Gamification and Machine Learning Inspired Approach for Classroom Engagement and Learning

Abstract

Technology has enhanced the scope and span of the teaching and learning process but somehow it could not enhance the self-motivation and engagement among the students to the same scale. The lack of self-motivation and intermittent engagement is one of the prime challenges faced by educators today. Perplexing tasks for the faculty are to embroil students during the lecture. This work paves new ways to scale up the enticement using artificial intelligence and machine learning. The intelligent framework proposed here is built on yet another novel methodology used globally for user engagement and is termed gamification. The primary objective of the present research work is to negate the issue of disengagement by designing and implementing a gamified framework on 120 students from higher education that will include student engagement, enticement, and motivation. Generally, mechanisms are designed for specific courses, whereas the gamified system proposed is an open-ended method irrespective of course and the program being studied, and this framework has endeavored on multiple courses. To enhance the utility of the gamified framework, ANFIS model is utilized for smart decision-making concerning rewards distribution that is directly proportional to the number of coins gained by the students. As an outcome, better participation of a group of students under the proposed intelligent gamified system is reported as compared to the control group thus endorsing the success of the model.