Development of the AI-Personalized Learning Framework Model: An Innovation for Enhancing Student Effectiveness and Engagement in Modern Education

Abstract

Abstract: This study aims to develop the AI-Personalized Learning Framework (AI-PLF) as an innovative framework to strengthen student personalized learning through artificial intelligence (AI) in school settings. Employing a research and development (R&D) approach with a modified ADDIE model, the study involved teachers, students, and experts. Data were collected using questionnaires, interviews, and expert validation, and analyzed using descriptive and quantitative methods. Initial findings indicate that teachers hold positive perceptions and demonstrate high readiness for AI integration. The AI-PLF model was structured into four main stages: data collection, analysis of student learning behavior, content personalization, and learning implementation. Pilot testing showed that teachers found the model practical and beneficial, while students responded positively to personalized learning experiences. The Aiken’s V score of 0.89 confirmed the high validity of the framework. This study contributes to the advancement of educational science, particularly in integrating AI technologies to enhance learning effectiveness, engagement, and instructional differentiation in a sustainable and adaptive manner.

Keywords: personalized learning, artificial intelligence, AI-PLF, framework, education