An Adaptive Testcase Recommendation System to Engage Students in Learning: A Practice Study in Fundamental Programming Courses

This paper proposes a testcase recommendation system (TRS) to assist beginner-level learners in introductory programming courses with completing assignments on learning management (LMS). These often struggle generate complex testcases and handle numerous code errors, leading disengaging their attention from the study. The proposed TRS addresses this problem by applying using singular value decomposition (SVD) zone of proximal development (ZPD) provide small appropriate set based learner’s ability. We implement university-level Fundamental Programming for evaluation. data analysis has demonstrated that significantly increases student interactions system.