AI enhanced inquiry based learning for English language development in a dyslexic learner a mixed methods case study from Lebanon

Despite increasing global interest in Artificial Intelligence (AI) in education, little research has examined how AI tools such as ChatGPT can function as scaffolds within inquiry-based learning (IBL) frameworks for learners with dyslexia, particularly in under-researched contexts such as Lebanon. This mixed-methods case study investigates how AI-enhanced IBL aligns with changes in English language development and 21st-century skills in one 10-year-old dyslexic learner over an academic year. The intervention integrated ChatGPT (GPT-4) within a structured IBL cycle across three progressive phases. Quantitative data included naturally occurring school grades and weekly assessments; qualitative data included interviews, observation logs, and reflective accounts. Results indicate sustained improvements in grammar, reading, composition, and participation, alongside increased autonomy and confidence. Vocabulary development showed plateau effects, highlighting the limits of AI support without structured retrieval practice. While findings are associative rather than causal due to the single-case design, the study demonstrates the feasibility of moderated AI scaffolding within IBL for dyslexic learners. It contributes preliminary evidence for inclusive AI-assisted pedagogy in Lebanon and informs future controlled investigations.