Development of STEM-Based Renewable Energy E-Learning with Bot (RENEWBOT) on Renewable Energy Topics

Abstract

This study aims to develop and validate a STEM-based learning media called Renewable Energy E-Learning with Bot (RENEWBOT), which is integrated with artificial intelligence (AI) to enhance students' conceptual understanding of renewable energy topics. The research employed a research and development (R&D) method adapted from the Borg and Gall model, consisting of five stages: needs analysis, model design, prototype development, limited implementation, and evaluation. The study involved 10th-grade students from a public high school in Jakarta, with approximately 60 participants selected through purposive sampling. Data were collected using observation sheets, questionnaires, and a learning outcome test comprising 30 multiple-choice items. The results indicate that the developed media is valid, practical, and effective in improving students' conceptual understanding, as evidenced by the increase in posttest scores and normalized gain (N-gain). Furthermore, the integration of AI-based chatbot features supports interactive and adaptive learning, enabling students to engage more actively with the material. In conclusion, the RENEWBOT media has strong potential to support STEM-based learning and improve students' understanding of renewable energy concepts in a more contextual and engaging manner.