AI usage and history students

The dataset was designed to explore the factors that most significantly influence the level of AI tool usage among history students at Jan Evangelista Purkyně University (UJEP) in their academic work. It directly addresses three core research questions:
- RQ1 investigates which perceptions, attitudes, and behavioral intentions shape AI tool usage.
- RQ2 examines the antecedent factors—such as demographic characteristics, digital literacy, and epistemic orientation—that may predict AI engagement.
- RQ3 probes whether frequent AI tool users represent a distinct subgroup, suggesting non-random selection into higher usage patterns.
The central variable, "AIFrequency", captures students’ self-reported frequency of AI tool use in study-related tasks. This is an ordinal variable measured on a 5-point Likert scale, ranging from 1 ("Never") to 5 ("Daily or Almost Daily"). This variable serves as the primary outcome measure, enabling analysis of usage intensity across different student profiles. The survey also includes items aligned with Technology Acceptance Models (TAM and VAM), covering constructs such as perceived usefulness, ease of use, trust, and intention to continue using AI tools. These constructs are operationalized through multiple Likert-scale items, allowing for both descriptive and inferential statistical analysis.
The dataset thus provides a rich foundation for examining not only how often students use AI tools, but also why they do so, and who is most likely to engage with them regularly.