Validity Analysis of Renewable Energy E-Module Based on Deep Learning Approach and Local Wisdom Assisted by Canva AI to Facilitate Students' Creative Thinking Skills

Abstract

The rapid development of science and technology in the 21st century requires education to focus not only on mastering concepts but also on developing high-level competencies, particularly creative thinking skills. However, a preliminary study at SMAN 15 Padang showed that students' creative thinking skills in physics learning are still low, especially in linking physics concepts to contextual issues such as renewable energy. This study aims to develop and test the validity of a renewable energy e-module based on a deep learning approach (mindful, meaningful, and joyful learning) and local wisdom assisted by Canva AI to facilitate students' creative thinking skills. This study uses the Research and Development (R&D) method with the 4D model (Define, Design, Develop, Disseminate), which is limited to the validation stage. The e-module was validated by three physics lecturers of FMIPA Padang State University using a four-point Likert scale questionnaire analyzed with Aiken's V index. The results showed that the e-module obtained an average overall validity value of 0.95 (very valid category), including material substance (0.94), visual communication (0.96), learning design (0.96), software utilization (0.93), application of deep learning approach and local wisdom (0.91), and creative thinking skills (1.00). These findings indicate that the developed e-module is very valid and suitable for use as an innovative teaching material to support meaningful and contextual physics learning in accordance with the demands of 21st century competencies.