Hybrid Gamification and AI Tutoring Framework using Machine Learning and Adaptive Neuro-Fuzzy Inference System

Abstract

Although technology has significantly improved the teaching and learning process, it has not been able to increase students' self-motivation and engagement at the same level. The lack of self-motivation and intermittent engagement is currently one of the primary challenges faced by educators. This new approach to learning called the hybrid gamification framework uses a combination of artificial intelligence (AI), machine learning (ML), and the Adaptive Neuro-Fuzzy Inference System (ANFIS) to create a more engaging and personalized learning experience. By tracking students' interactions and performance, the system can allocate rewards based on their progress, which helps to increase their motivation and engagement. This technology makes it possible for educators to collect and analyse data related to students' engagement patterns, quiz scores, time spent on learning activities, participation in discussion forums, and much more. This data analysis enables educators to identify struggling students and high achievers, allowing them to provide tailored support and instruction to maximize student success. A pilot implementation of this system involving 200 computer science students successfully demonstrated the effectiveness of this technology. This research provides a comprehensive understanding of gamification's impact by combining quantitative data with qualitative insights.