A UDL- and UDT-Informed Content Analysis of Instructional Quality in AI-Generated EFL Lesson Plans

کد مقاله : 1145-ELTCONF7. (R1)

نویسندگان

فاطمه خواجوند نوراشرفی *، شقایق درویشی، مریم فکری قره کند دانشگاه ارومیه

چکیده مقاله

While lesson planning is central to effective instruction, it is often time-consuming for teachers, creating a need for efficient alternatives. This study aimed to examine whether AI-generated lesson plans promote equal instructional features in English as a Foreign Language (EFL) classrooms by assessing their alignment with the Universal Design for Learning (UDL) and Universal Design for Transition (UDT) principles. Using a qualitative directed content analysis, the present study evaluated 18 ChatGPT-generated lesson plans across grammar, vocabulary, reading, writing, listening, and speaking. Each lesson plan was assessed using a UDL/UDT-based rubric covering seven dimensions: engagement, representation, expression, transition domain, assessment, self-determination, and resources/perspectives. The findings revealed partial alignment of AI-generated lesson plans with UDL/UDT principles. Moderate alignment was observed in engagement, representation, transition domain, and resources/perspectives, providing structured and culturally relevant content. Conversely, expression, assessment, and self-determination demonstrated weaker alignment, limiting opportunities for learner autonomy, formative assessment, and creative output. These findings suggest that AI-generated lesson plans can serve as a time-saving foundation but still require teacher customization. The study concludes that while AI-generated lesson plans can reduce teachers’ workload, pedagogical refinement is necessary to ensure effective instructional design.

کلیدواژه ها

AI-generated lesson plans, Instructional quality, UDL/UDT principles, Alignment

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