<![CDATA[This study addresses the growing demand for deep learning-oriented instruction in 21st-century education, particularly in special education, where instructional practices involve high levels of complexity. The study aims to analyze the determinants of deep learning oriented teaching behavior among special education teachers using the Theory of Planned Behavior (TPB). A quantitative explanatory survey design was employed, involving 66 teachers selected through snowball sampling. Data were collected using a structured questionnaire and analyzed through hierarchical multiple regression. The results indicate that perceived behavioral control (PBC) and subjective norm (SN) significantly predict both intention and teaching behavior, while attitude toward behavior (ATB) does not show a significant effect when controlling for other variables. Intention significantly predicts behavior; however, its additional contribution is relatively small (ΔR² = 0.013), indicating that behavioral implementation is influenced not only by intention but also by professional competence and environmental factors. Overall, the model demonstrates strong explanatory power, highlighting the importance of teacher capability and social support in facilitating the implementation of deep learning-oriented instruction in special education. This study contributes theoretically by strengthening the validity of TPB in special education while offering a new perspective that the transformation of teaching behavior is more strongly influenced by structural support, professional competence, and institutional expectations than by personal attitudes alone. Therefore, this study underscores that the successful implementation of deep learning in special education requires a systemic approach integrating psychological readiness, teacher competency development, and institutional support to promote inclusive, meaningful, adaptive, and sustainable learning that enhances students higher order thinking skills.]]>
