Survey Dataset on AI Framing, Role, and Ethical Compliance among Students and Educators
Description
This dataset contains survey responses collected to investigate the influence of artificial intelligence (AI) advice framing, accountability, and normative alignment on human decision-making, ethical judgments, and behavioral responses in higher education contexts. The study employs a vignette-based experimental approach to examine how individuals evaluate and respond to AI-generated recommendations across academic and ethical decision-making scenarios. The dataset incorporates experimental conditions involving AI advice framing, accountability levels, and the alignment of AI recommendations with established norms. Participants evaluated hypothetical scenarios involving academic activities, including assignment writing and the use of citations and sources. Their responses capture varying levels of compliance with AI recommendations, perceived moral acceptability, ethical justification, and responsibility attribution. The dataset includes measures of behavioral intention and ethical evaluation, such as compliance with AI recommendations, moral acceptability, ethical justification, perceived responsibility, and decision confidence. Emotional responses, including guilt, shame, outrage, and anxiety, are also recorded to examine the affective dimensions of AI-assisted decision-making. Additional measures assess participants' willingness to recommend decisions to peers and their perceptions of AI agency and accountability. Information on participants' AI usage frequency, comfort with AI technologies, AI-related knowledge, and previous AI training is included to support investigations into the relationship between AI familiarity and ethical decision-making. Demographic and academic characteristics, including age, gender, academic discipline, educational level, professional experience, and institutional role, are also provided. This dataset may support research in human–AI interaction, responsible artificial intelligence, educational technology, AI ethics, behavioral compliance, moral psychology, and accountability in AI-assisted decision-making. It can also facilitate comparative investigations of how AI advice presentation and accountability conditions influence ethical judgments, responsibility attribution, and behavioral responses across different academic scenarios. The dataset provides a resource for researchers examining the behavioral, cognitive, and affective implications of AI-supported decision-making in higher education.