AbstractOnline learning environments, such as Massive Open Online Courses (MOOCs), often rely on videos as a major component to convey knowledge. However, these videos exclude potential participants who do not understand the lecturer's language, regardless of whether that is due to language unfamiliarity or aural handicaps. Subtitles and/or interactive transcripts solve this issue, ease navigation based on the content, and enable indexing and retrieval by search engines. Although there are several automated speech-to-text converters and translation tools, their quality varies and the process of integrating them can be quite tedious. Thus, in practice, many videos on MOOC platforms only receive subtitles after the course is already finished (if at all) due to a lack of resources. This work describes an approach to tackle this issue by providing a dedicated tool, which is closing this gap between MOOC platforms and transcription and translation tools and offering a simple workflow that can easily be handled by users with a less technical background. The proposed method is designed and evaluated by qualitative interviews with three major MOOC providers.
CodeOcean and CodeHarbor: Auto-Grader and Code Repository. Serth, Sebastian; Staubitz, Thomas; Teusner, Ralf; Meinel, Christoph C. Shaffer, P. Brusilovsky, K. Koedinger, S. Edwards (reds.) (2021). 5.
HerausgeberShaffer, 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.
Have Your Tickets Ready! Impede Free Riding in Large Scale Team Assignments. Staubitz, Thomas; Traifeh, Hanadi; Chujfi, Salim; Meinel, Christoph in L@S ’20 (2020). 349–352.
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.
A Systematic Quantitative and Qualitative Analysis of Participants’ Opinions on Peer Assessment in Surveys and Course Forum Discussions of MOOCs. Staubitz, Thomas; Meinel, Christoph (2020). 962–971.
MOOCs in Secondary Education - Experiments and Observations from German Classrooms. Staubitz, Thomas; Teusner, Ralf; Meinel, Christoph (2019). 173–182.
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.
Graded Team Assignments in MOOCs: Effects of Team Composition and Further Factors on Team Dropout Rates and Performance. Staubitz, Thomas; Meinel, Christoph in L@S ’19 (2019). 5:1–5:10.
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.
Skill Confidence Ratings in a MOOC: Examining the Link Between Skill Confidence and Learner Development. von Schmieden, Karen; Staubitz, Thomas; Mayer, Lena; Meinel, Christoph (2019). (Vol. 1) 533–40.
Skill Confidence Ratings in a MOOC: Examining the Link between Skill Confidence and Learner Development. von Schmieden, Karen; Staubitz, Thomas; Mayer, Lena; Meinel, Christoph (2019).
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.
Corporate MOOC Trends Friedl, Christian; Staubitz, Thomas (D. Jansen; L. Konings, reds.) (2018). 35–38. EADTU.
AbstractThis work presents insights about the long-term effects and retention rates of knowledge acquired within MOOCs. In 2015 and 2017, we conducted two introductory MOOCs on object-oriented programming in Java with each over 10,000 registered participants. In this paper, we analyze course scores, quiz results and self-stated skill levels of our participants. The aim of our analysis is to uncover factors influencing the retention of acquired knowledge, such as time passed or knowledge application, in order to improve long-term success. While we know that some participants learned the programming basics within our course, we lack information on whether this knowledge was applied and fortified after the course's end. To fill this knowledge gap, we conducted a survey in 2018 among all participants of our 2015 and 2017 programming MOOCs. The first part of the survey elicits responses on whether and how MOOC knowledge was applied and gives participants opportunity to voice individual feedback. The second part of the survey contains several questions of increasing difficulty and complexity regarding course content in order to learn about the consolidation of the acquired knowledge. We distinguish three programming knowledge areas in the survey: First, understanding of concepts, such as loops and boolean algebra. Second, syntax knowledge, such as specific keywords. Third, practical skills including debugging and coding. We further analyzed the long-term effects separately per participant skill group. While answer rates were low, the collected data shows a decrease of knowledge over time, relatively unaffected by skill level. Application of the acquired knowledge improves the memory retention rates of MOOC participants across all skill levels.
Team based assignments in MOOCs: results and observations. Staubitz, Thomas; Meinel, Christoph (2018). 47:1–47:4.
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.
Effects of Automated Interventions in Programming Assignments: Evidence from a Field Experiment. Teusner, Ralf; Hille, Thomas; Staubitz, Thomas (2018).
AbstractA typical problem in MOOCs is the missing opportunity for course conductors to individually support students in overcoming their problems and misconceptions. This paper presents the results of automatically intervening on struggling students during programming exercises and offering peer feedback and tailored bonus exercises. To improve learning success, we do not want to abolish instructionally desired trial and error but reduce extensive struggle and demotivation. Therefore, we developed adaptive automatic just-in-time interventions to encourage students to ask for help if they require considerably more than average working time to solve an exercise. Additionally, we offered students bonus exercises tailored for their individual weaknesses. The approach was evaluated within a live course with over 5,000 active students via a survey and metrics gathered alongside. Results show that we can increase the call outs for help by up to 66% and lower the dwelling time until issuing action. Learnings from the experiments can further be used to pinpoint course material to be improved and tailor content to be audience specific.
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.
Automatisierte Qualitätssicherung in MOOCs durch Learning Analytics. Renz, Jan; Rohloff, Tobias; Meinel, Christoph C. Ullrich, M. Wessner (reds.) (2017).
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.
Collaboration and Teamwork on a MOOC Platform: A Toolset. Staubitz, Thomas; Meinel, Christoph in L@S ’17 (2017). 165–168.
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.
Towards a Repository for Open Auto-Gradable Programming Exercises. Staubitz, Thomas; Teusner, Ralf; Meinel, Christoph (2017).
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.
Collaboration and Teamwork on a MOOC Platform - A Toolset. Staubitz, Thomas; Meinel, Christoph (2017).
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 platform’s OPS-team, which prepares the courses in accordance with the requirements of the teaching teams. The evaluation is based on the analysis of data, which has been collected in five courses that have been conducted on one of our platforms during 2015 and 2016 and interviews with the platform’s OPS-team.
Video Conferencing as a Peephole to MOOC Participants. Teusner, Ralf; Wittstruck, Nicholas; Staubitz, Thomas (2017).
AbstractDistance education gained considerable attention with the rise of Massive Open Online Courses (MOOCs). Given the significant role collaboration plays in practical computer science education on campus, it becomes evident that nowadays online course platforms mostly lack the necessary collaborative capabilities. We present a solution to support collaborative programming through video conferencing for practical exercises employed in MOOC contexts. Two user surveys showed that albeit users value the possibilities, privacy concerns remain. We therefore propose to additionally use the technology to face another challenge: MOOCs usually are conceptualized and produced to a large extent before the actual course runtime. Reaction on current events within the course is possible but requires insights on students’ problems. Course conductors can use the tutoring mode in our WebIDE to understand struggling students and potentially uncover topics that lack additional background material or need additional training exercises.
Collaboration and Teamwork on a MOOC Platform - A Toolset. Staubitz, Thomas; Meinel, Christoph (2017).
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 platform’s OPS-team, which prepares the courses in accordance with the requirements of the teaching teams. The evaluation is based on the analysis of data, which has been collected in five courses that have been conducted on one of our platforms during 2015 and 2016 and interviews with the platform’s OPS-team.
Can MOOCs Support Secondary Education in Computer Science?. Grella, Catrina Tamara; Staubitz, Thomas; Teusner, Ralf; Meinel, Christoph M. E. Auer, D. Guralnick, J. Uhomoibhi (reds.) (2017). 478–493.
HerausgeberAuer, 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.
Using A/B Testing in MOOC Environments. Renz, Jan; Hoffmann, Daniel; Staubitz, Thomas; Meinel, Christoph (2016).
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.
First Steps in Automated Proctoring. Staubitz, Thomas; Teusner, Ralf; Renz, Jan; Meinel, Christoph (2016).
Automatisierte Online-Aufsicht im Kontext der Wertigkeit von Zertifikaten einer MOOC Plattform. Staubitz, Thomas; Teusner, Ralf; Renz, Jan; Meinel, Christoph (2016). 125–136.
AbstractDie Glaubwürdigkeit und Überprüfbarkeit der Zertifikate ist ein wesentlicher Bestandteil von jeglicher Form von zertifiziertem Training. Diese Aussage gilt natürlich auch für MOOCs. In diesem Kontext kommt allerdings erschwerend hinzu, dass eine individuelle, persönliche Beaufsichtigung der Prüfungen tausender TeilnehmerInnen offline nur schwer zu realisieren ist. Es wird daher eine Technik benötigt, diese Beaufsichtigung online durchzuführen, um die Vertrauenswürdigkeit oder Wertigkeit dieser Zertifikate zu erhöhen. In dieser Studie vergleichen wir verschiedene Spielarten der Online-Aufsicht. Wir stellen die Ergebnisse einiger Umfragen unter unseren TeilnehmerInnen, die sich mit deren Sicht bezüglich der Wertigkeit der Zertifikate befassen, vor und bewerten die Aussagen in unserem Kontext. Schließlich stellen wir ein Experiment vor, das wir mit einer neuen Variante der Online-Aufsicht durchgeführt haben. Anstatt sich auf menschliche Augen zu verlassen, wird ein automatisierter Abgleich des Gesichts vor der Kamera mit einem hinterlegten Bild durchgeführt, um zu überprüfen ob die angemeldete TeilnehmerIn auch die ist, die die Prüfung ablegt.
Enabling Schema Agnostic Learning Analytics in a Service-Oriented MOOC Platform. Renz, Jan; Navarro-Suarez, Gerardo; Sathi, Rowshan; Staubitz, Thomas; Meinel, Christoph (2016).
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.
CodeOcean - A Versatile Platform for Practical Programming Excercises in Online Environments. Staubitz, Thomas; Klement, Hauke; Teusner, Ralf; Renz, Jan; Meinel, Christoph (2016).
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.
Improving Collaborative Learning With Video Lectures. Bauer, Matthias; Malchow, Martin; Staubitz, Thomas; Meinel, Christoph (2016). 5511–5517.
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.
CodeOcean - A Versatile Platform for Practical Programming Excercises in Online Environments. Staubitz, Thomas; Klement, Hauke; Teusner, Ralf; Renz, Jan; Meinel, Christoph (2016).
Cellular Automata as Basis for Programming Exercises in a MOOC on Testdriven Development. Staubitz, Thomas; Teusner, Ralf; Prakash, Nishanth; Meinel, Christoph (2016).
AbstractProgramming tasks are an important part of teaching computer programming as they foster students to develop essential programming skills and techniques through practice. The design of educational problems plays a crucial role in the extent to which the experiential knowledge is imparted to the learner both in terms of quality and quantity. Badly designed tasks have been known to put-off students from practicing programming. Hence, there is a need for carefully designed problems. Cellular Automata programming lends itself as a very suitable candidate among problems designed for programming practice. In this paper we describe how various types of problems can be designed using concepts from Cellular Automata and discuss the features which make them good practice problems with regard to instructional pedagogy. We also present a case study on a Cellular Automata programming exercise used in a MOOC on Test Driven Development using JUnit, and discuss the automated evaluation of code submissions and the feedback about the reception of this exercise by participants in this course.
Automatisierte Online-Aufsicht im Kontext der Wertigkeit von Zertifikaten einer MOOC Plattform. Staubitz, Thomas; Teusner, Ralf; Renz, Jan; Meinel, Christoph (2016). 125–136.
AbstractDie Glaubwürdigkeit und Überprüfbarkeit der Zertifikate ist ein wesentlicher Bestandteil von jeglicher Form von zertifiziertem Training. Diese Aussage gilt natürlich auch für MOOCs. In diesem Kontext kommt allerdings erschwerend hinzu, dass eine individuelle, persönliche Beaufsichtigung der Prüfungen tausender TeilnehmerInnen offline nur schwer zu realisieren ist. Es wird daher eine Technik benötigt, diese Beaufsichtigung online durchzuführen, um die Vertrauenswürdigkeit oder Wertigkeit dieser Zertifikate zu erhöhen. In dieser Studie vergleichen wir verschiedene Spielarten der Online-Aufsicht. Wir stellen die Ergebnisse einiger Umfragen unter unseren TeilnehmerInnen, die sich mit deren Sicht bezüglich der Wertigkeit der Zertifikate befassen, vor und bewerten die Aussagen in unserem Kontext. Schließlich stellen wir ein Experiment vor, das wir mit einer neuen Variante der Online-Aufsicht durchgeführt haben. Anstatt sich auf menschliche Augen zu verlassen, wird ein automatisierter Abgleich des Gesichts vor der Kamera mit einem hinterlegten Bild durchgeführt, um zu überprüfen ob die angemeldete TeilnehmerIn auch die ist, die die Prüfung ablegt.
Enhance Embedded System E-learning Experience with Sensors. Malchow, Martin; Renz, Jan; Bauer, Matthias; Meinel, Christoph (2016). 175–183.
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.
Vagrant Virtual Machines for Hands-On Exercises in Massive Open Online Courses. Staubitz, Thomas; Brehm, Maximilian; Jasper, Johannes; Werkmeister, Thomas; Teusner, Ralf; Willems, Christian; Renz, Jan; Meinel, Christoph (2016). 363–373.
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.
Cellular Automata as Basis for Programming Exercises in a MOOC on Testdriven Development. Staubitz, Thomas; Teusner, Ralf; Prakash, Nishanth; Meinel, Christoph (2016).
AbstractProgramming tasks are an important part of teaching computer programming as they foster students to develop essential programming skills and techniques through practice. The design of educational problems plays a crucial role in the extent to which the experiential knowledge is imparted to the learner both in terms of quality and quantity. Badly designed tasks have been known to put-off students from practicing programming. Hence, there is a need for carefully designed problems. Cellular Automata programming lends itself as a very suitable candidate among problems designed for programming practice. In this paper we describe how various types of problems can be designed using concepts from Cellular Automata and discuss the features which make them good practice problems with regard to instructional pedagogy. We also present a case study on a Cellular Automata programming exercise used in a MOOC on Test Driven Development using JUnit, and discuss the automated evaluation of code submissions and the feedback about the reception of this exercise by participants in this course.
Improving Collaborative Learning With Video Lectures. Bauer, Matthias; Malchow, Martin; Staubitz, Thomas; Meinel, Christoph (2016). 5511–5517.
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.
Enabling Schema Agnostic Learning Analytics in a Service-Oriented MOOC Platform. Renz, Jan; Navarro-Suarez, Gerardo; Sathi, Rowshan; Staubitz, Thomas; Meinel, Christoph (2016).
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.
Improving the Peer Assessment Experience on MOOC Platforms. Staubitz, Thomas; Petrick, Dominic; Bauer, Matthias; Renz, Jan; Meinel, Christoph (2016).
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.
Using A/B Testing in MOOC Environments. Renz, Jan; Hoffmann, Daniel; Staubitz, Thomas; Meinel, Christoph (2016).
Scaling Youth Development Training in IT Using an xMOOC Platform. v. Löwis, Martin; Staubitz, Thomas; Teusner, Ralf; Renz, Jan; Tannert, Susanne; Meinel, Christoph (2015).
Enhancing Content between Iterations of a MOOC – Effects on Key Metrics. Teusner, Ralf; Richly, Keven; Staubitz, Thomas; Renz, Jan (2015). (Vol. 1) 147–156.
AbstractThis paper presents our findings of a comparison study conducted on three iterations of a MOOC run on our platform openHPI. We present the main facts shared by the courses and the planned as well as occurred differences. Additionally, we discuss the added technical features such as user groups along with the expected and actual outcomes. We relate our experiences from the second and third iteration to those of the first one. Findings show that demand for high quality content endures, even if the topic is rather specialized. Expectations of participants towards online courses are growing in general due to an increasing amount of organizations offering lectures. MOOCs are compared to school lessons, distance education and seminars. As a result, the pressure on platforms is increasing with regards to content, service and reliability. To cope with that, we share best practices and propose promising improvements to the platform and future courses.
Optimizing the Video Experience in MOOCs. Renz, Jan; Bauer, Matthias; Malchow, Martin; Staubitz, Thomas; Meinel, Christoph (2015).
Towards Practical Programming Exercises and Automated Assessment in Massive Open Online Courses. Staubitz, Thomas; Klement, Hauke; Renz, Jan; Teusner, Ralf; Meinel, Christoph (2015).
Towards Practical Programming Exercises and Automated Assessment in Massive Open Online Courses. Staubitz, Thomas; Klement, Hauke; Renz, Jan; Teusner, Ralf; Meinel, Christoph (2015).
Scaling Youth Development Training in IT Using an xMOOC Platform. v. Löwis, Martin; Staubitz, Thomas; Teusner, Ralf; Renz, Jan; Tannert, Susanne; Meinel, Christoph (2015).
Towards Social Gamification - Implementing a Social Graph in an xMOOC Platform. Staubitz, Thomas; Woinar, Sebastian; Renz, Jan; Meinel, Christoph (2014).
Lightweight Ad Hoc Assessment of Practical Programming Skills at Scale. Staubitz, Thomas; Renz, Jan; Willems, Christian; Jasper, Johannes; Meinel, Christoph (2014).
Reflections on Enrollment Numbers and Success Rates at the openHPI MOOC Platform. Willems, Christian; Renz, Jan; Staubitz, Thomas; Meinel, Christoph (2014).
Lightweight Ad Hoc Assessment of Practical Programming Skills at Scale. Staubitz, Thomas; Renz, Jan; Willems, Christian; Jasper, Johannes; Meinel, Christoph (2014).
Towards Social Gamification - Implementing a Social Graph in an xMOOC Platform. Staubitz, Thomas; Woinar, Sebastian; Renz, Jan; Meinel, Christoph (2014).
