AI-OPTIMIZATION FOR LESSON PLANNING TO ADDRESS STUDENT PSYCHOLOGY GAPS IN ELEMENTARY SCHOOLS - Nurfatih, Muhammad Sulkhan; Zikry, Arief (LPPM UNIVERSITAS BINA INSAN, 2024)
This study aims to optimize the use of artificial intelligence technology, specifically GPT (Generative Pre-trained Transformer), in creating personalized lesson plans (RPP) tailored to the psychology and learning styles of students at SD Negeri 2 Muara Enim. The use of GPT is expected to assist teachers in understanding the individual psychological needs of students, addressing the limitations of counseling services at the school. The research methodology includes three main phases: analysis, system design, and implementation. During the analysis phase, demographic, academic, psychological, and contextual data of students were collected to identify key correlations influencing academic performance. This data was then used to train a machine learning model using the k-means clustering algorithm, aimed at grouping students based on their learning characteristics. The findings indicate that GPT was successfully implemented to generate lesson plans aligned with students' psychological profiles and learning styles. The developed web-based system enables teachers to effectively personalize the learning process. Moreover, the application simplifies the lesson plan creation process by offering teaching strategy recommendations relevant to each student group. In conclusion, the use of GPT proves beneficial in enhancing the effectiveness of classroom learning and provides a solution to teachers' challenges in understanding students' psychological needs.