A TPACK-Assisted Descriptive Analysis of the Sri Lankan ICT Teachers’ Readiness to Teach AI in Schools

The integration of Artificial Intelligence (AI) into school curricula is a growing global initiative. While significant research addresses AI content and pedagogy, a pervasive challenge is ensuring the teaching workforce is adequately prepared to implement these curricula effectively. This paper addresses this crucial gap within the Sri Lankan context, investigating two primary issues: 1) the knowledge gaps—technical, pedagogical, and content—between curriculum stipulations and in-service teacher competencies, and 2) how teachers’ background variables contribute to these knowledge deficits. Employing a descriptive analysis of a secondary dataset mapped to the Technological, Pedagogical, and Content Knowledge (TPACK) framework, this study reveals three key findings. Firstly, Sri Lankan ICT teachers exhibit significant deficiencies across all three knowledge domains. Secondly, the deficit in content knowledge is substantially more pronounced compared to the other two areas. Finally, results indicate that female teachers possess considerably lower knowledge levels than their male counterparts, suggesting a critical need for more personalised attention within future teacher development programs. These findings offer crucial and actionable insights for policymakers and teacher educators responsible for designing professional development initiatives. The study particularly recommends adopting the systems thinking approach for the teacher professional development initiatives.