Profile of Deep Learning Implementation to Support High School Students' Conceptual Understanding of The Future Value of Annuity - Dina Maharini; Erlita Nur Rahmawati; Sunismi Sunismi; Any Herawati; Retno Trisniwari (Mathline : Jurnal Matematika dan Pendidikan Matematika, 2026)
This study reviewed the implementation of deep learning through discovery learning on the future value of annuity topic in senior high school mathematics, addressing Indonesia’s low PISA and OECD numeracy scores. Deep learning, grounded in the principles of meaningful, mindful, and joyful learning, is considered a promising approach to strengthen students’ conceptual understanding. This study aims to (1) analyze the implementation profile of deep learning by a model teacher on the future value of annuity topic, and (2) examine how learning activities support students’ conceptual understanding. A qualitative descriptive approach with a classroom-based study design was employed. The subject was a model teacher implementing on the topic of the Future Value of Annuity in a Grade XI class at a public senior high school in East Java. Data were collected through classroom video recordings and analyzed using lesson transcripts and student worksheets from three students representing high, moderate, and low ability levels, selected based on diagnostic assessment results. The analysis was conducted using the seven indicators of conceptual understanding proposed by the NCTM. Results show the teacher successfully integrated the three deep learning principles. In the opening activity, the teacher built readiness through contextual apperception and motivation. In the core activity, discovery learning enabled students to actively construct understanding of pranumerando and postnumerando through problem identification, data collection, processing, verification, and group presentation. Differentiated instruction based on diagnostic assessment and individual scaffolding supported students across ability levels. However, reflection and closing activities could not be completed due to time constraints from student mobilization between rooms. Overall, deep learning through discovery learning on the future value of annuity topic created active, contextual, and student-centered learning that strengthened students’ conceptual understanding.