Epistemic Cultures and AI Adoption in History Education: A Conceptual Framework with an Exploratory Czech Case Study

Abstract

The rapid diffusion of generative artificial intelligence (AI) in higher education has generated intense debate about its implications for disciplinary norms, digital competencies, and epistemic practices. While existing research draws heavily on technology-acceptance models, the unique epistemic culture of history – characterized by source criticism, contextual reasoning, and interpretive rigor – remains insufficiently theorized in AI-adoption studies. This paper develops a conceptual framework that integrates technology acceptance theory, digital literacy, and epistemic-culture perspectives to explain why humanities students adopt AI selectively rather than uniformly. We argue that meaningful AI engagement in history depends not only on perceived usefulness or ease of use but also on alignment with disciplinary epistemic actions such as verification and interpretive judgment. To illustrate the framework, we draw on an exploratory case study of history students at a Czech regional university ( n  = 120). The case is not designed to ensure statistical representativeness; rather, it serves both as an illustrative application of the proposed model in an authentic educational setting and as a comprehensive methodological demonstration, grounded in a piloted questionnaire and rigorous statistical procedures. Descriptive patterns and exploratory modeling reveal a consistent differentiation between epistemically aligned AI uses (e.g., data verification, annotation) and functions perceived as unreliable or misaligned with disciplinary norms (e.g., audio transcription, media generation). These empirical insights serve to validate and nuance the conceptual model. We conclude by outlining methodological recommendations for future large-scale population studies and by proposing a research agenda for conceptual, empirical, and comparative investigations of AI adoption across humanities disciplines.