Math-VR: Mathematics Serious Game for Madrasah Students using Combination of Virtual Reality and Ambient Intelligence

Abstract

The challenge to increasing understanding of mathematics lessons for students in madrasah schools makes the learning process require the support of adaptive alternative learning media. In this study, we propose a serious game-based learning media supported by virtual reality and ambient intelligence technology to equip students with adaptive responses to subject matter scenarios. Ambient intelligence works based on recommendations generated by the Multi-Criteria Recommender System (MCRS). In calculating a similarity between users and reference data, MCRS uses cosine-based similarity calculations, and average similarity is used for ranking. We developed this learning media experiment called Math-VR using the Unity game engine. The experimental test results show that MCRS-based ambient intelligence technology can provide an adaptive response to the choice of geometry subject matter recommendations for students according to their pre-test results. The analysis results show that the recommendation system as part of ambient intelligence has the highest accuracy rate of 0.92 when using 80 reference data.