Tailoring Themes and Elements Based on Learning Styles and Player Types in Adaptive Gamification in Education

Authors

  • Srimathi S Department of Applied Mathematics and Computational Science, Thiagarajar College of Engineering, Madurai, Tamilnadu
  • Anitha D Department of Applied Mathematics and Computational Science, Thiagarajar College of Engineering, Madurai, Tamilnadu

DOI:

https://doi.org/10.16920/jeet/2025/v38is2/25069

Keywords:

Adaptive Gamification; Bartle’s Player Type; Comparative analysis; Factor analysis; FSLSM; Fuzzy C means clustering.

Abstract

Gamification has become a powerful tool for enhancing student engagement in educational settings However, the effectiveness of a gamified system depends on its alignment with individual student characteristics. This has led to the rise of adaptive gamification, where game elements are tailored to meet the unique needs of each learner. This research aims to bridge the gap between adaptive gamification and student-centered learning by designing a personalized gamification platform based on the Felder-Silverman Learning Style Model (FSLSM) and Bartle's Four Player Types. However, traditional questionnaires can be overwhelming and potentially affect student engagement. This study aims to reduce lengthy versions of these questionnaires that retain diagnostic power while being more manageable for students, with the help of factor analysis and comparative analysis, FSLSM and Bartle’s player type questionnaires were reduced. Then a questionnaire is developed with reduced version of FSLSM and Bartle’s player type with some more questions to capture learners’ preferences for gamification element, themes, and suggestions for improving the gamified platform for education. This developed questionnaire has been floated among college students. Out of 218 valid responses, fuzzy c-means clustering revealed four distinct clusters, with two major clusters showing strong preferences for specific gamification themes. These themes were integrated into the platform to create a more engaging and personalized experience. By reducing and validating the FSLSM and Bartle’s questionnaires, this research offers a streamlined approach for educators to implement personalized gamification strategies in the classroom. The findings provide insights for developing effective, student-centered adaptive gamification systems in education.

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Published

2025-05-12

How to Cite

S, S., & D, A. (2025). Tailoring Themes and Elements Based on Learning Styles and Player Types in Adaptive Gamification in Education. Journal of Engineering Education Transformations, 38(2), 559–566. https://doi.org/10.16920/jeet/2025/v38is2/25069

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