The process of lesson planning using generative artificial intelligence: a study based on the TRACK model and UNESCO's competency framework

Abstract

The article discusses one of the key problems of modern pedagogical practice – the difficulties teachers face when formulating lesson objectives. Based on data from a survey of 300 schools conducted by the I. Altynsarin NAE (2023), in which 22% of teachers indicated difficulties with goal setting, the article explores the potential of large language models (LLMs) as a tool for optimizing this stage of planning. A structured algorithm for using the Google Gemini model to generate lesson objectives, descriptors, and learning tasks is proposed and described. The effectiveness and risks of this approach are analyzed through the lens of the TRASC (Technological Pedagogical Content Knowledge) theoretical framework and the UNESCO Artificial Intelligence Competency Framework for Educators. The article argues that AI can serve as a tool for educators, reducing the cognitive load in routine stages and freeing up resources for creative and analytical aspects of teaching. However, its effective integration requires educators to develop new competencies related to the critical evaluation of generated content and its adaptation to unique pedagogical contexts.