<![CDATA[Background. This study investigates the pedagogical strategies employed by junior secondary science teachers in designing deep Learning–oriented instruction on living systems and cells. Deep Learning is defined as an instructional orientation that promotes conceptual understanding, cognitive integration, and higher-order thinking skills. Methods. Adopting a qualitative case study approach, data were collected from five science teachers across diverse school contexts in Bantul Regency. Empirical evidence was generated through five semi-structured, in-depth interviews conducted between 18-22 July 2025, each lasting 60–90 minutes, complemented by a document analysis of five instructional planning documents, one from each participating teacher. The interviews were guided by a combined curricular and professional noticing framework, enabling systematic examination of teachers’ decision-making processes. Results. The findings reveal three significant insights. First, Grade VIII science lesson planning aligned with the independent curriculum and deep learning principles is structured to support experiences of conceptual understanding, application, and reflection. Conceptual understanding is facilitated through discussions, multiple learning resources, student projects, and presentations; application is emphasized through real-world case studies; and reflection is integrated through the evaluation of learning outcomes and opportunities for personal improvement. Second, teachers anticipate variations in students’ prior knowledge and tendencies toward passive participation. Third, in response, they adopt an asset-based approach and implement instructional steps to promote mindful, meaningful, reflective engagement that extends beyond traditional cognitive assessment. Conclusion. Theoretically, this study contributes to the literature on science pedagogical design by demonstrating how professional noticing can function as an analytic lens for understanding teachers’ planning for deep Learning, particularly in contexts transitioning toward competency-based curricula. The findings also extend existing discussions on deep Learning by illustrating how teachers translate curricular expectations into concrete pedagogical decisions within real classroom constraints.]]>
