DEVELOPMENT OF DEEP LEARNING E-MODULE ON HEAT AND TEMPERATURE TO IMPROVE LEARNING OUTCOMES

Abstract

This study developed an e-module for deep learning on the topics of temperature and heat to assess the e-module’s feasibility, student learning outcomes, and student responses to the e-module. This study employed a research and development (R&D) methodology. The research and development approach was based on the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). Product feasibility was evaluated through expert validation; students’ cognitive learning outcomes were measured using pretest- posttest assessments; and student responses were measured using a questionnaire. The main gaps identified were that the teaching process remained traditional (lecture method) and the limited development of e-modules that specifically integrate deep learning principles in schools. The results show that the developed deep learning e-module was categorized as highly feasible with a score of 90%. Implementation of the product was proven to improve student learning outcomes, with the average score increasing from 34 to 88 (N-Gain score of 0.8, High Category), and it received an excellent student response rate (87%). This study demonstrates that interactive e- modules applying the principles of meaningful, mindful, and joyful learning are an effective digital solution to address learning boredom and improve student learning outcomes