A TPACK-Based Framework for Integrating Robotics and AI in STEM Education: Development and Validation through Mixed Methods

Abstract

The rapid advancement of robotics and artificial intelligence (AI) has reshaped the educational landscape, particularly within Science, Technology, Engineering, and Mathematics (STEM) disciplines. While these technologies hold promise for enhancing computational thinking, problem-solving, creativity, and collaboration, their integration in classrooms has often remained fragmented due to limited teacher preparedness, resource constraints, and inadequate pedagogical frameworks. This study developed and validated a Technological Pedagogical Content Knowledge (TPACK)-based framework to guide the effective incorporation of robotics and AI in STEM education. A mixed-methods exploratory sequential design was employed, combining qualitative data from interviews and classroom observations with quantitative insights from large-scale teacher surveys and student assessments. The framework was empirically tested to evaluate its impact on both teaching practices and student learning outcomes. Findings provided a comprehensive understanding of teachers’ TPACK levels, established a validated integration framework, and generated actionable recommendations for professional development and policy. The study advanced theoretical discourse on TPACK in the digital era while offering practical guidance for educators and policymakers to promote meaningful adoption of robotics and AI in STEM classrooms.