Generative AI for Early Literacy Development: A Quasi-Experimental Study in Preschool Settings
Keywords:
Early childhood education, Early literacy, Generative AI, Narrative comprehension, Vocabulary developmentAbstract
This quasi-experimental study examines the effectiveness of generative artificial intelligence (AI) in supporting early literacy development among preschool children. Fifty‑two children (N = 52) from two intact classes were assigned to an experimental group receiving AI‑generated story‑based literacy activities and a control group using conventional picture books. Data were collected using validated measures: a vocabulary test (Cronbach’s α = .81), a narrative comprehension test (Cronbach’s α = .78), an observational engagement rubric, and a teacher perception questionnaire. Paired t‑tests and ANCOVA (controlling for pretest scores) show that the AI group showed substantial vocabulary gains (pretest M = 23.15; posttest M = 31.42; Cohen’s d = 2.21) and narrative comprehension (pretest M = 9.35; posttest M = 13.92; Cohen’s d = 2.07). ANCOVA results remained significant for vocabulary (F(1,49) = 18.74, p < .001) and comprehension (F(1,49) = 15.92, p < .001). Teachers reported increased engagement and usefulness for differentiated instruction, while noting concerns about ease of use, screen time, and content moderation. The study demonstrates that responsibly integrated generative AI can substantially enhance early literacy outcomes in resource‑adequate preschool settings. Implications include teacher capacity building, clear ethical guidelines for child‑safe AI use, and further research on long‑term effects and diverse educational contexts..
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