Enhancing Student Motivation in Programming Education Through N-EGM-Based Gamification: A Mobile Application Approach
DOI:
https://doi.org/10.37385/jaets.v7i2.8721Keywords:
Gamification, HMSAM, N-EGM, Programming, Motivation, EngagementAbstract
Programming education continues to face persistent challenges, including high cognitive load, abstract syntax complexity, and declining intrinsic motivation among students. Although gamification has been widely adopted to address these issues, existing frameworks such as MDA and Octalysis lack structured personalization and socialization mechanisms tailored specifically for programming learning contexts. This study proposes a mobile-based programming learning application designed using the Newton Enhanced Gamification Model (N-EGM) and empirically evaluates its effectiveness through the Hedonic Motivation System Adoption Model (HMSAM). The study involved 116 undergraduate Informatics students selected using purposive sampling. Data were collected using validated questionnaire instruments and analyzed through descriptive statistics, reliability testing, multiple regression analysis, multicollinearity diagnostics, and common method bias detection using SPSS. The findings indicate that gamification elements mapped through the N-EGM framework explain 99.1% of the variance in student motivation and 98.9% of the variance in engagement (p < 0.001). Leaderboard and Objective elements were the strongest predictors of motivation, while Economy and Quest significantly influenced immersion. Multicollinearity diagnostics confirmed acceptable VIF values (< 5), and Harman’s single-factor test indicated no critical common method bias. Theoretically, this study contributes by integrating a structured multi-layer gamification framework with a hedonic adoption model in a programming education context. Practically, it provides a systematic design blueprint for implementing adaptive and socially integrated gamification strategies in mobile STEM learning environments.
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