Integrating AI in individualized mathematics learning: A teacher-centered approach - Sunarto, M. J. Dewiyani (Universitas Islam Negeri Raden Intan Lampung, 2025)
The background of this research lies in the challenge of implementing individualized mathematics learning supported by Artificial Intelligence (AI) technology. This study aims to produce a valid learning model evaluated by experts in mathematics education and educational technology. The research adopts a Research and Development (R and D) approach following the Plomp model, which includes preliminary investigation, design, and development, and evaluation stages. The developed model integrates individualized learning principles and AI assistance to accommodate student differences, flexible learning paths, and adaptive feedback. Five experts conducted validation through content and construct assessments using validation sheets and interviews. The results indicate that the model achieved very high validity in content, construct, and feasibility aspects, supported by ICC and Cronbach’s Alpha values showing good reliability and consistency. These findings demonstrate that the model is theoretically and practically sound for use without revision. The study also provides a theoretical synthesis of individual learning, AI, and differentiated mathematics learning concepts, offering a framework applicable across educational levels. The developed model contributes to designing inclusive, adaptive, and transformative mathematics learning aligned with 21st-century competencies and highlights AI’s role as a supportive tool rather than a substitute for teachers in the learning process.