Optimizing Ethnophysics-Based Deep Learning Strategies to Improve the Quality of Teaching in SMA Negeri 8 Ambon - Marasi Bless Suryan; Erlin Eveline; Anastasija Limba; Seska Malawau; Ashari Bayu Dulhasyim (Pascasarjana Universitas Mataram, 2026)
This community service program aimed to enhance teachers’ pedagogical competence by introducing ethnophysics-based deep learning strategies and diagnostic assessment practices through socialization activities at SMA Negeri 8 Ambon. The program was implemented using a discussion-based approach that encouraged teachers to share classroom experiences, identify instructional challenges, and collaboratively explore contextual teaching strategies. The activity focused on strengthening teachers’ understanding of deep learning principles, which emphasize critical thinking, conceptual understanding, and meaningful learning, as well as the development and use of diagnostic assessments to identify students’ prior knowledge and misconceptions. The results indicated that teachers gained improved understanding of student-centered learning approaches and recognized the importance of integrating local cultural contexts into physics instruction to enhance relevance and engagement. Participants also developed practical insights into designing diagnostic assessment instruments and using assessment data to inform instructional decisions. Active discussions revealed increased teacher awareness of reflective teaching practices and the value of collaboration in professional development. In conclusion, the program effectively supported teachers in adopting more contextual and meaningful teaching practices. The integration of ethnophysics-based deep learning and diagnostic assessment is expected to improve instructional quality and contribute to better student learning outcomes.