Bayesian Knowledge Tracing Implemented in a Telecommunications Serious Game

Abstract

The University of Johannesburg has integrated serious games into its teaching, exemplified by Codebreakers, a 2D game teaching information theory. While successful, Codebreakers lacked personalisation and used a criticised assessment method based on answer streaks. Knowledge tracing algorithms, known for their effectiveness in intelligent tutoring systems, were considered to address these limitations. This led to the research question: "Can a new serious game be designed, incorporating knowledge tracing algorithms to deliver personalised learning experiences in telecommunications education?" In response, an escape-themed serious game was developed, integrating Bayesian Knowledge Tracing as a statistical student model for personalised learning. This innovative approach combines free-roam gameplay with tailored educational content, significantly advancing serious game design. While primarily aimed at enhancing Codebreakers, this new game contributes substantially to serious game theory by successfully implementing personalised learning within an engaging format. The project showcases the potential of knowledge tracing algorithms in creating adaptive, student-centered learning experiences within the context of educational games.

Keywords

• Knowledge Tracing
• Serious Games
• Procedural Generation
• Synthetic data generation
• 3D virtual environments
• Unity