Examining Individual and Group Kahoot! Participation as Predictors of Student Engagement in Game-Based Learning: Evidence from Higher Education Business Students in the UK

Abstract

This study investigates the predictive effects of individual and group Kahoot! participation constructs on student engagement in game-based learning within higher education. A quantitative cross-sectional research design was employed using a structured questionnaire administered to 111 business students enrolled in a Pearson BTEC Higher National Diploma programme in the United Kingdom. Data were analysed using simple, multiple and hierarchical regression techniques in SPSS to examine both individual and combined effects of participation constructs on student engagement. The findings reveal that individual participation constructs, particularly participation intensity and decision autonomy, significantly predict student engagement, whereas competitive engagement does not remain significant when analysed alongside other variables. For group participation, collaborative participation and shared decision making demonstrate significant positive effects, while group interaction does not show an independent effect in the combined model. The results further indicate that group participation constructs explain a greater proportion of variance in student engagement compared to individual participation constructs. Hierarchical regression analysis confirms that the inclusion of group-based variables significantly enhances the predictive power of the model. The study concludes that although both participation modes contribute to engagement, structured collaborative processes, especially shared decision making, have a stronger association with higher levels of engagement in Kahoot based learning environments. The study contributes to existing literature by providing a comparative analysis of participation modes and offers practical implications for the design of interactive learning strategies in higher education.