Analysis of Teachers' Challenges in Implementing Deep Learning in High Schools: A Qualitative Study

Abstract

This study is driven by the imperative of 21st-century educational transformation, which necessitates deep learning approaches to foster students' critical thinking and profound comprehension. Despite its importance, applying deep learning pedagogies encounters multifaceted challenges in practice. Consequently, this research aims to analyze current deep learning implementation and identify the primary barriers educators face in schools. A descriptive qualitative methodology was employed, involving school principals and teachers as participants. Data were systematically gathered through in-depth interviews, classroom observations, and document analysis, and subsequently evaluated using data reduction, data display, and conclusion-drawing techniques. The findings reveal that while deep learning principles are being introduced through interactive discussions, reflective practices, and contextualized real-world learning, their implementation remains suboptimal. Significant constraints include inadequate information technology infrastructure, varied levels of student comprehension, overwhelming administrative burdens on teachers, and insufficient family support. Despite these hurdles, teachers demonstrate resilience by adapting innovative, context-specific instructional strategies. Ultimately, the successful institutionalization of deep learning relies heavily on educator readiness, comprehensive infrastructure support, and robust synergy among schools, families, and policymakers. This study contributes to the broader educational discourse by offering empirical insights into the pedagogical realities of deep learning and by providing actionable recommendations for stakeholders to elevate the quality of global teaching and learning environments.