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'Cognitive Co-Pilot' or 'Ghostwriter'?--The Usage Mechanism and Adjustment Strategies of Learners for Generative AI in Academic Research

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Title: 'Cognitive Co-Pilot' or 'Ghostwriter'?--The Usage Mechanism and Adjustment Strategies of Learners for Generative AI in Academic Research
Language: English
Authors: Hao Yu (ORCID 0009-0001-8044-1775), Huajun Zhang (ORCID 0009-0001-4324-9223), Yan Dong (ORCID 0000-0003-1678-6370)
Source: European Journal of Education. 2026 61(2).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 15
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Influence of Technology, Undergraduate Students, Graduate Students, Computer Attitudes, Educational Benefits, Student Research, Ethics, Computer Assisted Instruction
DOI: 10.1111/ejed.70563
ISSN: 0141-8211
1465-3435
Abstract: Generative Artificial Intelligence (GenAI) has rapidly penetrated academic research, with both advantages such as efficiency improvement and cognitive supplementation, as well as challenges such as inaccurate content and ethical risks, triggering a positioning controversy between "cognitive co-pilot" and "ghostwriter". Existing research lacks exploration of the usage mechanism to address this positioning controversy from the learner's perspective. This study adopted a qualitative research method based on grounded theory, conducted semi-structured interviews with 18 learners covering educational levels from undergraduate to doctoral degrees and multiple disciplinary fields, and performed four-level coding analysis combined with NVivo software. The results show that learners are driven by the advantages of efficiency perception, cognitive supplementation, and academic need matching, face constraints from technical limitations, low disciplinary adaptability, ethical risks, and cognitive dependence, and achieve adjustment through strategies of tool optimisation, content validation, and cognitive reconstruction. Finally, this study constructs a usage mechanism of "advantage-driven--dilemma-constraining--adjustment strategies", and condenses five essential modes of existence of GenAI in academic research, namely tool-based, differentiated, contradictory, fluid, and reflective, combined with the characteristics of cognitive and usage patterns. This study fills the limitation of existing research that emphasises technology over users, and provides empirical evidence for learners to use GenAI while adhering to subjectivity and academic ethics, for differentiated guidance by educators, and for developers to optimise disciplinary adaptability.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506878
Database: ERIC
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  Data: 'Cognitive Co-Pilot' or 'Ghostwriter'?--The Usage Mechanism and Adjustment Strategies of Learners for Generative AI in Academic Research
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  Data: <searchLink fieldCode="AR" term="%22Hao+Yu%22">Hao Yu</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0001-8044-1775">0009-0001-8044-1775</externalLink>)<br /><searchLink fieldCode="AR" term="%22Huajun+Zhang%22">Huajun Zhang</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0001-4324-9223">0009-0001-4324-9223</externalLink>)<br /><searchLink fieldCode="AR" term="%22Yan+Dong%22">Yan Dong</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1678-6370">0000-0003-1678-6370</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22European+Journal+of+Education%22"><i>European Journal of Education</i></searchLink>. 2026 61(2).
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: 15
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  Data: 10.1111/ejed.70563
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  Data: 0141-8211<br />1465-3435
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Generative Artificial Intelligence (GenAI) has rapidly penetrated academic research, with both advantages such as efficiency improvement and cognitive supplementation, as well as challenges such as inaccurate content and ethical risks, triggering a positioning controversy between "cognitive co-pilot" and "ghostwriter". Existing research lacks exploration of the usage mechanism to address this positioning controversy from the learner's perspective. This study adopted a qualitative research method based on grounded theory, conducted semi-structured interviews with 18 learners covering educational levels from undergraduate to doctoral degrees and multiple disciplinary fields, and performed four-level coding analysis combined with NVivo software. The results show that learners are driven by the advantages of efficiency perception, cognitive supplementation, and academic need matching, face constraints from technical limitations, low disciplinary adaptability, ethical risks, and cognitive dependence, and achieve adjustment through strategies of tool optimisation, content validation, and cognitive reconstruction. Finally, this study constructs a usage mechanism of "advantage-driven--dilemma-constraining--adjustment strategies", and condenses five essential modes of existence of GenAI in academic research, namely tool-based, differentiated, contradictory, fluid, and reflective, combined with the characteristics of cognitive and usage patterns. This study fills the limitation of existing research that emphasises technology over users, and provides empirical evidence for learners to use GenAI while adhering to subjectivity and academic ethics, for differentiated guidance by educators, and for developers to optimise disciplinary adaptability.
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