A Q Methodology Study: Exploring Attitudes Toward “AI Hallucinations” in Human–AI Collaborative Academic Writing in Higher Education
Yupeng Guo, Tinglan Huang, Shengchen Yue, Jieting Yu, Mengwei Wei, Meifang Chen
Jiangxi Science and Technology Normal University Emilio Aguinaldo College
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摘要与影响
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.
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计算机 / AIArtificial Intelligence in Education
Q Methodology Applications · Educational Strategies and Epistemologies
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