Russian Federation
The article presents the development and rationale of a teaching technology designed to train future special education teachers (defectologists) to design instructional elements within the Moscow Electronic School (MES) platform using artificial intelligence tools. At the diagnostic stage, a survey of 217 pre‑service teachers revealed a gap between the high level of personal use of generative AI and its considerably lower professional application in working with children, as well as three barrier groups — access, trust and competence barriers — that hinder the integration of AI into teaching practice. Based on these findings, a five‑stage teaching technology was developed and implemented within an elective course on MES resources, comprising demonstration‑analytical, instrumental‑technological, productive‑practical, methodological‑integration and reflective‑expert stages. The article describes the content of the theoretical part of the course (basic AI concepts, ethical and legal issues, overview of AI services, fundamentals of prompt engineering) and the practical work of students on generating, adapting and integrating learning materials into MES lesson scenarios for students with special educational needs. Expert evaluation of the resulting lesson scenarios indicated qualitative improvements in methodological justification, students’ critical attitude towards AI-generated outputs, and their readiness to use generative tools in an informed way.
teaching technology, teacher training, future defectologists (pre-service special education teachers), artificial intelligence in education, Moscow Electronic School (MES), digital teacher competencies, students with disabilities
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