Teachers’ Perceptions of Deep Learning-Based Instructional Transformation in the Context of Primary Education Reform

Abstract

The global shift toward deep learning-oriented pedagogy has redefined instructional transformation in primary education; however, empirical evidence regarding teachers’ perceptions as a mediating factor of reform remains limited, particularly in developing educational contexts. This study aims to examine primary school teachers’ perceptions of deep learning-based instructional transformation and to identify their cognitive understanding, affective disposition, and behavioral readiness toward its implementation. Employing a quantitative survey design, the study involved 87 primary school teachers selected through purposive sampling. Data were collected using a validated perception instrument and analyzed using descriptive statistical techniques. The findings indicate that teachers demonstrate a high conceptual endorsement of deep learning principles, particularly in fostering critical thinking, meaningful engagement, and knowledge transfer. Nevertheless, a moderate level of behavioral readiness suggests a perception–practice gap, especially in authentic assessment design and instructional alignment. Theoretically, this study contributes by positioning teacher perception as a strategic lever in systemic pedagogical transformation and extends deep learning discourse within primary education reform frameworks. Practically, the findings highlight the urgency of structured professional development and policy alignment to sustain deep learning implementation at the foundational level of schooling.