Enhancing Students’ Mathematical Communication through Deep Learning-Based Course Review Horay in the Society 5.0 Era - Eko Agustiawan; Agusriyanti Puspitorini; Kurratul Aini (AL-ISHLAH: Jurnal Pendidikan, 2025)
In the Society 5.0 era, students are expected to not only solve mathematical problems but also articulate their reasoning clearly. However, many students struggle with mathematical communication, especially in expressing, justifying, and representing their thinking. This study investigates the effectiveness of the Deep Learning-Based Course Review Horay (CRH) model in enhancing students’ mathematical communication skills through an interactive and technology-supported approach. A sequential explanatory mixed-methods design was employed involving 15 eighth-grade students at MTs. Nurul Hidayah, Sumenep. The intervention integrated Course Review Horay—a collaborative, game-based strategy—with deep learning analytics that provided automated, personalized feedback on students’ written responses. Quantitative data were collected using a validated Mathematical Communication Test (pre- and post-intervention), while qualitative insights were drawn from classroom observations and student interviews. Findings revealed a significant improvement in mathematical communication scores, from a pretest mean of 42.87 to a posttest mean of 78.93, t(14) = 4.38, p 0.001, with a large effect size (Cohen’s d = 1.13). Thematic analysis showed increased participation, clearer expression of reasoning, and enhanced student confidence supported by real-time feedback. The Deep Learning-Based CRH model effectively fostered cognitive and communicative growth by combining active learning and intelligent feedback. It supported students in verbalizing, representing, and justifying mathematical ideas in a low-anxiety, reflective environment. This model presents a scalable, student-centered approach aligned with the goals of Society 5.0 and 21st-century education.