Master Thesis MSTR-2021-12

BibliographyEscobar Gava, Tatiane: A gamification-based approach for learning IoT.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Master Thesis No. 12 (2021).
105 pages, english.
Abstract

In recent years, gamification has been employed in several domains, including in IoT applications, to improve, for example, human engagement, performance and sustainability. Such an approach aims to increase human motivation by employing gamified elements (e.g., badges, points) in non-game contexts. To support the learning process, a gamification approach was developed in the scope of this master thesis to teach IoT concepts within IoT platforms. To achieve this goal, several gamification-based frameworks have been analyzed. Based on this analysis, a generic gamification-based approach to learn IoT concepts was designed and prototypically implemented. To verify the effectiveness of the elements, a user experience evaluation was performed with 10 participants, which verified the learning growth in IoT and the behaviours generated with the gamified elements. This evaluation proved that the participants learned the main concepts of IoT and that all the elements implemented in the prototype proved to be important for the user’s journey in learning. In conclusion, the goals of this master thesis were achieved through proofing of IoT knowledge growth and that the gamified elements proved to be important throughout the journey, as pointed out by the user evaluation participants.

Department(s)University of Stuttgart, Institute of Software Technology, Empirical Software Engineering
Superviser(s)Wagner, Prof. Stefan; Franco da Silva, Dr. Ana Cristina; Hirmer, Dr. Pascal
Entry dateMay 14, 2021
   Publ. Computer Science