TRANSFORMING CHEMISTRY LEARNING THROUGH DEEP LEARNING: AN EVALUATION WITH CIPP MODEL

Abstract

Deep learning has emerged as a transformative pedagogical approach that emphasizes mindful, meaningful, and joyful learning experiences. In the context of chemistry education, this approach encourages students to connect scientific concepts with real-life situations and to develop higher-order thinking skills aligned with the Merdeka Curriculum. This study aims to evaluate the implementation of the deep learning approach in chemistry education through the Context, Input, Process, and Product (CIPP) evaluation model. A qualitative evaluative design was employed, involving classroom observations, document analysis, and interviews with teachers and students. Data were analyzed inductively to capture the processes, impacts, and challenges of deep learning implementation in school settings. The findings indicate that the principles of deep learning, though not yet formally institutionalized, have been partially applied in chemistry instruction. Teachers and students demonstrated positive engagement in connecting learning materials to real-world contexts. The learning environment supports active participation and enhances students’ conceptual understanding and motivation. However, challenges remain, including limited teacher training, time constraints, and varying student competencies. The study concludes that deep learning holds strong potential for improving the quality of chemistry education when supported by professional development, institutional facilitation, and curriculum alignment. Effective implementation of this approach can further realize the objectives of the Merdeka Curriculum and nurture students’ critical and creative capacities.