Bachelor Thesis BCLR-2022-45

BibliographyFriedel, Christian: Integrating an emotion-based Teachable Machine into Moodle e-learning Platform.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Bachelor Thesis No. 45 (2022).
45 pages, english.

Online learning is an increasingly important component for schools and universities, especially since the spread of COVID-19. While e-learning enables many possibilities, it also comes with its own challenges for both the teaching staff and the students. Therefore, it is important to support tools to allow the creation of online courses and the participation in them as easy and flexible as possible. There are several platforms that are available that already offer lots of useful functionalities, one of them being Moodle, an open source e-learning platform that is free to use. While Moodle already offers many core functions for creating online courses by itself, it allows the option to expand its functionality through the support of plugin. These Plugins can be installed to improve the experience for bot teaching staff and the students. While many plugin focuses on general base functionalities, this thesis is about creating a plugin specifically teaching machine learning of facial emotions. Therefore, a concept used by Teachable Machine is being adapted to specialize on facial emotion recognition and then implemented into a plugin for Moodle to support its usage in online courses on Moodle. The goal is to create a prototype for practical example of emotion recognition through machine learning and make it available for the online learning platform Moodle, in a way that is easy to use for both faculty and students, so that students can test out machine learning in the Moodle course itself. The prototype is ready to run, but there is still potential for improvement to make the application as user-friendly and instructive as possible.

Department(s)University of Stuttgart, Institute of Software Technology, Empirical Software Engineering
Superviser(s)Graziotin, Dr. Daniel; Michels, Lisa-Marie
Entry dateOctober 27, 2022
   Publ. Computer Science