AI-Supported Scaffold Design for Lower-Proficiency EFL Learners: Experiences of Pre-Service Teachers in Inclusive Reading Instruction
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https://doi.org/10.52296/vje.2026.912-
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Abstract
Teaching reading in mixed-ability EFL classrooms remains challenging as lower-proficiency learners struggle with grade-level texts. Although scaffolding is widely acknowledged as a strategy for greater accessibility and participation, designing effective scaffolds can be demanding to novice teachers. The growing availability of generative artificial intelligence (AI) offers new possibilities to support teachers throughout this process. Despite growing research on AI in language education, little has been known about how pre-service teachers employ AI to design scaffolds for inclusive reading instruction during their teaching practicum. This study explored how pre-service teachers (PSTs) utilized AI to design scaffolding materials for lower-proficiency learners during reading lessons. A qualitative research design was employed involving seven PSTs and 22 lower-proficiency secondary school learners across an eight-week teaching practicum. Data were collected via lesson plans, scaffold artifacts, reflective journals, and semi-structured interviews before being thematically analysed. Results indicated that PSTs use AI to create lexical, procedural, conceptual, and affective scaffolds that reduce barriers to reading engagement. Learners reported higher levels of behavioral, emotional, and cognitive engagement, including greater participation, confidence, and use of reading strategies. AI was considered as a valuable source of pedagogical assistance although participants noted the need to adapt AI-produced materials to better suit learners and classroom contexts. The study also suggests that AI is a teacher-facing tool for inclusive reading instruction and PSTs preparation.
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