Enhancing the Competence of High School Teachers in Implementing Deep Learning through Mathematical Connections

Abstract

This community service program aimed to enhance the competence of senior high school mathematics teachers in Banjarmasin City in implementing the Deep Learning approach through the strengthening of mathematical connection skills. The program was conducted using a Community-Based Participatory Research (CBPR) approach, which actively involved the Mathematics Teachers’ Association (MGMP) in the stages of needs identification, program planning, implementation, evaluation, and follow-up. The activity consisted of a 32-hour intensive training held from September 4 to 11, 2025, involving 59 teachers. Program effectiveness was evaluated using a pretest–posttest design comprising 10 multiple-choice items assessing teachers’ understanding of Deep Learning dimensions (meaningful, mindful, and joyful learning) and mathematical connection competencies. The results indicated an increase in the mean score from 86.95 (SD = 8.96) to 90.85 (SD = 10.05), with an average gain of 3.90 points (4.48%). A paired sample t-test demonstrated a statistically significant improvement, t = 2.806, p = 0.007, with a moderate effect size (Cohen’s d = 0.41). In addition to quantitative improvements, teachers demonstrated enhanced ability in designing contextual mathematical problems that integrate inter-topic connections and real-world applications aligned with Deep Learning principles. To promote sustainability, the program was extended through a structured three-month mentoring phase to support classroom implementation and reflective practice. Overall, the findings indicate that the CBPR-based training effectively strengthened teachers’ conceptual understanding and instructional competence while reinforcing collaborative partnerships for sustainable professional development.