Saudi Primary Teachers' Perceptions of Artificial Intelligence in Education: A Qualitative Investigation Through the TPACK-C Framework

Abstract

Saudi Arabia's Vision 2030 identifies education as the principal driver of economic diversification and situates the Human Capability Development Program at the core of workforce preparation. Notwithstanding these ambitions, the 2018 PISA cycle showed that more than 50 percent of Saudi learners failed to attain minimum reading proficiency. The COVID-19 crisis subsequently demonstrated the system's capacity for rapid digital adaptation, characterised by agility and innovation. In this milieu, artificial intelligence has shifted from peripheral curiosity to policy imperative.

No published study has yet employed the Technological Pedagogical Content Knowledge-Contextualised (TPACK-C) model enriched with Islamic constructs to investigate Saudi primary classrooms. This qualitative study explores five primary teachers' AI perceptions through TPACK-C, TAM, and SDT frameworks. Semi-structured Arabic interviews with teachers from diverse infrastructural contexts were analyzed using reflexive thematic analysis, revealing six key themes: instructional-efficiency catalyst, the infrastructure divide, variable student digital readiness, professional identity re-negotiation, fragmented professional learning, and the necessity of ethical-cultural safeguarding. Findings reveal a novel Threshold-Trajectory Model requiring sequential progression through digital-infrastructure, competency development, and ethical-cultural alignment phases. Results extend TPACK-C with Student Technological Knowledge (STK) and a culturally specific Ethical Knowledge domain, while providing actionable recommendations supporting Vision 2030 objectives.