An Artificial Intelligence-Based Mathematics Education Evaluation Model To Improve Research Quality In Higher Education Institutions - Syahrir Syahrir; A. Fandir (Lembaga Bale Literasi, 2026)
The low accuracy and objectivity of manual evaluation of mathematics learning in higher education impacts the quality of student research. This study aims to develop an Artificial Intelligence (AI)-based evaluation model to improve the effectiveness of assessment and the quality of mathematics education research. The method used was Research and Development (R&D) with a modified Borg & Gall model, encompassing needs analysis, design, expert validation, and limited trials. The resulting model consists of four main components: Data Input, AI Processing, Assessment Output, and Feedback System, all connected through a feedback loop. Validation results showed a