Deep Learning Based Interactive Edpuzzle Improves Science Learning Outcomes on Energy in Elementary School Students - Shelly Mei Fransiska; Muhammad Nuruddin (Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya, 2025)
Background: Science learning in elementary schools still faces challenges because many materials—particularly energy concepts—are abstract and difficult for students to understand, resulting in low learning outcomes. This condition requires learning media that provide more interactive and meaningful learning experiences. Aim: This study aims to examine the effect of using Edpuzzle as an interactive video-based learning medium supported by a deep learning approach, which in this study refers to deep conceptual learning rather than the use of artificial intelligence algorithms. Method: The research employed a quantitative method with a one-group pretest–posttest design involving 30 fourth-grade students from SDN Banjaragung 3 Jombang. The research instrument consisted of validated and reliable multiple-choice learning outcome tests, and the data were analyzed using a paired sample t-test at a 0.05 significance level. The findings show a significant increase in students’ average scores, rising from 58.20 on the pretest to 82.40 on the posttest. Prerequisite tests confirmed that the data met normality and homogeneity assumptions, while hypothesis testing produced a significance value of 0.000 < 0.05, indicating a meaningful difference between pretest and posttest scores. Therefore, the use of Edpuzzle supported by a deep conceptual learning approach is effective in improving students’ understanding of energy concepts and their science learning outcomes.