Visualizing the invisible: A deep learning-based VR module to enhance students’ communication of integral area concepts - Alfiani Athma Putri Rosyadi; Octavina Rizky Putri Utami; Mohammad Syaifuddin; Z. Zukhrufurrohmah; Rabia Rasheed (Universitas Muhammadiyah Malang, 2026)
Background-Students' low mathematical communication skills are caused by difficulties in visualizing abstract calculus concepts, such as integral areas. Objectives-This study aims to develop and evaluate a deep learning-based VR module specifically designed to enhance students' mathematical communication skills. Method-This study is a Research and Development (R&D) project employing the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). The research instruments included expert validation sheets, mathematical communication ability tests (pre-test and post-test), and student response questionnaires. Data were analyzed descriptively to determine validity and effectiveness through the N-Gain test. Results-The results indicate that the developed VR module met high validity criteria, with an average score of 88.8% from both subject matter and media experts. The implementation of this module significantly improved students' mathematical communication skills, as evidenced by an increase in the average score from 58.5 to 84.2, with an N-Gain value of 0.62 (moderate category). Conclusions-The deep learning-based VR module is proven to be a valid and effective tool in assisting students to communicate complex mathematical concepts.