Does low confidence drive reliance on AI, or does reliance erode confidence? A four-wave RI-CLPM study of chinese language and literature undergraduates

Xinran Du and Sedan Yu

PLOS ONE, 2026, vol. 21, issue 10, 1-22

Abstract: Generative AI tools are now routinely used by Chinese Language and Literature majors for tasks once considered the province of individual literary craft: drafting verse, shaping narrative prose, revising fiction. Two competing accounts describe what this means for students’ confidence in their own creative writing. A cognitive-offloading account holds that repeated reliance on AI displaces the mastery experiences through which writing self-efficacy is built, so reliance erodes confidence over time. A compensatory-use account holds the reverse: students whose confidence is already low turn to AI to avoid the discomfort of unassisted composition, so low confidence drives reliance. Cross-sectional and standard cross-lagged designs cannot separate these accounts because they confound stable between-person differences with genuine within-person change. We addressed this using a random-intercept cross-lagged panel model (RI-CLPM) across four waves spanning one academic year among Chinese Language and Literature undergraduates (N = 390 recruited; N = 387 analyzed under full-information maximum likelihood, of whom 298 supplied complete four-wave data). Generative AI writing reliance (GAWR) and literary creative writing self-efficacy (LCWSE) were assessed at each wave. The trait-level association between the two constructs was negative and could not be distinguished from zero (r = −.342, Δχ²(1) = 2.26, p = .133). At the within-person level, declines in self-efficacy predicted subsequent increases in reliance (β = −.276, p

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0361489

DOI: 10.1371/journal.pone.0361489

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