THE IMPACT OF AI-DRIVEN GAMIFIED LEARNING OF MATHEMATICAL ECONOMICS ON HIGHER-EDUCATION STUDENT MOTIVATION AND ACHIEVEMENT: AN EMPIRICAL SURVEY IN SPORT MANAGEMENT UNDERGRADUATE STUDENTS IN GREECE
E. Choustoulakis
This research investigates the impact of AI-driven gamified learning on the motivation and academic achievement of higher-education students in the field of sport management in Greece. As the educational landscape evolves, integrating Artificial Intelligence (AI) with gamification presents a promising approach to enhance student engagement and performance. This study aims to evaluate the effectiveness of such an approach in a specific academic discipline and cultural context.
The primary goal of this research is to assess how AI-driven gamified learning platforms influence the intrinsic and extrinsic motivation of sport management undergraduates, and to measure their subsequent academic achievement. The study also seeks to identify potential challenges and limitations associated with implementing these technologies in higher education.
Methodologically, the study employs a mixed-methods approach. Quantitative data was collected through pre- and post-intervention surveys assessing student motivation and academic performance metrics. Additionally, qualitative data was gathered via focus group discussions and individual interviews to capture in-depth insights into student experiences and perceptions. The sample comprised 150 undergraduate students from three universities in Greece, participating over a semester-long course integrated with an AI-driven gamified learning platform.
The results indicate a significant positive correlation between the use of AI-driven gamified learning tools and increased levels of student motivation. Notably, students reported higher levels of engagement, satisfaction, and intrinsic motivation towards their coursework. Furthermore, the analysis revealed an improvement in academic achievement, with students in the experimental group outperforming their peers in traditional learning settings. The qualitative findings corroborate these results, highlighting enhanced student interaction, enjoyment, and perceived relevance of the learning material.
Despite these promising findings, the study acknowledges several limitations. The relatively short duration of the intervention limits the ability to generalize long-term impacts. Additionally, the specific cultural and academic context of sport management students in Greece may influence the applicability of results to other disciplines or regions. Technical challenges and varying levels of digital literacy among students also posed potential barriers to the seamless integration of AI-driven gamified learning tools.
In conclusion, this research provides empirical evidence supporting the efficacy of AI-driven gamified learning in enhancing student motivation and academic achievement in higher education. These findings advocate for the broader adoption of such technologies in diverse educational settings. However, further research is recommended to explore long-term impacts, scalability across different disciplines, and the mitigation of technical and contextual barriers. Future studies should also consider larger and more diverse sample sizes to enhance the generalizability of the results. By addressing these areas, educators and policymakers can better harness the potential of AI and gamification to foster an engaging and effective learning environment.
Keywords: AI-driven gamified learning, Higher education, Student motivation, Academic achievement, Sport management, mathematical economics.