Development of an artificial intelligence based fine arts learning management system using the borg & gall model to enhance learning effectiveness
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This study aims to develop an artificial intelligence (AI)-based Learning Management System (LMS) specifically designed for two-dimensional art learning. This system integrates three main AI-based features, namely learning analytics (TrackBoot), intelligent tutoring chatbot (ArtBoot), and adaptive recommendation engine. The research used the Research and Development (R&D) method with the Borg & Gall model, which includes the stages of needs analysis, planning, development, expert validation, limited and main field trials, and final product revision. Data were collected through pre-tests and post-tests, validation sheets, practicality questionnaires, and LMS activity logs. The results showed a significant increase in student learning outcomes with an average N-Gain score of 0.78 (high category). The validity of the material and media increased from the “Less Valid” category to “Very Valid,” while the practicality level reached a score of 4.49 (very practical category). Regression analysis showed that interaction with ArtBoot had a significant effect on student learning outcomes (p < 0.001). These findings prove that AI integration through learning analytics, adaptive feedback, and personalized learning is effective in increasing student motivation, conceptual understanding, and learning independence. This research contributes to the development of adaptive, contextual AI-based digital learning innovations that are in line with the spirit of the Merdeka Curriculum.
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