Hasso-Plattner-Institut
 
    • de
 

Jan Renz

Hasso-Plattner-Institut (HPI) für
Softwaresystemtechnik GmbH
Universität Potsdam
Prof.-Dr.-Helmert-Str. 2-3
D-14482 Potsdam
Germany 

office:

H-1.36

phone:

+49 (0)331-5509-283

fax:

+49 (0)331-5509-325

e-mail:

jan.renz(at)hpi.de

Publications

Enhance Embedded System E-learning Experience with Sensors

Martin Malchow, Jan Renz, Matthias Bauer, Christoph Meinel
In 2016 IEEE Global Engineering Education Conference (EDUCON), pages 175-183, 4 2016 IEEE.

DOI: 10.1109/EDUCON.2016.7474550

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.

Keywords:

Teleteaching, Tele-Lecturing, Distance Learning, E-Learning, Virtual Lab, computer aided instruction,computer science education,educational courses,embedded systems,MOOC,Web technologies,analog-to-digital converter,electronic learning,embedded LED system,embedded system e-learning experience,learning experience,light sensor,massive open online courses,programming exercises,programming language learning,student code execution evaluation,student feedback,student motivation,temperature sensor,Embedded systems,Sensor systems

BibTeX file

@inproceedings{Martin2016a,
author = { Martin Malchow, Jan Renz, Matthias Bauer, Christoph Meinel },
title = { Enhance Embedded System E-learning Experience with Sensors },
year = { 2016 },
pages = { 175-183 },
month = { 4 },
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. },
keywords = { Teleteaching, Tele-Lecturing, Distance Learning, E-Learning, Virtual Lab, computer aided instruction,computer science education,educational courses,embedded systems,MOOC,Web technologies,analog-to-digital converter,electronic learning,embedded LED system,embedded system e-learning experience,learning experience,light sensor,massive open online courses,programming exercises,programming language learning,student code execution evaluation,student feedback,student motivation,temperature sensor,Embedded systems,Sensor systems },
publisher = { IEEE },
booktitle = { 2016 IEEE Global Engineering Education Conference (EDUCON) },
priority = { 0 }
}

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last change: Wed, 21 Dec 2016 10:57:18 +0100