Generative AI and media literacy: how AI tools reshape students’ skills of searching, verifying, and interpreting information

Generative artificial intelligence (GenAI) is increasingly used as an “answer engine” in higher education, raising risks of plausibility replacing verifiability. This study tested whether a semester-long GenAI media literacy module improves undergraduates’ procedural skills of searching, verifying, and interpreting AI-mediated information. Using a quasi-experimental non-equivalent groups pretest–posttest design (T0–T1), we compared two cohorts from L.N. Gumilyov Eurasian National University and Astana International University in Astana, Kazakhstan (N = 135; EG n = 70; CG n = 65). The experimental group completed a 13-week module emphasising primary-source retrieval, lateral reading, evidential reasoning, and responsible attribution; the control group followed the standard curriculum. Outcomes included the 15-item GenAI Media Literacy Questionnaire (GMLQ; 1–7) and a performance task requiring verification of three GenAI-generated claims scored with a rubric (0–27). ANCOVA models adjusted for baseline scores and covariates (age, gender, language of instruction, GPA, baseline GenAI-use frequency) showed a post-test advantage for the experimental group: adjusted EG–CG differences were +0.63 on GMLQ total and +4.67 on performance. Positive effects were consistent across GMLQ subscales and performance components (Search, Verify, Interpret). The findings support embedding sustained, procedure-focused GenAI media literacy instruction in pre-service teacher education to strengthen evidence-based practices.