Integration of the ethnopedology-based RADEC learning model with artificial intelligence to enhance elementary school students' verbal-linguistic intelligence

The traditional teacher-centered learning model is often ineffective when implemented without variation, leading to student disengagement and boredom. To address this, the Ethno pedagogy-based RADEC learning model integrates local cultural values into education, providing more meaningful learning experiences, particularly in contexts near cultural heritage areas. This study explores the integration of Artificial Intelligence (AI) into the RADEC model to further enhance its effectiveness in improving students' verbal-linguistic intelligence. The primary objectives are to assess the potential of AI-supported RADEC in developing students' listening, speaking, reading, and writing skills, detail its implementation in Indonesian Language classes, and evaluate its impact on learning outcomes. Using a mixed-method approach with a sequential exploratory design, qualitative data were gathered through observations and interviews with principals, teachers, and students. Quantitative data were collected via a quasi-experimental design involving 45 fifth-grade students. Parametric tests, including normality, homogeneity, paired sample t-tests, and N-Gain assessments, were employed. Findings indicate that the integration of AI in the RADEC model could provide personalized feedback, enhance student engagement, and improve performance. Initial results show an increase in average scores from 73.44 to 86.08, with an N-Gain of 0.4198, reflecting moderate improvement. The study highlights the potential of AI in optimizing the RADEC model for broader and more effective educational outcomes.