Rini Rosmiati (1)
General Background: Mathematics learning in elementary schools requires learning media that support conceptual understanding through interactive and technology-based approaches. Specific Background: Fraction topics remain challenging for students due to limited visualization and minimal utilization of digital learning media in classroom practice. Knowledge Gap: Although educational games and deep learning approaches have been discussed separately, the development of web-based educational games explicitly integrating deep learning principles for elementary fraction learning is still limited. Aims: This study aims to develop a web-based educational game applying a deep learning approach to support fourth-grade students’ understanding of fraction concepts. Results: Using a Research and Development method with the ADDIE model, the developed game “Pizzeria Pecahan – Ultimate Edition” obtained very high validation scores from material experts, media experts, and classroom teachers, and student learning outcomes showed a notable increase between pretest and posttest results. Novelty: This study presents a web-based educational game that systematically embeds deep learning elements such as exploration, reflection, and problem-solving within fraction learning activities. Implications: The findings indicate that web-based game media grounded in deep learning principles can serve as an alternative digital learning resource to support meaningful and student-centered mathematics learning in elementary education.
• The study produced a web-based educational game integrating deep learning principles• Expert validation confirmed high feasibility in content, design, and pedagogy• Student fraction understanding showed substantial improvement after implementation
Educational Game; Deep Learning; Fraction Concepts; Web-Based Learning Media; Mathematics Learning
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