A Machine Learning Based Method to Evaluate Learning in Gamification Practices

Abstract

With the integration of advanced methods and technologies in higher vocational education, educational gamification has emerged as a new approach to encourage students’ active participation in learning. However, it is difficult to accurately evaluate student participation in this environment and delve into the process of interactive evolution. Most existing research methods primarily focus on qualitative analysis, while attempts to conduct quantitative analysis are often constrained by traditional statistical methods. Moreover, these methods frequently fail to consider the interactive dynamics that occur between teachers and students. This study proposes a method to evaluate learning participation in educational gamification. K-means clustering was used, and a framework for educational gamification was constructed using a process interaction evolutionary game. By conducting a thorough analysis of the interactive dynamics between teachers and students, this study offers practical guidance and strategies for educators.