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arXiv · 2404.15301

Development of a Gamification Model for Personalized E-learning

Abstract

This study designed a personality-based gamification model for E-learning systems. It also implemented the model and evaluated the performance of the gamification model implemented. These were with a view to developing a model for gamifying personalization of e-learning systems. Personalization requirements for motivational tendencies based on the Myers-Briggs Type Indicator (MBTI) and gamification elements were elicited for e-learning from existing literature and from education experts using interview and questionnaire. The gamification model for personalized e-learning was designed by mapping motivational tendencies to corresponding gamification elements using set theory and rendered using Unified modelling language (UML) tools. The model was implemented using Hypertext Markup Language for the front end, Hypertext Preprocessor (PHP) for the backend and Structured Query Language (SQL) for database on WordPress. The model was evaluated using appeal, emotion, user-centricity as well as satisfaction as engagement criteria, and clarity, error correction as well as feedback for educational usability. The results collected from the implemented system database and questionnaires administered to learners showed an average appeal rating of 4.3, an emotion rating of 4.5, a user-centricity rating of 4.4, and a satisfaction rating of 4.4 in terms of engagement on a 5.0 scale. The results also showed that clarity, error correction and feedback received an average rating of 3.9, 4.7, and 4.8 respectively on a 5.0 scale concerning educational usability. In addition, when comparing educational usability (4.5) to engagement (4.4), educational usability received slightly higher ratings. The study concluded that the gamification model for personalized e-learning was suitable for increasing learner motivation and engagement within the personalized e-learning environment.

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BibTeXRIS

Afvensu Enoch Ibisu. 2024-03-28. Development of a Gamification Model for Personalized E-learning. https://arxiv.org/abs/2404.15301

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