Reimagining Post-Primary Computer Science Education in Ireland: Integrating AI, Machine Learning and Generative AI

This thesis investigates the integration of Artificial Intelligence (AI), Machine Learning (ML) and Generative AI (GenAI) in Computer Science (CS) education, with a particular emphasis on post-primary curricula, and the Irish Leaving Certificate Computer Science (LCCS) subject. The study is structured around three core research questions: (1) What is the current state of artificial intelligence and machine learning educational practice in post-primary education? (2) How can Generative AI be effectively integrated into introductory programming? and (3) How should artificial intelligence and machine learning content be appropriately strengthened in the Irish Leaving Certificate Computer Science curriculum? Using a mixed-methods approach, the research combines comparative curriculum analysis, literature synthesis, and empirical data from surveys and interviews with Irish post-primary CS teachers. A detailed curriculum mapping exercise benchmarks Irish and international AI/ML education practices against an AI framework developed by UNESCO. The findings reveal growing interest in AI education globally, yet highlight disparities in depth, pedagogy, and implementation across jurisdictions. Within Ireland, AI, ML and GenAI content remain underdeveloped in the formal curriculum, despite increasing relevance. The thesis introduces the TAM-AI-Edu framework (an adaptation of the Technology Acceptance Model) to analyse factors influencing teacher readiness and perceptions of AI integration. Teachers expressed both enthusiasm for AI/GenAI integration and concerns around training, assessment, and curriculum constraints. The study also presents structured guidelines for introducing GenAI into introductory programming, identifying pedagogical opportunities and risks, and mapping this against the LCCS curriculum to inform future redevelopment. This research contributes to the evolving field of AI and CS education by offering actionable recommendations for curriculum reform, teacher professional development, and ethical AI literacy. It aims to support a more future-oriented, inclusive, and pedagogically grounded integration of AI, ML, and GenAI into post-primary computing education.