and the outcomes of several workshops with teachers and school administrators.
• 
  Rohloff, T., Renz, J., Bothe, M., Meinel, C.: Supporting Multi-Device E-Learning Patterns with Second Screen Mobile Applications.Proceedings of the 16th World Conference on Mobile and Contextual Learning (mLearn 2017). p. 25:1--25:8. Association for Computing Machinery (2017).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Many providers of Massive Open Online Course (MOOC) platforms released mobile applications in the recent years to enable learning offline and on the go, for a more ubiquitous learning experience. However, mainly the MOOC content was optimized for small screens, but mobile devices provide the opportunity to enrich the MOOC experience even further by enabling new forms of learning. Based on a previous learning patterns evaluation and a user survey, this paper presents a second screen prototype for the MOOC platform of the Hasso Plattner Institute, whereby the mobile application can be used as a learning companion while using the web platform on a computer. Four different actions were implemented which can be done next to watching a video lecture. The evaluation showed that the prototype was helpful and made learning more efficient, as reported by users, and also ideas for further improvements were proposed.
  @inproceedings{Rohloff2017SecondScreen, abstract = {Many providers of Massive Open Online Course (MOOC) platforms released mobile applications in the recent years to enable learning offline and on the go, for a more ubiquitous learning experience. However, mainly the MOOC content was optimized for small screens, but mobile devices provide the opportunity to enrich the MOOC experience even further by enabling new forms of learning. Based on a previous learning patterns evaluation and a user survey, this paper presents a second screen prototype for the MOOC platform of the Hasso Plattner Institute, whereby the mobile application can be used as a learning companion while using the web platform on a computer. Four different actions were implemented which can be done next to watching a video lecture. The evaluation showed that the prototype was helpful and made learning more efficient, as reported by users, and also ideas for further improvements were proposed.}, author = {Rohloff, Tobias and Renz, Jan and Bothe, Max and Meinel, Christoph}, booktitle = {Proceedings of the 16th World Conference on Mobile and Contextual Learning (mLearn 2017)}, keywords = {mobilelearning moocs}, pages = {25:1–25:8}, publisher = {Association for Computing Machinery}, title = {Supporting Multi-Device E-Learning Patterns with Second Screen Mobile Applications}, year = 2017 }
  Further Information

  URNhttp://dx.doi.org/10.1145/3136907.3136931

  AbstractMany providers of Massive Open Online Course (MOOC) platforms released mobile applications in the recent years to enable learning offline and on the go, for a more ubiquitous learning experience. However, mainly the MOOC content was optimized for small screens, but mobile devices provide the opportunity to enrich the MOOC experience even further by enabling new forms of learning. Based on a previous learning patterns evaluation and a user survey, this paper presents a second screen prototype for the MOOC platform of the Hasso Plattner Institute, whereby the mobile application can be used as a learning companion while using the web platform on a computer. Four different actions were implemented which can be done next to watching a video lecture. The evaluation showed that the prototype was helpful and made learning more efficient, as reported by users, and also ideas for further improvements were proposed.

2016 [ to top ]

• 
  Luo, S., Yang, H., Wang, C., Che, X., Meinel, C.: Real-time action recognition in surveillance videos using ConvNets.International Conference on Neural Information Processing. pp. 529-537. Springer (2016).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  The explosive growth of surveillance cameras and its 7 * 24 recording period brings massive surveillance videos data. Therefore how to efficiently retrieve the rare but important event information inside the videos is eager to be solved. Recently deep convolutinal networks shows its outstanding performance in event recognition on general videos. Hence we study the characteristic of surveillance video context and propose a very competitive ConvNets approach for real-time event recognition on surveillance videos. Our approach adopts two-steam ConvNets to respectively recognition spatial and temporal information of one action. In particular, we propose to use fast feature cascades and motion history image as the template of spatial and temporal stream. We conducted our experiments on UCF-ARG and UT-interaction dataset. The experimental results show that our approach acquires superior recognition accuracy and runs in real-time.
  @inproceedings{2016_LUO_ICONIP, abstract = {The explosive growth of surveillance cameras and its 7 * 24 recording period brings massive surveillance videos data. Therefore how to efficiently retrieve the rare but important event information inside the videos is eager to be solved. Recently deep convolutinal networks shows its outstanding performance in event recognition on general videos. Hence we study the characteristic of surveillance video context and propose a very competitive ConvNets approach for real-time event recognition on surveillance videos. Our approach adopts two-steam ConvNets to respectively recognition spatial and temporal information of one action. In particular, we propose to use fast feature cascades and motion history image as the template of spatial and temporal stream. We conducted our experiments on UCF-ARG and UT-interaction dataset. The experimental results show that our approach acquires superior recognition accuracy and runs in real-time.}, author = {Luo, Sheng and Yang, Haojin and Wang, Cheng and Che, Xiaoyin and Meinel, Christoph}, booktitle = {International Conference on Neural Information Processing}, keywords = {its Motion_history_image Real-time_application Event_recognition Surveillance_videos}, month = 9, pages = {529-537}, publisher = {Springer}, title = {Real-time action recognition in surveillance videos using ConvNets}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/10.1007/978-3-319-46675-0_58

  AbstractThe explosive growth of surveillance cameras and its 7 * 24 recording period brings massive surveillance videos data. Therefore how to efficiently retrieve the rare but important event information inside the videos is eager to be solved. Recently deep convolutinal networks shows its outstanding performance in event recognition on general videos. Hence we study the characteristic of surveillance video context and propose a very competitive ConvNets approach for real-time event recognition on surveillance videos. Our approach adopts two-steam ConvNets to respectively recognition spatial and temporal information of one action. In particular, we propose to use fast feature cascades and motion history image as the template of spatial and temporal stream. We conducted our experiments on UCF-ARG and UT-interaction dataset. The experimental results show that our approach acquires superior recognition accuracy and runs in real-time.
• 
  Staubitz, T., Petrick, D., Bauer, M., Renz, J., Meinel, C.: Improving the Peer Assessment Experience on MOOC Platforms.Proceedings of ACM Learning at Scale Conference (L@S2016). ACM (2016).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Massive Open Online Courses (MOOCs) have revolutionized higher education by offering university-like courses for a large amount of learners via the Internet. The paper at hand takes a closer look on peer assessment as a tool for delivering individualized feedback and engaging assignments to MOOC participants. Benefits, such as scalability for MOOCs and higher order learning, and challenges, such as grading accuracy and rogue reviewers, are described. Common practices and the state-of-the-art to counteract challenges are highlighted. Based on this research, the paper at hand describes a peer assessment workflow and its implementation on the openHPI and openSAP MOOC platforms. This workflow combines the best practices of existing peer assessment tools and introduces some small but crucial improvements.
  @inproceedings{2016_Staubitz_LatS, abstract = {Massive Open Online Courses (MOOCs) have revolutionized higher education by offering university-like courses for a large amount of learners via the Internet. The paper at hand takes a closer look on peer assessment as a tool for delivering individualized feedback and engaging assignments to MOOC participants. Benefits, such as scalability for MOOCs and higher order learning, and challenges, such as grading accuracy and rogue reviewers, are described. Common practices and the state-of-the-art to counteract challenges are highlighted. Based on this research, the paper at hand describes a peer assessment workflow and its implementation on the openHPI and openSAP MOOC platforms. This workflow combines the best practices of existing peer assessment tools and introduces some small but crucial improvements.}, author = {Staubitz, Thomas and Petrick, Dominic and Bauer, Matthias and Renz, Jan and Meinel, Christoph}, booktitle = {Proceedings of ACM Learning at Scale Conference (L@S2016)}, keywords = {its}, publisher = {ACM}, title = {Improving the Peer Assessment Experience on MOOC Platforms}, year = 2016 }
  Further Information

  AbstractMassive Open Online Courses (MOOCs) have revolutionized higher education by offering university-like courses for a large amount of learners via the Internet. The paper at hand takes a closer look on peer assessment as a tool for delivering individualized feedback and engaging assignments to MOOC participants. Benefits, such as scalability for MOOCs and higher order learning, and challenges, such as grading accuracy and rogue reviewers, are described. Common practices and the state-of-the-art to counteract challenges are highlighted. Based on this research, the paper at hand describes a peer assessment workflow and its implementation on the openHPI and openSAP MOOC platforms. This workflow combines the best practices of existing peer assessment tools and introduces some small but crucial improvements.
• 
  Bauer, M., Malchow, M., Staubitz, T., Meinel, C.: Improving Collaborative Learning With Video Lectures.INTED2016 Proceedings. 10th International Technology, Education and Development ConferenceValencia, Spain. 7-9 March, 2016. pp. 5511-5517. IATED (2016).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  We have addressed the problems of independent e-lecture learning with an approach involving collaborative learning with lecture recordings. In order to make this type of learning possible, we have prototypically enhanced the video player of a lecture video platform with functionality that allows simultaneous viewing of a lecture on two or more computers. While watching the video, synchronization of the playback and every click event, such as play, pause, seek, and playback speed adjustment can be carried out. We have also added the option of annotating slides. With this approach, it is possible for learners to watch a lecture together, even though they are in different places. In this way, the benefits of collaborative learning can also be used when learning online. Now, it is more likely that learners stay focused on the lecture for a longer time (as the collaboration creates an additional obligation not to leave early and desert a friend). Furthermore, the learning outcome is higher because learners can ask their friends questions and explain things to each other as well as mark important points in the lecture video.
  @inproceedings{Matthias2016a, abstract = {We have addressed the problems of independent e-lecture learning with an approach involving collaborative learning with lecture recordings. In order to make this type of learning possible, we have prototypically enhanced the video player of a lecture video platform with functionality that allows simultaneous viewing of a lecture on two or more computers. While watching the video, synchronization of the playback and every click event, such as play, pause, seek, and playback speed adjustment can be carried out. We have also added the option of annotating slides. With this approach, it is possible for learners to watch a lecture together, even though they are in different places. In this way, the benefits of collaborative learning can also be used when learning online. Now, it is more likely that learners stay focused on the lecture for a longer time (as the collaboration creates an additional obligation not to leave early and desert a friend). Furthermore, the learning outcome is higher because learners can ask their friends questions and explain things to each other as well as mark important points in the lecture video.}, author = {Bauer, Matthias and Malchow, Martin and Staubitz, Thomas and Meinel, Christoph}, booktitle = {INTED2016 Proceedings. 10th International Technology, Education and Development ConferenceValencia, Spain. 7-9 March, 2016.}, keywords = {e-learning MOOC myown Didactics E-Learning E-Lecture its Collaborative_Learning Learning_Analytics}, month = 3, pages = {5511-5517}, publisher = {IATED}, title = {Improving Collaborative Learning With Video Lectures}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/http://dx.doi.org/10.21125/inted.2016.0322

  AbstractWe have addressed the problems of independent e-lecture learning with an approach involving collaborative learning with lecture recordings. In order to make this type of learning possible, we have prototypically enhanced the video player of a lecture video platform with functionality that allows simultaneous viewing of a lecture on two or more computers. While watching the video, synchronization of the playback and every click event, such as play, pause, seek, and playback speed adjustment can be carried out. We have also added the option of annotating slides. With this approach, it is possible for learners to watch a lecture together, even though they are in different places. In this way, the benefits of collaborative learning can also be used when learning online. Now, it is more likely that learners stay focused on the lecture for a longer time (as the collaboration creates an additional obligation not to leave early and desert a friend). Furthermore, the learning outcome is higher because learners can ask their friends questions and explain things to each other as well as mark important points in the lecture video.
• 
  Che, X., Staubitz, T., Yang, H., Meinel, C.: Pre-Course Key Segment Analysis of Online Lecture Videos.Proceedings of The 16th IEEE International Conference on Advanced Learning Technology (ICALT2016). , Austin, Texas, USA (2016).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  In this paper we propose a method to evaluate the importance of lecture video segments in online courses. The video will be first segmented based on the slide transition. Then we evaluate the importance of each segment based on our analysis of the teacher’s focus. This focus is mainly identified by exploring features in the slide and the speech. Since the whole analysis process is based on multimedia materials, it could be done before the official start of the course. By setting survey questions and collecting forum statistics in the MOOC “Web Technologies”, the proposed method is evaluated. Both the general trend and the high accuracy of selected key segments (over 70%) prove the effectiveness of the proposed method.
  @inproceedings{2016_Che_ICALT, abstract = {In this paper we propose a method to evaluate the importance of lecture video segments in online courses. The video will be first segmented based on the slide transition. Then we evaluate the importance of each segment based on our analysis of the teacher’s focus. This focus is mainly identified by exploring features in the slide and the speech. Since the whole analysis process is based on multimedia materials, it could be done before the official start of the course. By setting survey questions and collecting forum statistics in the MOOC “Web Technologies”, the proposed method is evaluated. Both the general trend and the high accuracy of selected key segments (over 70%) prove the effectiveness of the proposed method.}, address = {Austin, Texas, USA}, author = {Che, Xiaoyin and Staubitz, Thomas and Yang, Haojin and Meinel, Christoph}, booktitle = {Proceedings of The 16th IEEE International Conference on Advanced Learning Technology (ICALT2016)}, keywords = {e-learning myown mooc}, month = 7, title = {Pre-Course Key Segment Analysis of Online Lecture Videos}, year = 2016 }
  Further Information

  AbstractIn this paper we propose a method to evaluate the importance of lecture video segments in online courses. The video will be first segmented based on the slide transition. Then we evaluate the importance of each segment based on our analysis of the teacher’s focus. This focus is mainly identified by exploring features in the slide and the speech. Since the whole analysis process is based on multimedia materials, it could be done before the official start of the course. By setting survey questions and collecting forum statistics in the MOOC “Web Technologies”, the proposed method is evaluated. Both the general trend and the high accuracy of selected key segments (over 70%) prove the effectiveness of the proposed method.
• 
  Staubitz, T., Brehm, M., Jasper, J., Werkmeister, T., Teusner, R., Willems, C., Renz, J., Meinel, C.: Vagrant Virtual Machines for Hands-On Exercises in Massive Open Online Courses.Smart Education and e-Learning 2016. p. 363--373. Springer International Publishing (2016).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  In many MOOCs hands-on exercises are a key component. Their format must be deliberately planned to satisfy the needs of a more and more heterogeneous student body. At the same time, costs have to be kept low for maintenance and support on the course provider’s side. The paper at hand reports about our experiments with a tool called Vagrant in this context. It has been successfully employed for use cases similar to ours and thus promises to be an option for achieving our goals.
  @inproceedings{2016_Staubitz_KES-SEEL, abstract = {In many MOOCs hands-on exercises are a key component. Their format must be deliberately planned to satisfy the needs of a more and more heterogeneous student body. At the same time, costs have to be kept low for maintenance and support on the course provider’s side. The paper at hand reports about our experiments with a tool called Vagrant in this context. It has been successfully employed for use cases similar to ours and thus promises to be an option for achieving our goals.}, author = {Staubitz, Thomas and Brehm, Maximilian and Jasper, Johannes and Werkmeister, Thomas and Teusner, Ralf and Willems, Christian and Renz, Jan and Meinel, Christoph}, journal = {Smart Education and e-Learning 2016}, keywords = {e-learning myown assessment mooc vagrant assignment}, pages = {363–373}, publisher = {Springer International Publishing}, title = {Vagrant Virtual Machines for Hands-On Exercises in Massive Open Online Courses}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/10.1007/978-3-319-39690-3_32"

  AbstractIn many MOOCs hands-on exercises are a key component. Their format must be deliberately planned to satisfy the needs of a more and more heterogeneous student body. At the same time, costs have to be kept low for maintenance and support on the course provider’s side. The paper at hand reports about our experiments with a tool called Vagrant in this context. It has been successfully employed for use cases similar to ours and thus promises to be an option for achieving our goals.
• 
  Staubitz, T., Teusner, R., Renz, J., Meinel, C.: First Steps in Automated Proctoring.Proceedings of the Fourth MOOC European Stakeholders Summit (EMOOCs 2016). P.A.U (2016).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2016_Staubitz_Emoocs, author = {Staubitz, Thomas and Teusner, Ralf and Renz, Jan and Meinel, Christoph}, booktitle = {Proceedings of the Fourth MOOC European Stakeholders Summit (EMOOCs 2016)}, keywords = {e-learning myown assessment mooc assignment proctoring}, organization = {P.A.U}, title = {First Steps in Automated Proctoring}, year = 2016 }
  Further Information
• 
  Staubitz, T., Klement, H., Teusner, R., Renz, J., Meinel, C.: CodeOcean - A Versatile Platform for Practical Programming Excercises in Online Environments.Proceedings of IEEE Global Engineering Education Conference (EDUCON2016). IEEE (2016).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2016_Staubitz_Educon, author = {Staubitz, Thomas and Klement, Hauke and Teusner, Ralf and Renz, Jan and Meinel, Christoph}, booktitle = {Proceedings of IEEE Global Engineering Education Conference (EDUCON2016)}, keywords = {e-learning myown assessment autograder mooc assignment}, publisher = {IEEE}, title = {CodeOcean - A Versatile Platform for Practical Programming Excercises in Online Environments}, year = 2016 }
  Further Information
• 
  Renz, J., Navarro-Suarez, G., Sathi, R., Staubitz, T., Meinel, C.: Enabling Schema Agnostic Learning Analytics in a Service-Oriented MOOC Platform.Proceedings of ACM Learning at Scale Conference (L@S2016). ACM (2016).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2016_Renz_LatS, author = {Renz, Jan and Navarro-Suarez, Gerardo and Sathi, Rowshan and Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proceedings of ACM Learning at Scale Conference (L@S2016)}, keywords = {e-learning myown mooc learning-analytics}, publisher = {ACM}, title = {Enabling Schema Agnostic Learning Analytics in a Service-Oriented MOOC Platform}, year = 2016 }
  Further Information
• 
  Malchow, M., Renz, J., Bauer, M., Meinel, C.: Enhance Embedded System E-learning Experience with Sensors.2016 IEEE Global Engineering Education Conference (EDUCON). pp. 175-183. IEEE (2016).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Earlier research shows that using an embedded LED system motivates students to learn programming languages in massive open online courses (MOOCs) efficiently. Since this earlier approach was very successful the system should be improved to increase the learning experience for students during programming exercises. The problem of the current system is that only a static image was shown on the LED matrix controlled by students’ array programming over the embedded system. The idea of this paper to change this static behavior into a dynamic display of information on the LED matrix by the use of sensors which are connected with the embedded system. For this approach a light sensor and a temperature sensor are connected to an analog-to-digital converter (ADC) port of the embedded system. These sensors' values can be read by the students to compute the correct output for the LED matrix. The result is captured and sent back to the students for direct feedback. Furthermore, unit tests can be used to automatically evaluate the programming results. The system was evaluated during a MOOC course about web technologies using JavaScript. Evaluation results are taken from the student’s feedback and an evaluation of the students’ code executions on the system. The positive feedback and the evaluation of the students’ executions, which shows a higher amount of code executions compared to standard programming tasks and the fact that students solving these tasks have overall better course results, highlight the advantage of the approach. Due to the evaluation results, this approach should be used in e-learning e.g. MOOCs teaching programming languages to increase the learning experience and motivate students to learn programming.
  @inproceedings{Martin2016c, abstract = {Earlier research shows that using an embedded LED system motivates students to learn programming languages in massive open online courses (MOOCs) efficiently. Since this earlier approach was very successful the system should be improved to increase the learning experience for students during programming exercises. The problem of the current system is that only a static image was shown on the LED matrix controlled by students’ array programming over the embedded system. The idea of this paper to change this static behavior into a dynamic display of information on the LED matrix by the use of sensors which are connected with the embedded system. For this approach a light sensor and a temperature sensor are connected to an analog-to-digital converter (ADC) port of the embedded system. These sensors' values can be read by the students to compute the correct output for the LED matrix. The result is captured and sent back to the students for direct feedback. Furthermore, unit tests can be used to automatically evaluate the programming results. The system was evaluated during a MOOC course about web technologies using JavaScript. Evaluation results are taken from the student’s feedback and an evaluation of the students’ code executions on the system. The positive feedback and the evaluation of the students’ executions, which shows a higher amount of code executions compared to standard programming tasks and the fact that students solving these tasks have overall better course results, highlight the advantage of the approach. Due to the evaluation results, this approach should be used in e-learning e.g. MOOCs teaching programming languages to increase the learning experience and motivate students to learn programming.}, author = {Malchow, Martin and Renz, Jan and Bauer, Matthias and Meinel, Christoph}, booktitle = {2016 IEEE Global Engineering Education Conference (EDUCON)}, keywords = {learning_experience massive_open_online_courses programming_language_learning computer_science_education web_university embedded_systems temperature_sensor electronic_learning analog-to-digital_converter Sensor_systems Tele-Lecturing E-Learning student_motivation embedded_LED_system Embedded_systems Virtual_Lab educational_courses programming_exercises Web_technologies MOOC light_sensor student_feedback embedded_system_e-learning_experience student_code_execution_evaluation computer_aided_instruction Distance_Learning Teleteaching}, month = 4, pages = {175-183}, publisher = {IEEE}, title = {Enhance Embedded System E-learning Experience with Sensors}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/10.1109/EDUCON.2016.7474550

  AbstractEarlier research shows that using an embedded LED system motivates students to learn programming languages in massive open online courses (MOOCs) efficiently. Since this earlier approach was very successful the system should be improved to increase the learning experience for students during programming exercises. The problem of the current system is that only a static image was shown on the LED matrix controlled by students’ array programming over the embedded system. The idea of this paper to change this static behavior into a dynamic display of information on the LED matrix by the use of sensors which are connected with the embedded system. For this approach a light sensor and a temperature sensor are connected to an analog-to-digital converter (ADC) port of the embedded system. These sensors' values can be read by the students to compute the correct output for the LED matrix. The result is captured and sent back to the students for direct feedback. Furthermore, unit tests can be used to automatically evaluate the programming results. The system was evaluated during a MOOC course about web technologies using JavaScript. Evaluation results are taken from the student’s feedback and an evaluation of the students’ code executions on the system. The positive feedback and the evaluation of the students’ executions, which shows a higher amount of code executions compared to standard programming tasks and the fact that students solving these tasks have overall better course results, highlight the advantage of the approach. Due to the evaluation results, this approach should be used in e-learning e.g. MOOCs teaching programming languages to increase the learning experience and motivate students to learn programming.
• 
  Che, X., Wang, C., Yang, H., Meinel, C.: Punctuation Prediction for Unsegmented Transcript Based on Word Vector.Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). pp. 654-658. , Portorož, Slovenia (2016).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In this paper we propose an approach to predict punctuation marks for unsegmented speech transcript. The approach is purely lexical, with pre-trained Word Vectors as the only input. A training model of Deep Neural Network (DNN) or Convolutional Neural Network (CNN) is applied to classify whether a punctuation mark should be inserted after the third word of a 5-words sequence and which kind of punctuation mark the inserted one should be. TED talks within IWSLT dataset are used in both training and evaluation phases. The proposed approach shows its effectiveness by achieving better result than the state-of-the-art lexical solution which works with same type of data, especially when predicting puncuation position only.
  @inproceedings{2016_Che_LREC, abstract = {In this paper we propose an approach to predict punctuation marks for unsegmented speech transcript. The approach is purely lexical, with pre-trained Word Vectors as the only input. A training model of Deep Neural Network (DNN) or Convolutional Neural Network (CNN) is applied to classify whether a punctuation mark should be inserted after the third word of a 5-words sequence and which kind of punctuation mark the inserted one should be. TED talks within IWSLT dataset are used in both training and evaluation phases. The proposed approach shows its effectiveness by achieving better result than the state-of-the-art lexical solution which works with same type of data, especially when predicting puncuation position only.}, address = {Portorož, Slovenia}, author = {Che, Xiaoyin and Wang, Cheng and Yang, Haojin and Meinel, Christoph}, booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)}, keywords = {Punctuation_Prediction Deep_Learning its Word_Vector Convolutional_Neural_Network}, month = 5, pages = {654-658}, title = {Punctuation Prediction for Unsegmented Transcript Based on Word Vector}, year = 2016 }
  Further Information

  AbstractIn this paper we propose an approach to predict punctuation marks for unsegmented speech transcript. The approach is purely lexical, with pre-trained Word Vectors as the only input. A training model of Deep Neural Network (DNN) or Convolutional Neural Network (CNN) is applied to classify whether a punctuation mark should be inserted after the third word of a 5-words sequence and which kind of punctuation mark the inserted one should be. TED talks within IWSLT dataset are used in both training and evaluation phases. The proposed approach shows its effectiveness by achieving better result than the state-of-the-art lexical solution which works with same type of data, especially when predicting puncuation position only.
• 
  Malchow, M., Renz, J., Bauer, M., Meinel, C.: Improved E-learning Experience with Embedded LED System.2016 Annual IEEE Systems Conference (SysCon). IEEE (2016).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  During the last years, e-learning has become more and more important. There are several approaches like teleteaching or MOOCs to delivers knowledge information to the students on different topics. But, a major problem most learning platforms have is, students often get demotivated fast. This is caused e.g. by solving similar tasks again and again, and learning alone on the personal computer. To avoid this situation in coding-based courses one possible way could be the use of embedded devices. This approach increases the practical programming part and should push motivation to the students. This paper presents a possibility to the use of embedded systems with an LED panel to motivate students to use programming languages and solve the course successfully. To analyze the successfulness of this approach, it was tested within a MOOC called "Java for beginners" with 11,712 participants. The result was evaluated by personal feedback of the students and user data was analyzed to measure the acceptance and motivation of students by solving the embedded system tasks. The result shows that the approach is well accepted by the students and they are more motivated by tasks with real hardware support.
  @inproceedings{Martin2016d, abstract = {During the last years, e-learning has become more and more important. There are several approaches like teleteaching or MOOCs to delivers knowledge information to the students on different topics. But, a major problem most learning platforms have is, students often get demotivated fast. This is caused e.g. by solving similar tasks again and again, and learning alone on the personal computer. To avoid this situation in coding-based courses one possible way could be the use of embedded devices. This approach increases the practical programming part and should push motivation to the students. This paper presents a possibility to the use of embedded systems with an LED panel to motivate students to use programming languages and solve the course successfully. To analyze the successfulness of this approach, it was tested within a MOOC called "Java for beginners" with 11,712 participants. The result was evaluated by personal feedback of the students and user data was analyzed to measure the acceptance and motivation of students by solving the embedded system tasks. The result shows that the approach is well accepted by the students and they are more motivated by tasks with real hardware support.}, author = {Malchow, Martin and Renz, Jan and Bauer, Matthias and Meinel, Christoph}, booktitle = {2016 Annual IEEE Systems Conference (SysCon)}, keywords = {Java Tele-Lecturing E-Learning LED_Matrix embedded_LED_system its Programming Virtual_Lab coding-based_courses web_university educational_courses embedded_devices LED_panel Embedded_Systems MOOC personal_computer embedded_system_tasks e-learning_experience computer_aided_instruction Distance_Learning Teleteaching programming_languages}, month = 4, publisher = {IEEE}, title = {Improved E-learning Experience with Embedded LED System}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/10.1109/SYSCON.2016.7490569

  AbstractDuring the last years, e-learning has become more and more important. There are several approaches like teleteaching or MOOCs to delivers knowledge information to the students on different topics. But, a major problem most learning platforms have is, students often get demotivated fast. This is caused e.g. by solving similar tasks again and again, and learning alone on the personal computer. To avoid this situation in coding-based courses one possible way could be the use of embedded devices. This approach increases the practical programming part and should push motivation to the students. This paper presents a possibility to the use of embedded systems with an LED panel to motivate students to use programming languages and solve the course successfully. To analyze the successfulness of this approach, it was tested within a MOOC called "Java for beginners" with 11,712 participants. The result was evaluated by personal feedback of the students and user data was analyzed to measure the acceptance and motivation of students by solving the embedded system tasks. The result shows that the approach is well accepted by the students and they are more motivated by tasks with real hardware support.
• 
  Malchow, M., Bauer, M., Meinel, C.: Couch Learning Mode: Multiple-Video Lecture Playlist Selection out of a Lecture Video Archive for E-learning Students.Proceedings of the 2016 ACM on SIGUCCS Annual Conference. pp. 77-82. ACM (2016).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  During a video recorded university class students have to watch several hours of video content. This can easily add up to several days of video content during a semester. Naturally, not all 90 minutes of a typical lecture are relevant for the exam. When the semester ends with a final exam students have to study more intensively the important parts of all the lectures. To simplify the learning process and design it to be more efficient we have introduced the Couch Learning Mode in our lecture video archive. With this approach students can create custom playlists out of the video lecture archive with a time frame for every selected video. Finally, students can lean back and watch all relevant video parts consecutively for the exam without being interrupted. Additionally, the students can share their playlists with other students or they can use the video search to watch all relevant lecture videos about a topic. This approach uses playlists and HTML5 technologies to realize the consecutive video playback. Furthermore, the powerful Lecture Butler search engine is used to find worthwhile video parts for certain topics. Our approach shows that we have more satisfied students using the manual playlist creation to view reasonable parts for an exam. Finally, students are keen on watching the top search results showing reasonable parts of lectures for a topic of interest. The Couch Learning Mode supports and motivates students to learn with video lectures for an exam and daily life.
  @inproceedings{Martin2016b, abstract = {During a video recorded university class students have to watch several hours of video content. This can easily add up to several days of video content during a semester. Naturally, not all 90 minutes of a typical lecture are relevant for the exam. When the semester ends with a final exam students have to study more intensively the important parts of all the lectures. To simplify the learning process and design it to be more efficient we have introduced the Couch Learning Mode in our lecture video archive. With this approach students can create custom playlists out of the video lecture archive with a time frame for every selected video. Finally, students can lean back and watch all relevant video parts consecutively for the exam without being interrupted. Additionally, the students can share their playlists with other students or they can use the video search to watch all relevant lecture videos about a topic. This approach uses playlists and HTML5 technologies to realize the consecutive video playback. Furthermore, the powerful Lecture Butler search engine is used to find worthwhile video parts for certain topics. Our approach shows that we have more satisfied students using the manual playlist creation to view reasonable parts for an exam. Finally, students are keen on watching the top search results showing reasonable parts of lectures for a topic of interest. The Couch Learning Mode supports and motivates students to learn with video lectures for an exam and daily life.}, author = {Malchow, Martin and Bauer, Matthias and Meinel, Christoph}, booktitle = {Proceedings of the 2016 ACM on SIGUCCS Annual Conference}, keywords = {e-learning tele-TASK its lecture_video_archive video_lecture distance_learning self-paced_learning teleteaching web_university tele-lecturing video_playlist}, month = 11, pages = {77-82}, publisher = {ACM}, title = {Couch Learning Mode: Multiple-Video Lecture Playlist Selection out of a Lecture Video Archive for E-learning Students}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/10.1145/2974927.2974937

  AbstractDuring a video recorded university class students have to watch several hours of video content. This can easily add up to several days of video content during a semester. Naturally, not all 90 minutes of a typical lecture are relevant for the exam. When the semester ends with a final exam students have to study more intensively the important parts of all the lectures. To simplify the learning process and design it to be more efficient we have introduced the Couch Learning Mode in our lecture video archive. With this approach students can create custom playlists out of the video lecture archive with a time frame for every selected video. Finally, students can lean back and watch all relevant video parts consecutively for the exam without being interrupted. Additionally, the students can share their playlists with other students or they can use the video search to watch all relevant lecture videos about a topic. This approach uses playlists and HTML5 technologies to realize the consecutive video playback. Furthermore, the powerful Lecture Butler search engine is used to find worthwhile video parts for certain topics. Our approach shows that we have more satisfied students using the manual playlist creation to view reasonable parts for an exam. Finally, students are keen on watching the top search results showing reasonable parts of lectures for a topic of interest. The Couch Learning Mode supports and motivates students to learn with video lectures for an exam and daily life.
• 
  Che, X., Luo, S., Yang, H., Meinel, C.: Sentence Boundary Detection Based on Parallel Lexical and Acoustic Models.Proceedings of Interspeech 2016. pp. 257-261. , San Francisco, CA, USA (2016).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In this paper we propose a solution that detects sentence boundary from speech transcript. First we train a pure lexical model with deep neural network, which takes word vectors as the only input feature. Then a simple acoustic model is also prepared. Because the models work independently, they can be trained with different data. In next step, the posterior probabilities of both lexical and acoustic models will be involved in a heuristic 2-stage joint decision scheme to classify the sentence boundary positions. This approach ensures that the models can be updated or switched freely in actual use. Evaluation on TED Talks shows that the proposed lexical model can achieve good results: 75.5% accuracy on error-involved ASR transcripts and 82.4% on error-free manual references. The joint decision scheme can further improve the accuracy by 3�~10% when acoustic data is available.
  @inproceedings{2016_Che_Interspeech, abstract = {In this paper we propose a solution that detects sentence boundary from speech transcript. First we train a pure lexical model with deep neural network, which takes word vectors as the only input feature. Then a simple acoustic model is also prepared. Because the models work independently, they can be trained with different data. In next step, the posterior probabilities of both lexical and acoustic models will be involved in a heuristic 2-stage joint decision scheme to classify the sentence boundary positions. This approach ensures that the models can be updated or switched freely in actual use. Evaluation on TED Talks shows that the proposed lexical model can achieve good results: 75.5% accuracy on error-involved ASR transcripts and 82.4% on error-free manual references. The joint decision scheme can further improve the accuracy by 3� 10% when acoustic data is available.}, address = {San Francisco, CA, USA}, author = {Che, Xiaoyin and Luo, Sheng and Yang, Haojin and Meinel, Christoph}, booktitle = {Proceedings of Interspeech 2016}, keywords = {Sentence_Boundary_Detection its Parallel_Models Word_Vector Deep_Neural_Network}, month = 9, pages = {257-261}, title = {Sentence Boundary Detection Based on Parallel Lexical and Acoustic Models}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/10.21437

  AbstractIn this paper we propose a solution that detects sentence boundary from speech transcript. First we train a pure lexical model with deep neural network, which takes word vectors as the only input feature. Then a simple acoustic model is also prepared. Because the models work independently, they can be trained with different data. In next step, the posterior probabilities of both lexical and acoustic models will be involved in a heuristic 2-stage joint decision scheme to classify the sentence boundary positions. This approach ensures that the models can be updated or switched freely in actual use. Evaluation on TED Talks shows that the proposed lexical model can achieve good results: 75.5% accuracy on error-involved ASR transcripts and 82.4% on error-free manual references. The joint decision scheme can further improve the accuracy by 3�~10% when acoustic data is available.
• 
  Staubitz, T., Teusner, R., Renz, J., Meinel, C.: First Steps in Automated Proctoring.Proceedings of the Fourth MOOC European Stakeholders Summit (EMOOCs 2016). P.A.U (2016).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2016_Staubitz_Emoocs, author = {Staubitz, Thomas and Teusner, Ralf and Renz, Jan and Meinel, Christoph}, booktitle = {Proceedings of the Fourth MOOC European Stakeholders Summit (EMOOCs 2016)}, keywords = {its}, organization = {P.A.U}, title = {First Steps in Automated Proctoring}, year = 2016 }
  Further Information
• 
  Renz, J., Navarro-Suarez, G., Sathi, R., Staubitz, T., Meinel, C.: Enabling Schema Agnostic Learning Analytics in a Service-Oriented MOOC Platform.Proceedings of ACM Learning at Scale Conference (L@S2016). ACM (2016).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2016_Renz_LatS, author = {Renz, Jan and Navarro-Suarez, Gerardo and Sathi, Rowshan and Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proceedings of ACM Learning at Scale Conference (L@S2016)}, keywords = {its}, publisher = {ACM}, title = {Enabling Schema Agnostic Learning Analytics in a Service-Oriented MOOC Platform}, year = 2016 }
  Further Information
• 
  Che, X., Staubitz, T., Yang, H., Meinel, C.: Pre-Course Key Segment Analysis of Online Lecture Videos.Proceedings of The 16th IEEE International Conference on Advanced Learning Technology (ICALT2016). , Austin, Texas, USA (2016).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In this paper we propose a method to evaluate the importance of lecture video segments in online courses. The video will be first segmented based on the slide transition. Then we evaluate the importance of each segment based on our analysis of the teacher’s focus. This focus is mainly identified by exploring features in the slide and the speech. Since the whole analysis process is based on multimedia materials, it could be done before the official start of the course. By setting survey questions and collecting forum statistics in the MOOC “Web Technologies”, the proposed method is evaluated. Both the general trend and the high accuracy of selected key segments (over 70%) prove the effectiveness of the proposed method.
  @inproceedings{2016_Che_ICALT, abstract = {In this paper we propose a method to evaluate the importance of lecture video segments in online courses. The video will be first segmented based on the slide transition. Then we evaluate the importance of each segment based on our analysis of the teacher’s focus. This focus is mainly identified by exploring features in the slide and the speech. Since the whole analysis process is based on multimedia materials, it could be done before the official start of the course. By setting survey questions and collecting forum statistics in the MOOC “Web Technologies”, the proposed method is evaluated. Both the general trend and the high accuracy of selected key segments (over 70%) prove the effectiveness of the proposed method.}, address = {Austin, Texas, USA}, author = {Che, Xiaoyin and Staubitz, Thomas and Yang, Haojin and Meinel, Christoph}, booktitle = {Proceedings of The 16th IEEE International Conference on Advanced Learning Technology (ICALT2016)}, keywords = {Teacher’s_Focus MOOC its Pre-Course Key_Segment}, month = 7, title = {Pre-Course Key Segment Analysis of Online Lecture Videos}, year = 2016 }
  Further Information

  AbstractIn this paper we propose a method to evaluate the importance of lecture video segments in online courses. The video will be first segmented based on the slide transition. Then we evaluate the importance of each segment based on our analysis of the teacher’s focus. This focus is mainly identified by exploring features in the slide and the speech. Since the whole analysis process is based on multimedia materials, it could be done before the official start of the course. By setting survey questions and collecting forum statistics in the MOOC “Web Technologies”, the proposed method is evaluated. Both the general trend and the high accuracy of selected key segments (over 70%) prove the effectiveness of the proposed method.
• 
  Xiaoyin Che, S.L., Meinel, C.: An attempt at mooc localization for chinese-speaking users.International Journal of Information and Education Technology, Volume 6, Number 2. pp. 90-96 (2016).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Abstract—“Internetworking with TCP/IP” is a massive open online course (MOOC) provided by Germany-based MOOC platform “openHPI”, which has been offered in German, English and – recently – Chinese respectively, with similar content. In this paper, the authors, who worked jointly as a teacher (or as teaching assistants) in this course, want to share their ideas derived from daily teaching experiences, analysis of the statistics, comparison between the performance in different language offers and the feedback from user questionnaires. Additionally, the motivation, attempt and suggestion at MOOC localization will also be discussed.
  @inproceedings{2014_Che_ICDEL, abstract = {Abstract—“Internetworking with TCP/IP” is a massive open online course (MOOC) provided by Germany-based MOOC platform “openHPI”, which has been offered in German, English and – recently – Chinese respectively, with similar content. In this paper, the authors, who worked jointly as a teacher (or as teaching assistants) in this course, want to share their ideas derived from daily teaching experiences, analysis of the statistics, comparison between the performance in different language offers and the feedback from user questionnaires. Additionally, the motivation, attempt and suggestion at MOOC localization will also be discussed.}, author = {{Xiaoyin Che, Sheng Luo}, Cheng Wang and Meinel, Christoph}, booktitle = {International Journal of Information and Education Technology, Volume 6, Number 2}, keywords = {MOOC openHPI its Chinese-speaking_users Localization}, pages = {90-96}, title = {An attempt at mooc localization for chinese-speaking users}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/10.7763/IJIET.2016.V6.665

  AbstractAbstract—“Internetworking with TCP/IP” is a massive open online course (MOOC) provided by Germany-based MOOC platform “openHPI”, which has been offered in German, English and – recently – Chinese respectively, with similar content. In this paper, the authors, who worked jointly as a teacher (or as teaching assistants) in this course, want to share their ideas derived from daily teaching experiences, analysis of the statistics, comparison between the performance in different language offers and the feedback from user questionnaires. Additionally, the motivation, attempt and suggestion at MOOC localization will also be discussed.
• 
  Staubitz, T., Klement, H., Teusner, R., Renz, J., Meinel, C.: CodeOcean - A Versatile Platform for Practical Programming Excercises in Online Environments.Proceedings of IEEE Global Engineering Education Conference (EDUCON2016). IEEE (2016).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2016_Staubitz_Educon, author = {Staubitz, Thomas and Klement, Hauke and Teusner, Ralf and Renz, Jan and Meinel, Christoph}, booktitle = {Proceedings of IEEE Global Engineering Education Conference (EDUCON2016)}, keywords = {its}, publisher = {IEEE}, title = {CodeOcean - A Versatile Platform for Practical Programming Excercises in Online Environments}, year = 2016 }
  Further Information
• 
  Bauer, M., Malchow, M., Staubitz, T., Meinel, C.: Improving Collaborative Learning With Video Lectures.INTED2016 Proceedings. 10th International Technology, Education and Development Conference Valencia, Spain. 7-9 March, 2016. pp. 5511-5517. IATED (2016).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  We have addressed the problems of independent e-lecture learning with an approach involving collaborative learning with lecture recordings. In order to make this type of learning possible, we have prototypically enhanced the video player of a lecture video platform with functionality that allows simultaneous viewing of a lecture on two or more computers. While watching the video, synchronization of the playback and every click event, such as play, pause, seek, and playback speed adjustment can be carried out. We have also added the option of annotating slides. With this approach, it is possible for learners to watch a lecture together, even though they are in different places. In this way, the benefits of collaborative learning can also be used when learning online. Now, it is more likely that learners stay focused on the lecture for a longer time (as the collaboration creates an additional obligation not to leave early and desert a friend). Furthermore, the learning outcome is higher because learners can ask their friends questions and explain things to each other as well as mark important points in the lecture video.
  @inproceedings{Matthias2016a, abstract = {We have addressed the problems of independent e-lecture learning with an approach involving collaborative learning with lecture recordings. In order to make this type of learning possible, we have prototypically enhanced the video player of a lecture video platform with functionality that allows simultaneous viewing of a lecture on two or more computers. While watching the video, synchronization of the playback and every click event, such as play, pause, seek, and playback speed adjustment can be carried out. We have also added the option of annotating slides. With this approach, it is possible for learners to watch a lecture together, even though they are in different places. In this way, the benefits of collaborative learning can also be used when learning online. Now, it is more likely that learners stay focused on the lecture for a longer time (as the collaboration creates an additional obligation not to leave early and desert a friend). Furthermore, the learning outcome is higher because learners can ask their friends questions and explain things to each other as well as mark important points in the lecture video.}, author = {Bauer, Matthias and Malchow, Martin and Staubitz, Thomas and Meinel, Christoph}, booktitle = {INTED2016 Proceedings. 10th International Technology, Education and Development Conference Valencia, Spain. 7-9 March, 2016.}, keywords = {MOOC Didactics E-Learning E-Lecture its Collaborative_Learning Learning_Analytics}, month = 3, pages = {5511-5517}, publisher = {IATED}, title = {Improving Collaborative Learning With Video Lectures}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/http://dx.doi.org/10.21125/inted.2016.0322

  AbstractWe have addressed the problems of independent e-lecture learning with an approach involving collaborative learning with lecture recordings. In order to make this type of learning possible, we have prototypically enhanced the video player of a lecture video platform with functionality that allows simultaneous viewing of a lecture on two or more computers. While watching the video, synchronization of the playback and every click event, such as play, pause, seek, and playback speed adjustment can be carried out. We have also added the option of annotating slides. With this approach, it is possible for learners to watch a lecture together, even though they are in different places. In this way, the benefits of collaborative learning can also be used when learning online. Now, it is more likely that learners stay focused on the lecture for a longer time (as the collaboration creates an additional obligation not to leave early and desert a friend). Furthermore, the learning outcome is higher because learners can ask their friends questions and explain things to each other as well as mark important points in the lecture video.
• 
  Luo, S., Yang, H., Wang, C., Che, X., Meinel, C.: Action Recognition in Surveillance Video Using ConvNets and Motion History Image.Artificial Neural Networks and Machine Learning – ICANN 2016. pp. 187-195. Springer (2016).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  With significant increasing of surveillance cameras, the amount of surveillance videos is growing rapidly. Thereby how to automatically and efficiently recognize semantic actions and events in surveillance videos becomes an important problem to be addressed. In this paper, we investigate the state-of-the-art Deep Learning (DL) approaches for human action recognition, and propose an improved two-stream ConvNets architecture for this task. In particular, we propose to use Motion History Image (MHI) as motion expression for training the temporal ConvNet, which achieved impressive results in both accuracy and recognition speed. In our experiment, we conducted an in-depth study to investigate important network options and compared to the latest deep network for action recognition. The detailed evaluation results show the superior ability of our proposed approach, which achieves state-of-the-art in surveillance video context.
  @inproceedings{2016_LUO_ICANN, abstract = {With significant increasing of surveillance cameras, the amount of surveillance videos is growing rapidly. Thereby how to automatically and efficiently recognize semantic actions and events in surveillance videos becomes an important problem to be addressed. In this paper, we investigate the state-of-the-art Deep Learning (DL) approaches for human action recognition, and propose an improved two-stream ConvNets architecture for this task. In particular, we propose to use Motion History Image (MHI) as motion expression for training the temporal ConvNet, which achieved impressive results in both accuracy and recognition speed. In our experiment, we conducted an in-depth study to investigate important network options and compared to the latest deep network for action recognition. The detailed evaluation results show the superior ability of our proposed approach, which achieves state-of-the-art in surveillance video context.}, author = {Luo, Sheng and Yang, Haojin and Wang, Cheng and Che, Xiaoyin and Meinel, Christoph}, booktitle = {Artificial Neural Networks and Machine Learning – ICANN 2016}, keywords = {its Optical_flow Convolutional_neural_network Motion_History_Image Surveillance_videos}, month = 8, pages = {187-195}, publisher = {Springer}, title = {Action Recognition in Surveillance Video Using ConvNets and Motion History Image}, year = 2016 }
  Further Information

  URNhttp://dx.doi.org/10.1007/978-3-319-44781-0_23

  AbstractWith significant increasing of surveillance cameras, the amount of surveillance videos is growing rapidly. Thereby how to automatically and efficiently recognize semantic actions and events in surveillance videos becomes an important problem to be addressed. In this paper, we investigate the state-of-the-art Deep Learning (DL) approaches for human action recognition, and propose an improved two-stream ConvNets architecture for this task. In particular, we propose to use Motion History Image (MHI) as motion expression for training the temporal ConvNet, which achieved impressive results in both accuracy and recognition speed. In our experiment, we conducted an in-depth study to investigate important network options and compared to the latest deep network for action recognition. The detailed evaluation results show the superior ability of our proposed approach, which achieves state-of-the-art in surveillance video context.
• 
  Staubitz, T., Petrick, D., Bauer, M., Renz, J., Meinel, C.: Improving the Peer Assessment Experience on MOOC Platforms.Proceedings of ACM Learning at Scale Conference (L@S2016). ACM (2016).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  Massive Open Online Courses (MOOCs) have revolutionized higher education by offering university-like courses for a large amount of learners via the Internet. The paper at hand takes a closer look on peer assessment as a tool for delivering individualized feedback and engaging assignments to MOOC participants. Benefits, such as scalability for MOOCs and higher order learning, and challenges, such as grading accuracy and rogue reviewers, are described. Common practices and the state-of-the-art to counteract challenges are highlighted. Based on this research, the paper at hand describes a peer assessment workflow and its implementation on the openHPI and openSAP MOOC platforms. This workflow combines the best practices of existing peer assessment tools and introduces some small but crucial improvements.
  @inproceedings{2016_Staubitz_LatS, abstract = {Massive Open Online Courses (MOOCs) have revolutionized higher education by offering university-like courses for a large amount of learners via the Internet. The paper at hand takes a closer look on peer assessment as a tool for delivering individualized feedback and engaging assignments to MOOC participants. Benefits, such as scalability for MOOCs and higher order learning, and challenges, such as grading accuracy and rogue reviewers, are described. Common practices and the state-of-the-art to counteract challenges are highlighted. Based on this research, the paper at hand describes a peer assessment workflow and its implementation on the openHPI and openSAP MOOC platforms. This workflow combines the best practices of existing peer assessment tools and introduces some small but crucial improvements.}, author = {Staubitz, Thomas and Petrick, Dominic and Bauer, Matthias and Renz, Jan and Meinel, Christoph}, booktitle = {Proceedings of ACM Learning at Scale Conference (L@S2016)}, keywords = {e-learning myown assessment mooc peerassessment}, publisher = {ACM}, title = {Improving the Peer Assessment Experience on MOOC Platforms}, year = 2016 }
  Further Information

  AbstractMassive Open Online Courses (MOOCs) have revolutionized higher education by offering university-like courses for a large amount of learners via the Internet. The paper at hand takes a closer look on peer assessment as a tool for delivering individualized feedback and engaging assignments to MOOC participants. Benefits, such as scalability for MOOCs and higher order learning, and challenges, such as grading accuracy and rogue reviewers, are described. Common practices and the state-of-the-art to counteract challenges are highlighted. Based on this research, the paper at hand describes a peer assessment workflow and its implementation on the openHPI and openSAP MOOC platforms. This workflow combines the best practices of existing peer assessment tools and introduces some small but crucial improvements.

2015 [ to top ]

• 
  Renz, J., Bauer, M., Malchow, M., Staubitz, T., Meinel, C.: Optimizing the Video Experience in MOOCs.Proceedings of the 7th International Conference on Education and New Learning Technologies (EduLearn). IATED, Barcelona, Spain (2015).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2015_Renz_EduLearn, address = {Barcelona, Spain}, author = {Renz, Jan and Bauer, Matthias and Malchow, Martin and Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proceedings of the 7th International Conference on Education and New Learning Technologies (EduLearn)}, keywords = {Web_University its}, publisher = {IATED}, title = {Optimizing the Video Experience in MOOCs}, year = 2015 }
  Further Information
• 
  Bauer, M., Malchow, M., Meinel, C.: Enhance Teleteaching Videos with Semantic Technologies. In: Uskov, V.L., Howlett, R.J., and Jain, L.C. (eds.) Smart Education and Smart e-Learning. pp. 105-115. Springer International Publishing (2015).
  [ BibTeX ] [ Details ]
   
  @inbook{Matthias2015a, author = {Bauer, Matthias and Malchow, Martin and Meinel, Christoph}, booktitle = {Smart Education and Smart e-Learning}, chapter = {Enhance Teleteaching Videos with Semantic Technologies}, edition = {Smart Education and Smart e-Learning}, editor = {Uskov, Vladimir L. and Howlett, Robert J. and Jain, Lakhmi C.}, keywords = {Web_University tele-TASK its}, pages = {105-115}, publisher = {Springer International Publishing}, series = {Smart Innovation, Systems and Technologies}, title = {Enhance Teleteaching Videos with Semantic Technologies}, volume = 41, year = 2015 }
  Further Information

  Editor(s)Uskov, Vladimir L. and Howlett, Robert J. and Jain, Lakhmi C.

  URNhttp://dx.doi.org/10.1007/978-3-319-19875-0_10
• 
  Malchow, M., Bauer, M., Meinel, C.: Enhance Lecture Archive Search with OCR Slide Detection and In-Memory Database Technology.2015 IEEE 18th International Conference on Computational Science and Engineering (CSE). pp. 176-183. IEEE (2015).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  On the Web there are a lot of frequently used video lecture archives which have grown up fast during the last couple of years. This fact led to a lot of lecture recordings which include knowledge for a variety of subjects. The typical way of searching these videos is by title and description. Unfortunately, not all important keywords and facts are mentioned in the title or description if they are available. Furthermore, there is no possibility to analyze how important those detected keywords are for the whole video. Another lecture archive specific virtue is that every regular university lecture is repeated yearly. Normally this will lead to duplicate lecture recordings. In search results doubling is disturbing for students when they want to watch the most recent lectures from the search result. This paper deals with the idea to resolve these problems by analyzing the recorded lecture slides with Optical Character Recognition (OCR). In addition to the name and description the OCR data will be used for a full text analysis to create an index for the lecture archive search. Furthermore, a fuzzy search is introduced. This will solve the issue of misspelled search requests and OCR detection defects. Additionally, this paper deals with the performance issues of a full text search with an in-memory database, issues in OCR detection, handling duplicate recordings of lectures repeated every year. Finally, an evaluation of the search performance in comparison with other database ideas besides the in-memory database is performed. Additionally, a user acceptability survey for the search results to increase the learning experience on lecture archives was performed. As a result, this paper shows how to handle the big amount of OCR data for a full text live search performed on an in-memory database in reasonable time. During this search a fuzzy search is performed additionally to resolve spelling mistakes and OCR detection problems. In conclusion this paper shows a solution for an enhanced video lecture archive search that supports students in online research processes and enhances their learning experience.
  @inproceedings{Martin2015c, abstract = {On the Web there are a lot of frequently used video lecture archives which have grown up fast during the last couple of years. This fact led to a lot of lecture recordings which include knowledge for a variety of subjects. The typical way of searching these videos is by title and description. Unfortunately, not all important keywords and facts are mentioned in the title or description if they are available. Furthermore, there is no possibility to analyze how important those detected keywords are for the whole video. Another lecture archive specific virtue is that every regular university lecture is repeated yearly. Normally this will lead to duplicate lecture recordings. In search results doubling is disturbing for students when they want to watch the most recent lectures from the search result. This paper deals with the idea to resolve these problems by analyzing the recorded lecture slides with Optical Character Recognition (OCR). In addition to the name and description the OCR data will be used for a full text analysis to create an index for the lecture archive search. Furthermore, a fuzzy search is introduced. This will solve the issue of misspelled search requests and OCR detection defects. Additionally, this paper deals with the performance issues of a full text search with an in-memory database, issues in OCR detection, handling duplicate recordings of lectures repeated every year. Finally, an evaluation of the search performance in comparison with other database ideas besides the in-memory database is performed. Additionally, a user acceptability survey for the search results to increase the learning experience on lecture archives was performed. As a result, this paper shows how to handle the big amount of OCR data for a full text live search performed on an in-memory database in reasonable time. During this search a fuzzy search is performed additionally to resolve spelling mistakes and OCR detection problems. In conclusion this paper shows a solution for an enhanced video lecture archive search that supports students in online research processes and enhances their learning experience.}, author = {Malchow, Martin and Bauer, Matthias and Meinel, Christoph}, booktitle = {2015 IEEE 18th International Conference on Computational Science and Engineering (CSE)}, keywords = {In-Memory_Database Tele-Lecturing tele-TASK E-Learning its OCR_Search web_university Distance_Learning Teleteaching Fuzzy_Search}, month = 10, pages = {176-183}, publisher = {IEEE}, title = {Enhance Lecture Archive Search with OCR Slide Detection and In-Memory Database Technology}, year = 2015 }
  Further Information

  URNhttp://dx.doi.org/10.1109/CSE.2015.19

  AbstractOn the Web there are a lot of frequently used video lecture archives which have grown up fast during the last couple of years. This fact led to a lot of lecture recordings which include knowledge for a variety of subjects. The typical way of searching these videos is by title and description. Unfortunately, not all important keywords and facts are mentioned in the title or description if they are available. Furthermore, there is no possibility to analyze how important those detected keywords are for the whole video. Another lecture archive specific virtue is that every regular university lecture is repeated yearly. Normally this will lead to duplicate lecture recordings. In search results doubling is disturbing for students when they want to watch the most recent lectures from the search result. This paper deals with the idea to resolve these problems by analyzing the recorded lecture slides with Optical Character Recognition (OCR). In addition to the name and description the OCR data will be used for a full text analysis to create an index for the lecture archive search. Furthermore, a fuzzy search is introduced. This will solve the issue of misspelled search requests and OCR detection defects. Additionally, this paper deals with the performance issues of a full text search with an in-memory database, issues in OCR detection, handling duplicate recordings of lectures repeated every year. Finally, an evaluation of the search performance in comparison with other database ideas besides the in-memory database is performed. Additionally, a user acceptability survey for the search results to increase the learning experience on lecture archives was performed. As a result, this paper shows how to handle the big amount of OCR data for a full text live search performed on an in-memory database in reasonable time. During this search a fuzzy search is performed additionally to resolve spelling mistakes and OCR detection problems. In conclusion this paper shows a solution for an enhanced video lecture archive search that supports students in online research processes and enhances their learning experience.
• 
  Malchow, M., Bauer, M., Meinel, C.: Self-Test Integration in Lecture Video Archives.ICERI2015 Proceedings - 8th International Conference of Education, Research and Innovation. pp. 7631-7638. IATED (2015).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Lecture video archives offer hundreds of lectures. Students have to watch lecture videos in a lecture archive without any feedback. They do not know if they understood everything correctly in comparison to MOOCs (Massive Open Online Course) where a direct feedback with self-tests or assignments is common. In contrast to MOOCs, video lecture archives normally do not offer self-test or assignment sections after every video. Due to this behavior of lecture archives questions have to be made visible on the video page. Furthermore, lecture recording videos are typically longer than videos in MOOCs. So, it is not so reasonable and sometimes even demotivating to ask a lot of questions after a long video when not all information is already memorized by the student. The approach of this paper is to overcome these self-test problems in lecture video archives and to finally solve them in a reasonable way to increase the learning experience and support students to learn more efficient with recorded lecture videos.
  @inproceedings{Martin2015b, abstract = {Lecture video archives offer hundreds of lectures. Students have to watch lecture videos in a lecture archive without any feedback. They do not know if they understood everything correctly in comparison to MOOCs (Massive Open Online Course) where a direct feedback with self-tests or assignments is common. In contrast to MOOCs, video lecture archives normally do not offer self-test or assignment sections after every video. Due to this behavior of lecture archives questions have to be made visible on the video page. Furthermore, lecture recording videos are typically longer than videos in MOOCs. So, it is not so reasonable and sometimes even demotivating to ask a lot of questions after a long video when not all information is already memorized by the student. The approach of this paper is to overcome these self-test problems in lecture video archives and to finally solve them in a reasonable way to increase the learning experience and support students to learn more efficient with recorded lecture videos.}, author = {Malchow, Martin and Bauer, Matthias and Meinel, Christoph}, booktitle = {ICERI2015 Proceedings - 8th International Conference of Education, Research and Innovation}, keywords = {e-learning user_feedback assessment tele-TASK self-test its lecture_video_archive web_university}, month = 11, pages = {7631-7638}, publisher = {IATED}, title = {Self-Test Integration in Lecture Video Archives}, year = 2015 }
  Further Information

  AbstractLecture video archives offer hundreds of lectures. Students have to watch lecture videos in a lecture archive without any feedback. They do not know if they understood everything correctly in comparison to MOOCs (Massive Open Online Course) where a direct feedback with self-tests or assignments is common. In contrast to MOOCs, video lecture archives normally do not offer self-test or assignment sections after every video. Due to this behavior of lecture archives questions have to be made visible on the video page. Furthermore, lecture recording videos are typically longer than videos in MOOCs. So, it is not so reasonable and sometimes even demotivating to ask a lot of questions after a long video when not all information is already memorized by the student. The approach of this paper is to overcome these self-test problems in lecture video archives and to finally solve them in a reasonable way to increase the learning experience and support students to learn more efficient with recorded lecture videos.
• 
  v. Löwis, M., Staubitz, T., Teusner, R., Renz, J., Tannert, S., Meinel, C.: Scaling Youth Development Training in IT Using an xMOOC Platform.Proceedings of the IEEE Frontiers in Education. IEEE, El Paso, TX, USA (2015).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2015_LOWIS_FIE, address = {El Paso, TX, USA}, author = {v. Löwis, Martin and Staubitz, Thomas and Teusner, Ralf and Renz, Jan and Tannert, Susanne and Meinel, Christoph}, booktitle = {Proceedings of the IEEE Frontiers in Education}, keywords = {its}, publisher = {IEEE}, title = {Scaling Youth Development Training in IT Using an xMOOC Platform}, year = 2015 }
  Further Information

  URNhttp://dx.doi.org/10.1109/FIE.2015.7344145
• 
  Renz, J., Bauer, M., Malchow, M., Staubitz, T., Meinel, C.: Optimizing the Video Experience in MOOCs.Proceedings of the 7th International Conference on Education and New Learning Technologies (EduLearn). IATED, Barcelona, Spain (2015).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2015_Renz_EduLearn, address = {Barcelona, Spain}, author = {Renz, Jan and Bauer, Matthias and Malchow, Martin and Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proceedings of the 7th International Conference on Education and New Learning Technologies (EduLearn)}, keywords = {e-learning myown mooc}, publisher = {IATED}, title = {Optimizing the Video Experience in MOOCs}, year = 2015 }
  Further Information
• 
  Che, X., Yang, H., Meinel, C.: Table Detection from Slide Images.Pacific-Rim Symposium on Image and Video Technology. pp. 762-774. , Auckland, New Zealand (2015).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In this paper we propose a solution to detect tables from slide images. Presentation slides are one type of document with growing importance. But the layout difference between slides and traditional documents makes many existing table detection methods less effective on slides. The proposed solution works with both high-resolution slide images from digital files and low-resolution slide screenshots from videos. By taking OCR (Optical Character Recognition) as initial step, a heuristic analysis on page layout focuses not only on the table structure but also the textual content. The evaluation result shows that the proposed solution achieves an approximate accuracy of 80 %. It is way better than the open-source academic solution Tesseract and also outperforms the commercial software ABBYY FineReader, which is supposed to be one of the best table detection tools.
  @inproceedings{2015_Che_PSIVT, abstract = {In this paper we propose a solution to detect tables from slide images. Presentation slides are one type of document with growing importance. But the layout difference between slides and traditional documents makes many existing table detection methods less effective on slides. The proposed solution works with both high-resolution slide images from digital files and low-resolution slide screenshots from videos. By taking OCR (Optical Character Recognition) as initial step, a heuristic analysis on page layout focuses not only on the table structure but also the textual content. The evaluation result shows that the proposed solution achieves an approximate accuracy of 80 %. It is way better than the open-source academic solution Tesseract and also outperforms the commercial software ABBYY FineReader, which is supposed to be one of the best table detection tools.}, address = {Auckland, New Zealand}, author = {Che, Xiaoyin and Yang, Haojin and Meinel, Christoph}, booktitle = {Pacific-Rim Symposium on Image and Video Technology}, keywords = {Table_detection its Slide_image Table_structure}, month = 11, pages = {762-774}, title = {Table Detection from Slide Images}, year = 2015 }
  Further Information

  URNhttp://dx.doi.org/10.1007/978-3-319-29451-3_60

  AbstractIn this paper we propose a solution to detect tables from slide images. Presentation slides are one type of document with growing importance. But the layout difference between slides and traditional documents makes many existing table detection methods less effective on slides. The proposed solution works with both high-resolution slide images from digital files and low-resolution slide screenshots from videos. By taking OCR (Optical Character Recognition) as initial step, a heuristic analysis on page layout focuses not only on the table structure but also the textual content. The evaluation result shows that the proposed solution achieves an approximate accuracy of 80 %. It is way better than the open-source academic solution Tesseract and also outperforms the commercial software ABBYY FineReader, which is supposed to be one of the best table detection tools.
• 
  v. Löwis, M., Staubitz, T., Teusner, R., Renz, J., Tannert, S., Meinel, C.: Scaling Youth Development Training in IT Using an xMOOC Platform.Proceedings of the IEEE Frontiers in Education. IEEE, El Paso, TX, USA (2015).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2015_LOWIS_FIE, address = {El Paso, TX, USA}, author = {v. Löwis, Martin and Staubitz, Thomas and Teusner, Ralf and Renz, Jan and Tannert, Susanne and Meinel, Christoph}, booktitle = {Proceedings of the IEEE Frontiers in Education}, keywords = {e-learning myown assessment k-12 mooc assignment}, publisher = {IEEE}, title = {Scaling Youth Development Training in IT Using an xMOOC Platform}, year = 2015 }
  Further Information

  URNhttp://dx.doi.org/10.1109/FIE.2015.7344145
• 
  Yang, H., Wang, C., Che, X., Luo, S., Meinel, C.: An Improved System For Real-Time Scene Text Recognition.Proceedings of the 5th ACM on International Conference on Multimedia Retrieval (ICMR 2015). pp. 657-660. , Shanghai, China (2015).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In this paper we showcase a system for real-time text detection and recognition. We apply deep features created by Convolutional Neural Networks (CNNs) for both text detection and word recognition task. For text detection we follow the common localization-verification scheme which already shown its excellent ability in numerous previous work. In text localization stage, textual regions are roughly detected by using a MSERs (Maximally Stable Extremal Regions) detector with high recall rate. False alarms are then eliminated by using a CNNs classifier, and remaining text regions are further grouped into words. In the word recognition stage, we developed an skeleton-based text binarization method for segmenting text from its background. A CNNs based recognizer is then applied for recognizing character. The initial experiments show the powerful ability of deep features for text classification comparing with commonly used visual features. Our current implementation demonstrates real-time performance for recognizing scene text by using a standard PC with webcam.
  @inproceedings{2015_Yang_ICMR, abstract = {In this paper we showcase a system for real-time text detection and recognition. We apply deep features created by Convolutional Neural Networks (CNNs) for both text detection and word recognition task. For text detection we follow the common localization-verification scheme which already shown its excellent ability in numerous previous work. In text localization stage, textual regions are roughly detected by using a MSERs (Maximally Stable Extremal Regions) detector with high recall rate. False alarms are then eliminated by using a CNNs classifier, and remaining text regions are further grouped into words. In the word recognition stage, we developed an skeleton-based text binarization method for segmenting text from its background. A CNNs based recognizer is then applied for recognizing character. The initial experiments show the powerful ability of deep features for text classification comparing with commonly used visual features. Our current implementation demonstrates real-time performance for recognizing scene text by using a standard PC with webcam.}, address = {Shanghai, China}, author = {Yang, Haojin and Wang, Cheng and Che, Xiaoyin and Luo, Sheng and Meinel, Christoph}, booktitle = {Proceedings of the 5th ACM on International Conference on Multimedia Retrieval (ICMR 2015)}, keywords = {Algorithms Experimentation its Demonstration}, month = 6, pages = {657-660}, title = {An Improved System For Real-Time Scene Text Recognition}, year = 2015 }
  Further Information

  URNhttp://dx.doi.org/10.1145/2671188.2749352

  AbstractIn this paper we showcase a system for real-time text detection and recognition. We apply deep features created by Convolutional Neural Networks (CNNs) for both text detection and word recognition task. For text detection we follow the common localization-verification scheme which already shown its excellent ability in numerous previous work. In text localization stage, textual regions are roughly detected by using a MSERs (Maximally Stable Extremal Regions) detector with high recall rate. False alarms are then eliminated by using a CNNs classifier, and remaining text regions are further grouped into words. In the word recognition stage, we developed an skeleton-based text binarization method for segmenting text from its background. A CNNs based recognizer is then applied for recognizing character. The initial experiments show the powerful ability of deep features for text classification comparing with commonly used visual features. Our current implementation demonstrates real-time performance for recognizing scene text by using a standard PC with webcam.
• 
  Malchow, M., Bauer, M., Meinel, C.: Lecture Butler - Teaching Reasonable Lectures from a Lecture Video Archive.Proceedings of the 2015 ACM Annual Conference on SIGUCCS. pp. 3-9. ACM (2015).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Lecture video archives offer a large variety of lecture recordings in different topics. Naturally, topics are described superficially, easily or detailed in different lectures. Users interested in certain topics have problems finding lectures describing a topic chronology from basic lectures to more detailed difficult lectures. The Lecture Butler is going to automatically offer e-learning students lectures for the topics of interest in chronological playlists. The approach is finding lecture information using title, description, OCR and ASR data. This data is indexed and searched by an in-memory database to fulfill the speed requirements for playlist creation. In the search results lectures are going to be ordered by lecture occurrence in the university semester time schedule or by given lecture level of difficulty. As a result students can automatically create playlists for their topic of interest in sequence of the lecture level. Hence, students are not overstrained by lectures when they start with basic lectures first. Basic lectures provide information to understand more complex lectures. The research shows that an automatic approach by adding the level of difficulty or university semester time table is going to show reasonable playlists to find topics of interest. This solves the main problem students encounter when they try to learn a topic step-by-step using recorded lectures. The approach will support and motivate students using e-learning opportunities.
  @inproceedings{Martin2015a, abstract = {Lecture video archives offer a large variety of lecture recordings in different topics. Naturally, topics are described superficially, easily or detailed in different lectures. Users interested in certain topics have problems finding lectures describing a topic chronology from basic lectures to more detailed difficult lectures. The Lecture Butler is going to automatically offer e-learning students lectures for the topics of interest in chronological playlists. The approach is finding lecture information using title, description, OCR and ASR data. This data is indexed and searched by an in-memory database to fulfill the speed requirements for playlist creation. In the search results lectures are going to be ordered by lecture occurrence in the university semester time schedule or by given lecture level of difficulty. As a result students can automatically create playlists for their topic of interest in sequence of the lecture level. Hence, students are not overstrained by lectures when they start with basic lectures first. Basic lectures provide information to understand more complex lectures. The research shows that an automatic approach by adding the level of difficulty or university semester time table is going to show reasonable playlists to find topics of interest. This solves the main problem students encounter when they try to learn a topic step-by-step using recorded lectures. The approach will support and motivate students using e-learning opportunities.}, author = {Malchow, Martin and Bauer, Matthias and Meinel, Christoph}, booktitle = {Proceedings of the 2015 ACM Annual Conference on SIGUCCS}, keywords = {In-Memory_Database Tele-Lecturing tele-TASK E-Learning its Lecture_Video_Archive OCR_Search web_university Distance_Learning Semantic_Web Teleteaching}, month = 11, pages = {3-9}, publisher = {ACM}, title = {Lecture Butler - Teaching Reasonable Lectures from a Lecture Video Archive}, year = 2015 }
  Further Information

  URNhttp://dx.doi.org/10.1145/2815546.2815557

  AbstractLecture video archives offer a large variety of lecture recordings in different topics. Naturally, topics are described superficially, easily or detailed in different lectures. Users interested in certain topics have problems finding lectures describing a topic chronology from basic lectures to more detailed difficult lectures. The Lecture Butler is going to automatically offer e-learning students lectures for the topics of interest in chronological playlists. The approach is finding lecture information using title, description, OCR and ASR data. This data is indexed and searched by an in-memory database to fulfill the speed requirements for playlist creation. In the search results lectures are going to be ordered by lecture occurrence in the university semester time schedule or by given lecture level of difficulty. As a result students can automatically create playlists for their topic of interest in sequence of the lecture level. Hence, students are not overstrained by lectures when they start with basic lectures first. Basic lectures provide information to understand more complex lectures. The research shows that an automatic approach by adding the level of difficulty or university semester time table is going to show reasonable playlists to find topics of interest. This solves the main problem students encounter when they try to learn a topic step-by-step using recorded lectures. The approach will support and motivate students using e-learning opportunities.
• 
  Luo, S., Yang, H., Meinel, C.: Reward-based Intermittent Reinforcement in Gamification for E-learning.Proceedings of the 7th International Conference on Computer Supported Education. pp. 177-184. , Lisbon, Portugal (2015).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Nowadays gamification is a hot topic in the world, a lot of websites, applications and researches adapt this method to arouse users' motivation. From the past experience, gamification indeed has a positive influence on users' motivation especially in e-learning field. However, the gamification method either is hard to be applied to professional content called meaningful gamification or is negative on user's intrinsic motivation called reward-based gamification. So we study the game addiction mechanism and propose the reward-based intermittent reinforcement method in gamification to take advantage of user independence feature in the latter one and eliminate the negative influence on user's intrinsic motivation. In order to investigate the practicability and integrate effectiveness, we implement this model in our tele-teaching platform.
  @inproceedings{2015_Luo_CSEDU, abstract = {Nowadays gamification is a hot topic in the world, a lot of websites, applications and researches adapt this method to arouse users' motivation. From the past experience, gamification indeed has a positive influence on users' motivation especially in e-learning field. However, the gamification method either is hard to be applied to professional content called meaningful gamification or is negative on user's intrinsic motivation called reward-based gamification. So we study the game addiction mechanism and propose the reward-based intermittent reinforcement method in gamification to take advantage of user independence feature in the latter one and eliminate the negative influence on user's intrinsic motivation. In order to investigate the practicability and integrate effectiveness, we implement this model in our tele-teaching platform.}, address = {Lisbon, Portugal}, author = {Luo, Sheng and Yang, Haojin and Meinel, Christoph}, booktitle = {Proceedings of the 7th International Conference on Computer Supported Education}, keywords = {Reward-based E-learning Intermittent_Reinforcement its Gamification}, month = 8, pages = {177-184}, title = {Reward-based Intermittent Reinforcement in Gamification for E-learning}, year = 2015 }
  Further Information

  URNhttp://dx.doi.org/10.5220/0005402201770184

  AbstractNowadays gamification is a hot topic in the world, a lot of websites, applications and researches adapt this method to arouse users' motivation. From the past experience, gamification indeed has a positive influence on users' motivation especially in e-learning field. However, the gamification method either is hard to be applied to professional content called meaningful gamification or is negative on user's intrinsic motivation called reward-based gamification. So we study the game addiction mechanism and propose the reward-based intermittent reinforcement method in gamification to take advantage of user independence feature in the latter one and eliminate the negative influence on user's intrinsic motivation. In order to investigate the practicability and integrate effectiveness, we implement this model in our tele-teaching platform.
• 
  Staubitz, T., Pfeiffer, T., Renz, J., Willems, C., Meinel, C.: Collaborative Learning in a MOOC Environment.Proceedings of the 8th annual International Conference of Education, Research and Innovation. pp. 8237-8246. IATED, Seville, Spain (2015).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2015_Staubitz_ICERI, address = {Seville, Spain}, author = {Staubitz, Thomas and Pfeiffer, Tobias and Renz, Jan and Willems, Christian and Meinel, Christoph}, booktitle = {Proceedings of the 8th annual International Conference of Education, Research and Innovation}, keywords = {its}, pages = {8237-8246}, publisher = {IATED}, title = {Collaborative Learning in a MOOC Environment}, year = 2015 }
  Further Information
• 
  Staubitz, T., Klement, H., Renz, J., Teusner, R., Meinel, C.: Towards Practical Programming Exercises and Automated Assessment in Massive Open Online Courses.Proceedings of the IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE2015). IEEE, Zhuhai, China (2015).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2015_Staubitz_TALE, address = {Zhuhai, China}, author = {Staubitz, Thomas and Klement, Hauke and Renz, Jan and Teusner, Ralf and Meinel, Christoph}, booktitle = {Proceedings of the IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE2015)}, keywords = {its}, publisher = {IEEE}, title = {Towards Practical Programming Exercises and Automated Assessment in Massive Open Online Courses}, year = 2015 }
  Further Information
• 
  Che, X., Yang, H., Meinel, C.: Adaptive E-Lecture Video Outline Extraction Based on Slides Analysis.Proceedings of 2015 International Conference on Advances in Web-Based Learning (ICWL2015). pp. 59-68. , Guangzhou, China (2015).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In this paper, we propose an automated adaptive solution to generate logical, accurate and detailed tree-structure outline for video-based online lectures, by extracting the attached slides and reconstructing their content. The proposed solution begins with slide-transition detection and optical character recognition, and then proceeds by a static method of analyzing the layout of single slide and the logical relations within the slides series. Some features about the under-processing slides series, such as a �xed title position, will be �gured out and applied in the adaptive rounds to improve the outline quality. The result of our experiments shows that the general accuracy of the �nal lecture outline reaches 85%, which is about 13% higher than the static method.
  @inproceedings{2015_Che_ICWL, abstract = {In this paper, we propose an automated adaptive solution to generate logical, accurate and detailed tree-structure outline for video-based online lectures, by extracting the attached slides and reconstructing their content. The proposed solution begins with slide-transition detection and optical character recognition, and then proceeds by a static method of analyzing the layout of single slide and the logical relations within the slides series. Some features about the under-processing slides series, such as a �xed title position, will be �gured out and applied in the adaptive rounds to improve the outline quality. The result of our experiments shows that the general accuracy of the �nal lecture outline reaches 85%, which is about 13% higher than the static method.}, address = {Guangzhou, China}, author = {Che, Xiaoyin and Yang, Haojin and Meinel, Christoph}, booktitle = {Proceedings of 2015 International Conference on Advances in Web-Based Learning (ICWL2015)}, keywords = {Lecture_Outline E-Learning its Adaptive_Slides_Analysis}, month = 11, pages = {59-68}, title = {Adaptive E-Lecture Video Outline Extraction Based on Slides Analysis}, year = 2015 }
  Further Information

  URNhttp://dx.doi.org/10.1007/978-3-319-25515-6_6

  AbstractIn this paper, we propose an automated adaptive solution to generate logical, accurate and detailed tree-structure outline for video-based online lectures, by extracting the attached slides and reconstructing their content. The proposed solution begins with slide-transition detection and optical character recognition, and then proceeds by a static method of analyzing the layout of single slide and the logical relations within the slides series. Some features about the under-processing slides series, such as a �xed title position, will be �gured out and applied in the adaptive rounds to improve the outline quality. The result of our experiments shows that the general accuracy of the �nal lecture outline reaches 85%, which is about 13% higher than the static method.

2014 [ to top ]

• 
  Staubitz, T., Woinar, S., Renz, J., Meinel, C.: Towards Social Gamification - Implementing a Social Graph in an xMOOC Platform.Proc. 7th International Conference of Education, Research and Innovation. , Sevilla, Spain (2014).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2014_Staubitz_iCeri, address = {Sevilla, Spain}, author = {Staubitz, Thomas and Woinar, Sebastian and Renz, Jan and Meinel, Christoph}, booktitle = {Proc. 7th International Conference of Education, Research and Innovation}, keywords = {its}, title = {Towards Social Gamification - Implementing a Social Graph in an xMOOC Platform}, year = 2014 }
  Further Information
• 
  Renz, J., Staubitz, T., Pollack, J., Meinel, C.: Improving the Onboarding User Experience in MOOCs.Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN2014). , Barcelona, Spain (2014).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2014_Renz_EDULEARN, address = {Barcelona, Spain}, author = {Renz, Jan and Staubitz, Thomas and Pollack, Jaqueline and Meinel, Christoph}, booktitle = {Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN2014)}, keywords = {its}, title = {Improving the Onboarding User Experience in MOOCs}, year = 2014 }
  Further Information
• 
  Renz, J., Staubitz, T., Willems, C., Klement, H., Meinel, C.: Handling Re-grading of Automatically Graded Assignments in MOOCs.Proceedings of IEEE Global Engineering Education Conference (EDUCON2014). IEEE, Istanbul, Turkey (2014).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2014_Meinel_EDUCONb, address = {Istanbul, Turkey}, author = {Renz, Jan and Staubitz, Thomas and Willems, Christian and Klement, Hauke and Meinel, Christoph}, booktitle = {Proceedings of IEEE Global Engineering Education Conference (EDUCON2014)}, keywords = {its}, month = 4, publisher = {IEEE}, title = {Handling Re-grading of Automatically Graded Assignments in MOOCs}, year = 2014 }
  Further Information
• 
  Bauer, M., Meinel, C.: A Concept to Analyze User Navigation Behavior Inside a Recorded Lecture (to Identify Difficult Spots).Information Technology Based Higher Education and Training (ITHET). pp. 1-4. IEEE (2014).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  This paper provides a brief report of our concept to scan the streaming server's log files in order to identify specific behavior of the users. A distinct form of behavior is the jump-back. Students do it when they watched a scene of a recorded lecture and then watch it again after a short amount of time. So, it can be assumed that this scene is of higher interest because it is either very interesting or hard to understand for the viewer. The knowledge of these found hotspots could be used in order to improve teaching materials such as slides and teaching style. In this paper, we describe how we plan to gather the data, how to analyze it and how the insights can be utilized. It is not only focused on the technological perspective of video-based e-learning but also on the pedagogical view.
  @inproceedings{Matthias2014a, abstract = {This paper provides a brief report of our concept to scan the streaming server's log files in order to identify specific behavior of the users. A distinct form of behavior is the jump-back. Students do it when they watched a scene of a recorded lecture and then watch it again after a short amount of time. So, it can be assumed that this scene is of higher interest because it is either very interesting or hard to understand for the viewer. The knowledge of these found hotspots could be used in order to improve teaching materials such as slides and teaching style. In this paper, we describe how we plan to gather the data, how to analyze it and how the insights can be utilized. It is not only focused on the technological perspective of video-based e-learning but also on the pedagogical view.}, author = {Bauer, Matthias and Meinel, Christoph}, booktitle = {Information Technology Based Higher Education and Training (ITHET)}, keywords = {its}, month = 9, pages = {1-4}, publisher = {IEEE}, series = {Information Technology Based Higher Education and Training (ITHET)}, title = {A Concept to Analyze User Navigation Behavior Inside a Recorded Lecture (to Identify Difficult Spots)}, year = 2014 }
  Further Information

  URNhttp://dx.doi.org/10.1109/ITHET.2014.7155691

  AbstractThis paper provides a brief report of our concept to scan the streaming server's log files in order to identify specific behavior of the users. A distinct form of behavior is the jump-back. Students do it when they watched a scene of a recorded lecture and then watch it again after a short amount of time. So, it can be assumed that this scene is of higher interest because it is either very interesting or hard to understand for the viewer. The knowledge of these found hotspots could be used in order to improve teaching materials such as slides and teaching style. In this paper, we describe how we plan to gather the data, how to analyze it and how the insights can be utilized. It is not only focused on the technological perspective of video-based e-learning but also on the pedagogical view.
• 
  Willems, C., Renz, J., Staubitz, T., Meinel, C.: Reflections on Enrollment Numbers and Success Rates at the openHPI MOOC Platform.Proceedings of the Second MOOC European Stakeholders Summit (EMOOCs2014). , Lausanne, Switzerland (2014).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2014_Meinel_EMOOCS, address = {Lausanne, Switzerland}, author = {Willems, Christian and Renz, Jan and Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proceedings of the Second MOOC European Stakeholders Summit (EMOOCs2014)}, keywords = {its}, month = 2, title = {Reflections on Enrollment Numbers and Success Rates at the openHPI MOOC Platform}, year = 2014 }
  Further Information
• 
  Malchow, M., Bauer, M., Meinel, C.: The Future of Teleteaching in MOOC Times.2014 IEEE 17th International Conference on Computational Science and Engineering (CSE). pp. 438-443. IEEE (2014).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In the last decades, a lot of different e-learning platforms have established. There are several types of them for example teleteaching platforms. For a couple of years, MOOC platforms have come up and have been enjoying great popularity. In this paper we analyze how important teleteaching platforms are in times of MOOCs. A teleteaching platform is understood as an online service which offers live or recorded lectures as video streams. Furthermore, different concepts how teleteaching can be integrated into MOOC courses are discussed as well as approaches to analyze differences in learning outcome and behavior of students using MOOCs and teleteaching platforms. We analyze if there are urgent factors for the use of teleteaching systems with a view on students' behavior and learn success. It is further discussed how intelligent integration methods can be used to offer students an enhanced learning experience.
  @inproceedings{Martin2014a, abstract = {In the last decades, a lot of different e-learning platforms have established. There are several types of them for example teleteaching platforms. For a couple of years, MOOC platforms have come up and have been enjoying great popularity. In this paper we analyze how important teleteaching platforms are in times of MOOCs. A teleteaching platform is understood as an online service which offers live or recorded lectures as video streams. Furthermore, different concepts how teleteaching can be integrated into MOOC courses are discussed as well as approaches to analyze differences in learning outcome and behavior of students using MOOCs and teleteaching platforms. We analyze if there are urgent factors for the use of teleteaching systems with a view on students' behavior and learn success. It is further discussed how intelligent integration methods can be used to offer students an enhanced learning experience.}, author = {Malchow, Martin and Bauer, Matthias and Meinel, Christoph}, booktitle = {2014 IEEE 17th International Conference on Computational Science and Engineering (CSE)}, keywords = {User_Analysis Educational_institutions Built-in_self-test its Watches teleteaching web_university eLearning MOOC tele-TASK Streaming_media Databases Semantic_Web Collaborative_Learning}, month = 12, pages = {438-443}, publisher = {IEEE}, title = {The Future of Teleteaching in MOOC Times}, year = 2014 }
  Further Information

  URNhttp://dx.doi.org/10.1109/CSE.2014.108

  AbstractIn the last decades, a lot of different e-learning platforms have established. There are several types of them for example teleteaching platforms. For a couple of years, MOOC platforms have come up and have been enjoying great popularity. In this paper we analyze how important teleteaching platforms are in times of MOOCs. A teleteaching platform is understood as an online service which offers live or recorded lectures as video streams. Furthermore, different concepts how teleteaching can be integrated into MOOC courses are discussed as well as approaches to analyze differences in learning outcome and behavior of students using MOOCs and teleteaching platforms. We analyze if there are urgent factors for the use of teleteaching systems with a view on students' behavior and learn success. It is further discussed how intelligent integration methods can be used to offer students an enhanced learning experience.
• 
  Renz, J., Staubitz, T., Meinel, C.: MOOC to Go.Proc. 10th International Conference on Mobile Learning (ML 2014). , Madrid, Spain (2014).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2014_Renz_ML, address = {Madrid, Spain}, author = {Renz, Jan and Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proc. 10th International Conference on Mobile Learning (ML 2014)}, keywords = {its}, title = {MOOC to Go}, year = 2014 }
  Further Information
• 
  Renz, J., Staubitz, T., Willems, C., Klement, H., Meinel, C.: Handling Re-grading of Automatically Graded Assignments in MOOCs.Proceedings of IEEE Global Engineering Education Conference (EDUCON2014). IEEE, Istanbul, Turkey (2014).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2014_Meinel_EDUCONb, address = {Istanbul, Turkey}, author = {Renz, Jan and Staubitz, Thomas and Willems, Christian and Klement, Hauke and Meinel, Christoph}, booktitle = {Proceedings of IEEE Global Engineering Education Conference (EDUCON2014)}, keywords = {e-learning myown assessment mooc}, month = 4, publisher = {IEEE}, title = {Handling Re-grading of Automatically Graded Assignments in MOOCs}, year = 2014 }
  Further Information
• 
  Staubitz, T., Renz, J., Willems, C., Meinel, C.: Supporting Social Interaction and Collaboration on an xMOOC Platform.Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN14). , Barcelona, Spain (2014).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2014_Staubitz_EDULEARN, address = {Barcelona, Spain}, author = {Staubitz, Thomas and Renz, Jan and Willems, Christian and Meinel, Christoph}, booktitle = {Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN14)}, keywords = {its}, title = {Supporting Social Interaction and Collaboration on an xMOOC Platform}, year = 2014 }
  Further Information
• 
  Renz, J., Staubitz, T., Meinel, C.: MOOC to Go.Proc. 10th International Conference on Mobile Learning (ML 2014). , Madrid, Spain (2014).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2014_Renz_ML, address = {Madrid, Spain}, author = {Renz, Jan and Staubitz, Thomas and Meinel, Christoph}, booktitle = {Proc. 10th International Conference on Mobile Learning (ML 2014)}, keywords = {e-learning myown mooc learning mobile}, title = {MOOC to Go}, year = 2014 }
  Further Information
• 
  Renz, J., Staubitz, T., Pollack, J., Meinel, C.: Improving the Onboarding User Experience in MOOCs.Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN2014). , Barcelona, Spain (2014).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2014_Renz_EDULEARN, address = {Barcelona, Spain}, author = {Renz, Jan and Staubitz, Thomas and Pollack, Jaqueline and Meinel, Christoph}, booktitle = {Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN2014)}, keywords = {e-learning myown mooc}, title = {Improving the Onboarding User Experience in MOOCs}, year = 2014 }
  Further Information
• 
  Staubitz, T., Renz, J., Willems, C., Jasper, J., Meinel, C.: Lightweight Ad Hoc Assessment of Practical Programming Skills at Scale.Proceedings of IEEE Global Engineering Education Conference (EDUCON2014). IEEE, Istanbul, Turkey (2014).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2014_Meinel_EDUCON, address = {Istanbul, Turkey}, author = {Staubitz, Thomas and Renz, Jan and Willems, Christian and Jasper, Johannes and Meinel, Christoph}, booktitle = {Proceedings of IEEE Global Engineering Education Conference (EDUCON2014)}, keywords = {its}, month = 4, publisher = {IEEE}, title = {Lightweight Ad Hoc Assessment of Practical Programming Skills at Scale}, year = 2014 }
  Further Information
• 
  Staubitz, T., Renz, J., Willems, C., Jasper, J., Meinel, C.: Lightweight Ad Hoc Assessment of Practical Programming Skills at Scale.Proceedings of IEEE Global Engineering Education Conference (EDUCON2014). IEEE, Istanbul, Turkey (2014).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2014_Meinel_EDUCON, address = {Istanbul, Turkey}, author = {Staubitz, Thomas and Renz, Jan and Willems, Christian and Jasper, Johannes and Meinel, Christoph}, booktitle = {Proceedings of IEEE Global Engineering Education Conference (EDUCON2014)}, keywords = {e-learning myown assessment autograder assignment}, month = 4, publisher = {IEEE}, title = {Lightweight Ad Hoc Assessment of Practical Programming Skills at Scale}, year = 2014 }
  Further Information
• 
  Staubitz, T., Renz, J., Willems, C., Meinel, C.: Supporting Social Interaction and Collaboration on an xMOOC Platform.Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN14). , Barcelona, Spain (2014).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2014_Staubitz_EDULEARN, address = {Barcelona, Spain}, author = {Staubitz, Thomas and Renz, Jan and Willems, Christian and Meinel, Christoph}, booktitle = {Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN14)}, keywords = {e-learning myown assessment mooc collaboration}, title = {Supporting Social Interaction and Collaboration on an xMOOC Platform}, year = 2014 }
  Further Information
• 
  Staubitz, T., Woinar, S., Renz, J., Meinel, C.: Towards Social Gamification - Implementing a Social Graph in an xMOOC Platform.Proc. 7th International Conference of Education, Research and Innovation. , Sevilla, Spain (2014).
  [ BibTeX ] [ Details ]
   
  @inproceedings{2014_Staubitz_iCeri, address = {Sevilla, Spain}, author = {Staubitz, Thomas and Woinar, Sebastian and Renz, Jan and Meinel, Christoph}, booktitle = {Proc. 7th International Conference of Education, Research and Innovation}, keywords = {e-learning gamification myown mooc}, title = {Towards Social Gamification - Implementing a Social Graph in an xMOOC Platform}, year = 2014 }
  Further Information
• 
  Willems, C., Fricke, N., Meyer, S., Meissner, R., Rollmann, K.-A., Voelcker, S., Woinar, S., Meinel, C.: Motivating the Masses – Gamified Massive Open Online Courses on openHPI.Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN14). , Barcelona, Spain (2014).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2014_Willems_EDULEARN, address = {Barcelona, Spain}, author = {Willems, Christian and Fricke, Nicolas and Meyer, Sebastian and Meissner, Richard and Rollmann, Kai-Adrian and Voelcker, Simon and Woinar, Sebastian and Meinel, Christoph}, booktitle = {Proc. 6th International Conference on Education and New Learning Technologies (EDULEARN14)}, keywords = {its}, title = {Motivating the Masses – Gamified Massive Open Online Courses on openHPI}, year = 2014 }
  Further Information
• 
  Chujfi, S., Meinel, C.: Modeling cognitive style patterns to explore individuals’ capabilities for processing knowledge in virtual settings.Proceedings of the 2014 European Conference on Cognitive Ergonomics (ECCE 2014). ACM (2014).
  [ Abstract ] [ BibTeX ] [ Details ]
   
  Organizations continue building virtual working teams (Teleworkers) to become more dynamic as part of their strategic innovation with great benefits to individuals, business, and society. Geographically distributed organizations however have the big challenge of managing people’s knowledge not only to keep operations running but also to promote innovation within the organization creating new knowledge. This study analyses how knowledge-based organizations working with decentralized staff may need considering cognitive styles (CS) and learning styles (LS) of individuals participating on their programs to effectively manage knowledge in virtual settings. The study aims at modeling patterns to identify abilities of individuals according to their cognitive and learning styles attempting to match affinities to work remotely and take part in virtual team work, and also to correctly determine the use of appropriate hypermedia tools to help overcoming lower performance and effectiveness, which may occur due to the lack face-to-face communication normally found in typical offices.
  @inproceedings{2014_CHUJFI_ECCE, abstract = {Organizations continue building virtual working teams (Teleworkers) to become more dynamic as part of their strategic innovation with great benefits to individuals, business, and society. Geographically distributed organizations however have the big challenge of managing people’s knowledge not only to keep operations running but also to promote innovation within the organization creating new knowledge. This study analyses how knowledge-based organizations working with decentralized staff may need considering cognitive styles (CS) and learning styles (LS) of individuals participating on their programs to effectively manage knowledge in virtual settings. The study aims at modeling patterns to identify abilities of individuals according to their cognitive and learning styles attempting to match affinities to work remotely and take part in virtual team work, and also to correctly determine the use of appropriate hypermedia tools to help overcoming lower performance and effectiveness, which may occur due to the lack face-to-face communication normally found in typical offices.}, author = {Chujfi, Salim and Meinel, Christoph}, booktitle = {Proceedings of the 2014 European Conference on Cognitive Ergonomics (ECCE 2014)}, keywords = {its}, month = 9, publisher = {ACM}, title = {Modeling cognitive style patterns to explore individuals’ capabilities for processing knowledge in virtual settings}, year = 2014 }
  Further Information

  URNhttp://dx.doi.org/10.1145/2637248.2637263

  AbstractOrganizations continue building virtual working teams (Teleworkers) to become more dynamic as part of their strategic innovation with great benefits to individuals, business, and society. Geographically distributed organizations however have the big challenge of managing people’s knowledge not only to keep operations running but also to promote innovation within the organization creating new knowledge. This study analyses how knowledge-based organizations working with decentralized staff may need considering cognitive styles (CS) and learning styles (LS) of individuals participating on their programs to effectively manage knowledge in virtual settings. The study aims at modeling patterns to identify abilities of individuals according to their cognitive and learning styles attempting to match affinities to work remotely and take part in virtual team work, and also to correctly determine the use of appropriate hypermedia tools to help overcoming lower performance and effectiveness, which may occur due to the lack face-to-face communication normally found in typical offices.

2013 [ to top ]

• 
  Yang, H., Grünewald, F., Bauer, M., Meinel, C.: Lecture Video Browsing Using Multimodal Information Resources.12th International Conference on Web-based Learning (ICWL). pp. 204-213. Springer Berlin Heidelberg (2013).
  [ BibTeX ] [ Details ]
   
  @inproceedings{Haojin2013a, author = {Yang, Haojin and Grünewald, Franka and Bauer, Matthias and Meinel, Christoph}, booktitle = {12th International Conference on Web-based Learning (ICWL)}, keywords = {mma its}, month = 10, number = 8167, pages = {204-213}, publisher = {Springer Berlin Heidelberg}, title = {Lecture Video Browsing Using Multimodal Information Resources}, volume = {Lecture Notes in Computer Science}, year = 2013 }
  Further Information

  URNhttp://dx.doi.org/10.1007/978-3-642-41175-5_21
• 
  Totschnig, M., Willems, C., Meinel, C.: openHPI: Evolution of a MOOC Platform from LMS to SOA.Proceedings of the 5th International Conference on Computer Supported Education (CSEDU2013). pp. 49-54. SciTePress, Aachen, Germany (2013).
  [ BibTeX ] [ Download ] [ Details ]
   
  @inproceedings{2013_Totschnig_CSEDU, address = {Aachen, Germany}, author = {Totschnig, Michael and Willems, Christian and Meinel, Christoph}, booktitle = {Proceedings of the 5th International Conference on Computer Supported Education (CSEDU2013)}, keywords = {Service_Oriented_Architecture its Massive_Open_Online_Course Learning_Management_System}, month = 5, pages = {49-54}, publisher = {SciTePress}, title = {openHPI: Evolution of a MOOC Platform from LMS to SOA}, year = 2013 }
  Further Information

  URNhttp://dx.doi.org/10.5220/0004416905930598
• 
  Grünewald, F., Meinel, C., Totschnig, M., Willems, C.: Designing MOOCs for the Support of Multiple Learning Styles.Proceedings of the 8th European Conference on Technology Enhanced Learning (EC-TEL 2013). Springer, Paphos, Cyprus (2013).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  "Internetworking with TCP/IP" is a Massive Open Online Course, held in German at openHPI end of 2012, that attracted a large audience that has not been in contact with higher education before. The course followed the xMOOC model based on a well-defined sequence of learning content, mainly video lectures and interactive self-tests, and with heavy reliance on social collaboration features. From 2726 active participants, 38% have participated in a survey at the end of the course. This paper presents an analysis of the survey responses with respect to the following questions: 1) How can a MOOC accommodate different learning styles and 2) What recommendations for the design and organization of a MOOC can be concluded from the responses? We finally give an outlook on challenges for the further development of openHPI. Those challenges are based on didactical and technical affordances for a better support of the different learning styles. We propose an evolution of the xMOOC, that bridges the gap to the cMOOC model by developing tools that allow users to create diverging paths through the learning material, involve the user personally in the problem domain with (group) hands-on exercises and reward user contributions by means of gamification.
  @inproceedings{2013_Gruenewald_ECTEL, abstract = {"Internetworking with TCP/IP" is a Massive Open Online Course, held in German at openHPI end of 2012, that attracted a large audience that has not been in contact with higher education before. The course followed the xMOOC model based on a well-defined sequence of learning content, mainly video lectures and interactive self-tests, and with heavy reliance on social collaboration features. From 2726 active participants, 38% have participated in a survey at the end of the course. This paper presents an analysis of the survey responses with respect to the following questions: 1) How can a MOOC accommodate different learning styles and 2) What recommendations for the design and organization of a MOOC can be concluded from the responses? We finally give an outlook on challenges for the further development of openHPI. Those challenges are based on didactical and technical affordances for a better support of the different learning styles. We propose an evolution of the xMOOC, that bridges the gap to the cMOOC model by developing tools that allow users to create diverging paths through the learning material, involve the user personally in the problem domain with (group) hands-on exercises and reward user contributions by means of gamification.}, address = {Paphos, Cyprus}, author = {Grünewald, Franka and Meinel, Christoph and Totschnig, Michael and Willems, Christian}, booktitle = {Proceedings of the 8th European Conference on Technology Enhanced Learning (EC-TEL 2013)}, keywords = {gamification culture_of_participation massive_open_online_courses learning_styles its active_learning}, publisher = {Springer}, title = {Designing MOOCs for the Support of Multiple Learning Styles}, year = 2013 }
  Further Information

  Abstract"Internetworking with TCP/IP" is a Massive Open Online Course, held in German at openHPI end of 2012, that attracted a large audience that has not been in contact with higher education before. The course followed the xMOOC model based on a well-defined sequence of learning content, mainly video lectures and interactive self-tests, and with heavy reliance on social collaboration features. From 2726 active participants, 38% have participated in a survey at the end of the course. This paper presents an analysis of the survey responses with respect to the following questions: 1) How can a MOOC accommodate different learning styles and 2) What recommendations for the design and organization of a MOOC can be concluded from the responses? We finally give an outlook on challenges for the further development of openHPI. Those challenges are based on didactical and technical affordances for a better support of the different learning styles. We propose an evolution of the xMOOC, that bridges the gap to the cMOOC model by developing tools that allow users to create diverging paths through the learning material, involve the user personally in the problem domain with (group) hands-on exercises and reward user contributions by means of gamification.
• 
  Grünewald, F., Mazandarani, E., Meinel, C., Teusner, R., Totschnig, M., Willems, C.: openHPI - a Case-Study on the Emergence of two Learning Communities.Proceedings of 2013 IEEE Global Engineering Education Conference (EDUCON). IEEE Press (2013).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Recently a new format of online education has emerged that combines video lectures, interactive quizzes and social learning into an event that aspires to attract a massive number of participants. This format, referred to as Massive Open Online Course (MOOC), has garnered considerable public attention, and has been invested with great hopes (and fears) of transforming higher education by opening up the walls of closed institutions to a world-wide audience. In this paper, we present two MOOCs that were hosted at the same platform, and have implemented the same learning design. Due to their difference in language, topic domain and difficulty, the communities that they brought into existence were very different. We start by describing the MOOC format in more detail, and the distinguishing features of openHPI. We then discuss the literature on communities of practice and cultures of participation. After some statistical data about the first openHPI course, we present our qualitative observations about both courses, and conclude by giving an outlook on an ongoing comparative analysis of the two courses.
  @inproceedings{2013_Gruenewald_EDUCON, abstract = {Recently a new format of online education has emerged that combines video lectures, interactive quizzes and social learning into an event that aspires to attract a massive number of participants. This format, referred to as Massive Open Online Course (MOOC), has garnered considerable public attention, and has been invested with great hopes (and fears) of transforming higher education by opening up the walls of closed institutions to a world-wide audience. In this paper, we present two MOOCs that were hosted at the same platform, and have implemented the same learning design. Due to their difference in language, topic domain and difficulty, the communities that they brought into existence were very different. We start by describing the MOOC format in more detail, and the distinguishing features of openHPI. We then discuss the literature on communities of practice and cultures of participation. After some statistical data about the first openHPI course, we present our qualitative observations about both courses, and conclude by giving an outlook on an ongoing comparative analysis of the two courses.}, author = {Grünewald, Franka and Mazandarani, Elnaz and Meinel, Christoph and Teusner, Ralf and Totschnig, Michael and Willems, Christian}, booktitle = {Proceedings of 2013 IEEE Global Engineering Education Conference (EDUCON)}, keywords = {culture_of_participation community_of_practice learner_community online_course its}, month = 3, publisher = {IEEE Press}, title = {openHPI - a Case-Study on the Emergence of two Learning Communities}, year = 2013 }
  Further Information

  AbstractRecently a new format of online education has emerged that combines video lectures, interactive quizzes and social learning into an event that aspires to attract a massive number of participants. This format, referred to as Massive Open Online Course (MOOC), has garnered considerable public attention, and has been invested with great hopes (and fears) of transforming higher education by opening up the walls of closed institutions to a world-wide audience. In this paper, we present two MOOCs that were hosted at the same platform, and have implemented the same learning design. Due to their difference in language, topic domain and difficulty, the communities that they brought into existence were very different. We start by describing the MOOC format in more detail, and the distinguishing features of openHPI. We then discuss the literature on communities of practice and cultures of participation. After some statistical data about the first openHPI course, we present our qualitative observations about both courses, and conclude by giving an outlook on an ongoing comparative analysis of the two courses.
• 
  Willems, C., Jasper, J., Meinel, C.: Introducing Hands-On Experience to a Massive Open Online Course on openHPI.Proceedings of IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE 2013). IEEE Press, Kuta, Bali, Indonesia (2013).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Massive Open Online Courses (MOOCs) have become the trending topic in e-learning. Many institutions started to offer courses, either on commercial platforms like Coursera and Udacity or using own platform software. While many courses share the concept of lecture videos combined with automatically assessable assignments, and discussion forums, only few courses provide hands-on experience. The design of practical exercises poses a great challenge to a teaching team and gets even more challenging if these assignments should be gradable. In the course Internetworking with TCP/IP on the German MOOC platform openHPI, the teaching team conducted an experiment with three practical tasks that were implemented as assessed bonus exercises. The exercise design was limited by the constraint that the platform software could not be adapted for these exercises and that there could be no central training environment to perform these assignments. This paper describes the experiment setup, the challenges and pitfalls and evaluates the result based on statistical data and a survey taken by the course participants.
  @inproceedings{2013_Willems_TALE, abstract = {Massive Open Online Courses (MOOCs) have become the trending topic in e-learning. Many institutions started to offer courses, either on commercial platforms like Coursera and Udacity or using own platform software. While many courses share the concept of lecture videos combined with automatically assessable assignments, and discussion forums, only few courses provide hands-on experience. The design of practical exercises poses a great challenge to a teaching team and gets even more challenging if these assignments should be gradable. In the course Internetworking with TCP/IP on the German MOOC platform openHPI, the teaching team conducted an experiment with three practical tasks that were implemented as assessed bonus exercises. The exercise design was limited by the constraint that the platform software could not be adapted for these exercises and that there could be no central training environment to perform these assignments. This paper describes the experiment setup, the challenges and pitfalls and evaluates the result based on statistical data and a survey taken by the course participants.}, address = {Kuta, Bali, Indonesia}, author = {Willems, Christian and Jasper, Johannes and Meinel, Christoph}, booktitle = {Proceedings of IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE 2013)}, keywords = {MOOC its TCP/IP e-mail DNS online_assessment hands-on_experience}, publisher = {IEEE Press}, title = {Introducing Hands-On Experience to a Massive Open Online Course on openHPI}, year = 2013 }
  Further Information

  AbstractMassive Open Online Courses (MOOCs) have become the trending topic in e-learning. Many institutions started to offer courses, either on commercial platforms like Coursera and Udacity or using own platform software. While many courses share the concept of lecture videos combined with automatically assessable assignments, and discussion forums, only few courses provide hands-on experience. The design of practical exercises poses a great challenge to a teaching team and gets even more challenging if these assignments should be gradable. In the course Internetworking with TCP/IP on the German MOOC platform openHPI, the teaching team conducted an experiment with three practical tasks that were implemented as assessed bonus exercises. The exercise design was limited by the constraint that the platform software could not be adapted for these exercises and that there could be no central training environment to perform these assignments. This paper describes the experiment setup, the challenges and pitfalls and evaluates the result based on statistical data and a survey taken by the course participants.
• 
  Grünewald, F., Mazandarani, E., Meinel, C., Teusner, R., Totschnig, M., Willems, C.: openHPI: Soziales und Praktisches Lernen im Kontext eines MOOC.Proceedings of DeLFI 2013 - 11. e-Learning Fachtagung Informatik. Gesellschaft für Informatik, Bremen, Germany (2013).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  Mit dem Format des "Masssive Open Online Courses" (MOOC) hat sich in den letzten Jahren eine intensiv diskutierte neue Variante des E-Learnings herausgebildet. Zentrale Voraussetzung eines MOOCs ist die Öffnung eines Kurses aus den Schranken einer Bildungsinstitution heraus hin zur kostenlosen und uneingeschränkten Teilnahme. Über die für ein MOOC angemessenen pädagogischen Methoden wird zur Zeit zwar heftig diskutiert, Konsens besteht allerdings darüber, dass die wichtigste Herausforderung darin besteht, Lernprozesse durch soziale Interaktionen zwischen potentiell Tausenden von Teilnehmern zu stimulieren. In unserem Beitrag stellen wir openHPI vor, eine Plattform für MOOCs im Bereich der Informationstechnologie. Anhand von Kolbs Theorie der Lernstile analysieren wir eine Umfrage unter den Teilnehmern des ersten deutschsprachigen Kurses "Internetworking", und zeigen, dass ein vorrangig am Format der Vorlesung orientiertes MOOC zwar eher dem an Begriffsbildung und Beobachtung orientierten assimilierenden Lernstil entgegenkommt, dass es uns durch die Einführung von praktischen Zusatzaufgaben jedoch auch gelang, das aktive Experimentieren der Teilnehmer mit der Materie zu fördern. Wir beschreiben auch, in welchem Ausmaß die Teilnehmer, Funktionen der Plattform, die das soziale Lernen ermöglichen, nutzen, und welche zusätzlichen Funktionen nachgefragt werden. Für die Neuauflage dieses Kurses, sowie des ersten, englischsprachigen Kurses zum Thema "In-Memory Databases" ıst eine intensivere Integration praktischer Aufgaben in das Kurs-Design geplant. Die didaktischen und technischen Herausforderungen, die sich daraus ergeben, werden im zweiten Teil des Textes analysiert.
  @inproceedings{2013_Gruenewald_DELFI, abstract = {Mit dem Format des "Masssive Open Online Courses" (MOOC) hat sich in den letzten Jahren eine intensiv diskutierte neue Variante des E-Learnings herausgebildet. Zentrale Voraussetzung eines MOOCs ist die Öffnung eines Kurses aus den Schranken einer Bildungsinstitution heraus hin zur kostenlosen und uneingeschränkten Teilnahme. Über die für ein MOOC angemessenen pädagogischen Methoden wird zur Zeit zwar heftig diskutiert, Konsens besteht allerdings darüber, dass die wichtigste Herausforderung darin besteht, Lernprozesse durch soziale Interaktionen zwischen potentiell Tausenden von Teilnehmern zu stimulieren. In unserem Beitrag stellen wir openHPI vor, eine Plattform für MOOCs im Bereich der Informationstechnologie. Anhand von Kolbs Theorie der Lernstile analysieren wir eine Umfrage unter den Teilnehmern des ersten deutschsprachigen Kurses "Internetworking", und zeigen, dass ein vorrangig am Format der Vorlesung orientiertes MOOC zwar eher dem an Begriffsbildung und Beobachtung orientierten assimilierenden Lernstil entgegenkommt, dass es uns durch die Einführung von praktischen Zusatzaufgaben jedoch auch gelang, das aktive Experimentieren der Teilnehmer mit der Materie zu fördern. Wir beschreiben auch, in welchem Ausmaß die Teilnehmer, Funktionen der Plattform, die das soziale Lernen ermöglichen, nutzen, und welche zusätzlichen Funktionen nachgefragt werden. Für die Neuauflage dieses Kurses, sowie des ersten, englischsprachigen Kurses zum Thema "In-Memory Databases" ıst eine intensivere Integration praktischer Aufgaben in das Kurs-Design geplant. Die didaktischen und technischen Herausforderungen, die sich daraus ergeben, werden im zweiten Teil des Textes analysiert.}, address = {Bremen, Germany}, author = {Grünewald, Franka and Mazandarani, Elnaz and Meinel, Christoph and Teusner, Ralf and Totschnig, Michael and Willems, Christian}, booktitle = {Proceedings of DeLFI 2013 - 11. e-Learning Fachtagung Informatik}, keywords = {MOOC Lernstile its Theory_of_Practise Cultures_of_Participation}, publisher = {Gesellschaft für Informatik}, title = {openHPI: Soziales und Praktisches Lernen im Kontext eines MOOC}, year = 2013 }
  Further Information

  AbstractMit dem Format des "Masssive Open Online Courses" (MOOC) hat sich in den letzten Jahren eine intensiv diskutierte neue Variante des E-Learnings herausgebildet. Zentrale Voraussetzung eines MOOCs ist die Öffnung eines Kurses aus den Schranken einer Bildungsinstitution heraus hin zur kostenlosen und uneingeschränkten Teilnahme. Über die für ein MOOC angemessenen pädagogischen Methoden wird zur Zeit zwar heftig diskutiert, Konsens besteht allerdings darüber, dass die wichtigste Herausforderung darin besteht, Lernprozesse durch soziale Interaktionen zwischen potentiell Tausenden von Teilnehmern zu stimulieren. In unserem Beitrag stellen wir openHPI vor, eine Plattform für MOOCs im Bereich der Informationstechnologie. Anhand von Kolbs Theorie der Lernstile analysieren wir eine Umfrage unter den Teilnehmern des ersten deutschsprachigen Kurses "Internetworking", und zeigen, dass ein vorrangig am Format der Vorlesung orientiertes MOOC zwar eher dem an Begriffsbildung und Beobachtung orientierten assimilierenden Lernstil entgegenkommt, dass es uns durch die Einführung von praktischen Zusatzaufgaben jedoch auch gelang, das aktive Experimentieren der Teilnehmer mit der Materie zu fördern. Wir beschreiben auch, in welchem Ausmaß die Teilnehmer, Funktionen der Plattform, die das soziale Lernen ermöglichen, nutzen, und welche zusätzlichen Funktionen nachgefragt werden. Für die Neuauflage dieses Kurses, sowie des ersten, englischsprachigen Kurses zum Thema "In-Memory Databases" ıst eine intensivere Integration praktischer Aufgaben in das Kurs-Design geplant. Die didaktischen und technischen Herausforderungen, die sich daraus ergeben, werden im zweiten Teil des Textes analysiert.
• 
  Grünewald, F., Yang, H., Mazandarani, E., Bauer, M., Meinel, C.: Next Generation Tele-Teaching: Latest Recording Technology, User Engagement and Automatic Metadata Retrieval.Human Factors in Computing and Informatics. pp. 391-408 (2013).
  [ BibTeX ] [ Details ]
   
  @inproceedings{Franka2013a, author = {Grünewald, Franka and Yang, Haojin and Mazandarani, Elnaz and Bauer, Matthias and Meinel, Christoph}, booktitle = {Human Factors in Computing and Informatics}, keywords = {its}, month = 7, number = 7946, pages = {391-408}, title = {Next Generation Tele-Teaching: Latest Recording Technology, User Engagement and Automatic Metadata Retrieval}, volume = {Lecture Notes in Computer Science}, year = 2013 }
  Further Information

  URNhttp://dx.doi.org/10.1007/978-3-642-39062-3_25
• 
  Che, X., Yang, H., Meinel, C.: Lecture Video Segmentation by Automatically Analyzing the Synchronized Slides.Proceedings of the 21st ACM international conference on Multimedia. pp. 345-348. , Barcelona, Spain (2013).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In this paper we propose a solution which segments lecture video by analyzing its supplementary synchronized slides. The slides content derives automatically from OCR (Optical Character Recognition) process with an approximate accuracy of 90%. Then we partition the slides into different subtopics by examining their logical relevance. Since the slides are synchronized with the video stream, the subtopics of the slides indicate exactly the segments of the video. Our evaluation reveals that the average length of segments for each lecture is ranged from 5 to 15 minutes, and 45% segments achieved from test datasets are logically reasonable.
  @inproceedings{2013_Che_MM, abstract = {In this paper we propose a solution which segments lecture video by analyzing its supplementary synchronized slides. The slides content derives automatically from OCR (Optical Character Recognition) process with an approximate accuracy of 90%. Then we partition the slides into different subtopics by examining their logical relevance. Since the slides are synchronized with the video stream, the subtopics of the slides indicate exactly the segments of the video. Our evaluation reveals that the average length of segments for each lecture is ranged from 5 to 15 minutes, and 45% segments achieved from test datasets are logically reasonable.}, address = {Barcelona, Spain}, author = {Che, Xiaoyin and Yang, Haojin and Meinel, Christoph}, booktitle = {Proceedings of the 21st ACM international conference on Multimedia}, keywords = {Slides_Content_Analysis its OCR Video_Segmentation}, month = 10, pages = {345-348}, title = {Lecture Video Segmentation by Automatically Analyzing the Synchronized Slides}, year = 2013 }
  Further Information

  URNhttp://dx.doi.org/10.1145/2502081.2508115

  AbstractIn this paper we propose a solution which segments lecture video by analyzing its supplementary synchronized slides. The slides content derives automatically from OCR (Optical Character Recognition) process with an approximate accuracy of 90%. Then we partition the slides into different subtopics by examining their logical relevance. Since the slides are synchronized with the video stream, the subtopics of the slides indicate exactly the segments of the video. Our evaluation reveals that the average length of segments for each lecture is ranged from 5 to 15 minutes, and 45% segments achieved from test datasets are logically reasonable.
• 
  Che, X., Yang, H., Meinel, C.: Tree-structure Outline Generation for Lecture Videos with Synchronized Slides.Proceedings of the Second International Conference on e-Learning and e-Technologies in Education (ICEEE2013). pp. 87-92. , Lodz, Poland (2013).
  [ Abstract ] [ BibTeX ] [ Download ] [ Details ]
   
  In this paper we propose a solution to generate tree-structure outline for lecture videos by analyzing their synchronized slides, by which detailed lecture overview can be automatically provided to E-learning portal users. Starting with OCR (Optical Character Recognition) result, we reconstruct the content of each slide. After that, we explore logical relations between slides, in order to make them hierarchical. And all potential redundant content will also be removed. Our evaluation shows that, based on our test dataset, the final outline achieved retains about 1/4 of the original texts from all slides and is organized well in an up-to-6-level tree structure. Furthermore, the average accuracy of all slide titles, which are undoubtedly the most important information, reaches 86%.
  @inproceedings{2013_Che_ICEEE, abstract = {In this paper we propose a solution to generate tree-structure outline for lecture videos by analyzing their synchronized slides, by which detailed lecture overview can be automatically provided to E-learning portal users. Starting with OCR (Optical Character Recognition) result, we reconstruct the content of each slide. After that, we explore logical relations between slides, in order to make them hierarchical. And all potential redundant content will also be removed. Our evaluation shows that, based on our test dataset, the final outline achieved retains about 1/4 of the original texts from all slides and is organized well in an up-to-6-level tree structure. Furthermore, the average accuracy of all slide titles, which are undoubtedly the most important information, reaches 86%.}, address = {Lodz, Poland}, author = {Che, Xiaoyin and Yang, Haojin and Meinel, Christoph}, booktitle = {Proceedings of the Second International Conference on e-Learning and e-Technologies in Education (ICEEE2013)}, keywords = {Slides_Analysis Tree-Structure_Outline its OCR}, month = 9, pages = {87-92}, title = {Tree-structure Outline Generation for Lecture Videos with Synchronized Slides}, year = 2013 }
  Further Information

  URNhttp://dx.doi.org/10.1109/ICeLeTE.2013.6644353

  AbstractIn this paper we propose a solution to generate tree-structure outline for lecture videos by analyzing their synchronized slides, by which detailed lecture overview can be automatically provided to E-learning portal users. Starting with OCR (Optical Character Recognition) result, we reconstruct the content of each slide. After that, we explore logical relations between slides, in order to make them hierarchical. And all potential redundant content will also be removed. Our evaluation shows that, based on our test dataset, the final outline achieved retains about 1/4 of the original texts from all slides and is organized well in an up-to-6-level tree structure. Furthermore, the average accuracy of all slide titles, which are undoubtedly the most important information, reaches 86%.
• 
  Yang, H., Grünewald, F., Bauer, M., Meinel, C.: Lecture Video Browsing Using Multimodal Information Resources.12th International Conference on Web-based Learning (ICWL). pp. 204-213. Springer Berlin Heidelberg (2013).
  [ BibTeX ] [ Details ]