Interactive Problem-Based e-Module with Deep Learning Approach to Stimulate Computational Thinking and Self-Regulated Learning - Huda, Anwaril; Suyatna, Agus; Rohman, Fatkhur; Abdurrahman; Herlina, Kartini (Tadris: Jurnal Keguruan dan Ilmu Tarbiyah, 2025)
Teaching materials that stimulate Computational Thinking (CT) and Self-Regulated Learning (SRL), particularly for high school electricity topics, are currently limited. This study aims to develop an interactive problem-based e-module with a deep learning approach that is valid and suitable for pilot use to support CT and SRL. A mixed-methods design was employed, and the e-module was developed using the ADDIE model (analysis, design, development, implementation, evaluation). Validation was conducted by five experts (three lecturers and two physics teachers), assessing content, design, and language. A needs analysis of 50 high school physics teachers revealed that 76% had not actively stimulated CT in their teaching, and 90% reported the absence of problem-based interactive e-modules for CT and SRL. Expert validation resulted in an average score of 87.6%, indicating the product's validity. Teacher and student responses yielded practicality scores of 94.47% and 95.26%, respectively, showing the e-module's high suitability for use. Evaluation of learning effectiveness, including CT and SRL gains, remains an area for future research. In conclusion, the findings indicate that the developed e-module effectively addresses the need for problem-based digital learning materials and is ready for preliminary implementation to support CT and SRL development.