Evidence map›Paper›PMID 40417040›Full record

ArticleFrontiers in psychology2025

Navigating cognitive dissonance: master's students' experiences with ChatGPT in dissertation writing.

Xiaobin Ren, Wenwen Zheng, Min Zhang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiaobin RenSchool of Foreign Languages, Guangxi University, Nanning, China.
Wenwen ZhengSchool of Foreign Languages, Guangxi University, Nanning, China.
Min ZhangSchool of Foreign Languages, Guangxi University, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing prevalence of AI tools like ChatGPT in academic settings, understanding their impact on students' psychological experiences during dissertation writing is crucial. This study aims to explore the cognitive dissonance experienced by master's students during dissertation writing with the assistance of ChatGPT and identify the strategies they employ to manage this dissonance. Using grounded theory as the primary research methodology, we analyzed 28 interview transcripts to uncover key elements of cognitive dissonance and develop a corresponding theoretical model. Our findings revealed that the primary sources of cognitive dissonance among master's students were the strong intentions to use ChatGPT driven by subjective norms and technological expectations, conflicting with the reality of multiple choices. To alleviate this cognitive dissonance, students adopted strategies such as improving prompt quality, feeding relevant domain-specific data to the AI, avoiding academic misconduct, and maintaining academic integrity. This study challenged and extended the Technology Acceptance Model and the Theory of Planned Behavior by incorporating cognitive dissonance, and emphasized the underlying pathways and causes of dissonance. Practically, our findings offer significant implications for institutions and educators, emphasizing the importance of supporting and guiding the use of generative AI tools like ChatGPT in dissertation writing.

Indexed as

ChatGPTcognitive dissonancedissertation writinggrounded theorynavigating strategies

Identifiers

PMID40417040
PMCPMC12098579

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.