Designing AI-Assisted Visual English Reading Instruction for Deaf Learners: Breaking Phonocentric Deadlock
Keywords:
phonocentric approach; AI-assisted reading instruction; Simple View of Reading; Visual Language and Visual Learning; Deaf LearnersAbstract
English reading instruction for Deaf Learners (DLs) is often influenced by phonocentric practices that prioritize sound-based pathways. Such practices may create barriers because DLs primarily access language through visual channels. This study investigated how special education teachers utilized generative AI to design visual-conceptual reading instruction and explored the trends observed in DLs’ reading comprehension scores during routine classroom evaluations. A multiple-case study design was employed involving 15 teachers from five institutions. Data were collected through interviews, artifact analysis, and three phases of reading comprehension evaluations. The qualitative data were analysed using pattern matching, while the quantitative data were analysed using descriptive statistics. The findings revealed a three-phase instructional design sequence consisting of text preparation, digital prompting, and artifact evaluation. Positive trends were also observed in DLs’ reading comprehension scores across the three evaluation phases overall. The average post-test scores consistently increased from Phase 1 to Phase 3 across the beginner (50.0 to 53.0), pre-intermediate (57.5 to 60.0), and intermediate (69.0 to 72.5) proficiency levels. Future studies in reading instruction should employ longitudinal or experimental designs with larger participant cohorts to further examine this AI-assisted model.
https://doi.org/10.26803/ijlter.25.9.43
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