This study investigates the subjective perspectives and evaluative orientations of university students when navigating AI hallucinations during human–AI collaborative writing and offers empirical material for formulating tentative, data-informed pedagogical hypotheses concerning different patterns of epistemic and cognitive support in AI-assisted academic writing.
Abstract
While generative artificial intelligence (GenAI) is increasingly integrated into higher education academic writing, it introduces profound epistemic challenges such as AI hallucinations, including fabricated citations and data. Current literature predominantly focuses on macro-level technology acceptance, leaving students’ micro-level subjective perspectives relatively underexplored. This study investigates the subjective perspectives and evaluative orientations of university students when navigating AI hallucinations during human–AI collaborative writing. Employing Q methodology structurally anchored in the Cognitive Process Theory of Writing, 45 humanities and social science students prioritized a refined set of 40 statements. Quantitative factor analysis complemented by qualitative post-sort interviews identified five factor-defined perspectives: Autonomous Directors, Pragmatic Operators, Epistemic Sentinels, Conflicted Compromisers, and Creative Opportunists. These perspectives reflect shared configurations of epistemic trust, authorship control, and verification responsibility, which are interpreted in relation to cognitive agency rather than treated as separately measured constructs or fixed categories of students. The findings offer empirical material for formulating tentative, data-informed pedagogical hypotheses concerning different patterns of epistemic and cognitive support in AI-assisted academic writing; these hypotheses require validation through future intervention-based research.
The study investigates the lived experience of Iranian EFL university students navigating high-stakes academic writing assessment in a context where GenAI tools are widely available yet institutionally unregulated and proposes three principles for human-centered assessment design—transparency, integration, and relation...
Zahra Mirsanjari· Language Testing in Asia· 0 citations
A structured survey of AI hallucinations, synthesizing prior research to clarify their evolving definitions, underlying causes, and implications for Information Systems positions AI hallucinations as socio-technical phenomena with direct implications for trust, decision-making, and governance.
How educators working in Dutch academic medical settings perceive GenAI’s implications for students’ critical thinking and how they believe it should be integrated into medical curricula is explored are explored.
This exploratory mixed-method pilot study investigated students’ experiences with artificial intelligence (AI)-guided assignments across selected humanities, design, and STEM courses in higher education during the academic term beginning in August/September 2024. Using a custom survey tool grounded in Bloom’s taxonomy,...
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The rapid expansion of artificial intelligence tools in higher education demands understanding whether students' moral development is associated with more responsible AI use. Moral development, conceptualized through Kohlberg's stage theory, provides a theoretically grounded framework for examining this relationshi...
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Preliminary psychometric evidence is provided for a proposed multidimensional human disposition relevant to behavioral research on human–AI interaction; confirmatory, behavioral, and cross-context validation remains necessary.
S. J. Kang, Juyoung Lee, Seong-Joo Kang· Behavioral Science· 0 citations
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