AI Literacy Development in an AI-Augmented Developmental Psychology Course: A Longitudinal Learning Analytics Study

Abstract

The rapid integration of generative artificial intelligence (AI) into higher education has highlighted the importance of developing students’ AI literacy. However, limited empirical research has examined how AI literacy evolves through authentic learning processes. This study examines the longitudinal development of AI literacy in an AI-augmented developmental psychology course, employing a learning analytics approach. Repeated measurements were collected across a semester and analyzed using Generalized Estimating Equations (GEE). AI literacy was assessed across five dimensions: technical proficiency, critical evaluation, communication proficiency, creative application, and ethical awareness. Results revealed significant improvements across all five dimensions (all p < .001), indicating a consistent upward trajectory. The findings suggest that AI literacy develops progressively through iterative human–AI interaction, particularly through cycles of prompting, evaluation, and revision embedded in digital storytelling tasks. This study demonstrates how longitudinal learning analytics can capture the developmental trajectories of AI-related competencies in authentic educational contexts.