USE OF ARTIFICIAL INTELLIGENCE BY TEACHERS FOR SCHOOL TASKS: AN APPLICABLE FRAMEWORK FOR TEACHER TRAINING

Abstract

Artificial Intelligence (AI), specifically Generative AI, is rapidly gaining integration into teachers' daily life, such as lesson planning, creation, differentiation, feedback and assessment, family communication and information analysis. This paper is a critical review of the developing evidence of those uses and proposes a useful framework for teacher training. The best conclusion is that AI can enhance teaching and pupil outcomes, rather than that it reliably does these things; there is not enough direct evidence to back up these claims. Instead, the evidence suggests a more specific conclusion: Task-anchored professional learning with structured scaffolding can enhance teachers' AI literacy, confidence, and the quality of AI-supported planning artefacts, particularly when it integrates technical foundations, pedagogical design, ethical reflection, guided practice, and reflection. The current theories have varying contributions. Neither a Technology-acceptance model, which is capable of answering the question of whether teachers will use tools, nor a TPACK-derived model, which is capable of explaining the professional knowledge teachers require to use the tools pedagogically, is sufficient without a human-centred governance and agency perspective. The proposed framework thus positions AI as a co-designed professional practice, rather than a topic for training in the use of tools. It is a process that unfolds from context to foundation, design, proof, classroom performance and evidence of competence, with institutional protection measures at its core. Further research is needed to determine whether such programmes have an impact on observed instruction, the validity of assessment, equity, workload and pupil learning over time.