Desain Pembelajaran Deep Learning: Integrasi Contextual Teaching and Learning terhadap Peningkatan Komunikasi Matematis Siswa SMP

Abstract

Mathematical communication skills are one of the essential competencies that need to be developed in mathematics learning; however, these skills remain relatively low among many junior high school students. This study aims to describe the implementation of a Deep Learning instructional design integrated with the Contextual Teaching and Learning (CTL) approach and to analyze the improvement of students’ mathematical communication skills in learning solid geometry, particularly cubes. This research employed a pre-experimental method with a One Group Pretest–Posttest Design involving 30 eighth-grade students at SMPIT Putri Al-Hanif Cilegon, selected through purposive sampling. The research instrument was a mathematical communication skills test that had met the criteria of validity, reliability, difficulty index, and discrimination power. The data were analyzed using N-Gain calculations, the Shapiro–Wilk normality test, and the Paired Sample t-Test. The results showed that the instructional design integrated the three dimensions of Deep Learning, namely meaningful learning, mindful learning, and joyful learning, with CTL learning syntax to develop mathematical communication indicators consisting of Written Text, Drawing, and Mathematical Expression. The average N-Gain score was 0.80, which was categorized as “high”, while the paired sample t-test results showed a t-value of |t| = 37.530 with a significance level of 0.000 < 0.05, indicating a significant improvement in students’ mathematical communication skills. Therefore, the findings of this study suggest that implementing a Deep Learning instructional design integrated with the Contextual Teaching and Learning (CTL) approach has the potential to enhance students' mathematical communication skills.