Keywords
critical thinking
public humanities education
AI ethics
source evaluation
cultural bias
quasi-experimental study
Abstract
This study examines whether generative AI literacy training can improve critical thinking development in public humanities education. The study is designed as a quasi-experimental intervention involving approximately 480 learners from 12 public humanities courses, with 240 students in the experimental group and 240 students in the control group. The experimental group receives an eight-week AI literacy module covering AI-generated text recognition, image-generation ethics, prompt evaluation, source verification, bias identification, authorship judgment, and cultural representation analysis. The study collects pre-test and post-test data, including AI literacy scores, critical thinking rubric scores, source-evaluation accuracy, bias-identification accuracy, ethical reasoning scores, reflective writing scores, and scenario-based judgment scores. Quantitative analysis uses paired-sample t-tests, ANCOVA, multiple regression, structural equation modeling, and mediation analysis to examine whether AI literacy improves critical thinking directly or through digital judgment, ethical awareness, and source-evaluation ability. Qualitative coding of approximately 960 reflective responses is used to identify changes in students’ understanding of originality, cultural bias, and responsible AI use. The study’s innovation lies in moving generative AI education beyond tool-use training and linking it with measurable humanities learning outcomes, especially critical thinking, ethical reasoning, and cultural interpretation.
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