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Disciplinary and Educational Level Differences in AI-Mediated Informal Digital Learning of English (AI-IDLE): A Qualitative Epistemic Network Analysis

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Title: Disciplinary and Educational Level Differences in AI-Mediated Informal Digital Learning of English (AI-IDLE): A Qualitative Epistemic Network Analysis
Language: English
Authors: Chenghao Wang (ORCID 0009-0009-5655-3740), Lanfang Sun (ORCID 0000-0002-3990-7051), Jiahao Yan, Bin Zou (ORCID 0000-0002-4863-0998)
Source: Journal of Computer Assisted Learning. 2026 42(3).
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: 18
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Electronic Learning, English (Second Language), Student Attitudes, Undergraduate Students, Graduate Students, Doctoral Students, Intellectual Disciplines, Grade Level Differences, Foreign Countries, Informal Education
Geographic Terms: China
DOI: 10.1002/jcal.70244
ISSN: 0266-4909
1365-2729
Abstract: Background: As generative artificial intelligence (GenAI) becomes more deeply integrated into AI-mediated informal digital learning of English (AI-IDLE), understanding how learners organise their acceptance of these tools is increasingly important. Existing research has largely relied on variable-centred approaches, offering limited insight into how acceptance beliefs are configured across learner groups. Objectives: This study examines how learners' acceptance of GenAI beyond the classroom is structurally organised and how these configurations vary across educational levels and disciplinary backgrounds. Methods: Grounded in the Integrated Model of Technology Acceptance (IMTA), the study employed Epistemic Network Analysis (ENA) to model four acceptance networks: overall IMTA, perceived enjoyment (PE), perceived usefulness (PU) and negative use experience. Semi-structured online interviews were conducted with 24 Chinese university students (BA, MA, PhD; humanities and social sciences, STEM) and theory-driven coding was used to construct and compare network structures. Results and Conclusions: Findings revealed a developmental reconfiguration of acceptance. BA learners' IMTA networks were experience-oriented (PE, PEU), whereas postgraduate learners showed more utility-driven configurations integrating PU and behavioural intention. PE networks showed disciplinary differences and some developmental variation, shifting from accompaniment-centred structures towards confidence-oriented patterns. PU displayed the clearest educational differentiation, progressing from affordance-based evaluations to goal-aligned and critically engaged use. In contrast, negative-use networks showed structural stability across educational levels but differed by discipline. Overall, GenAI acceptance in AI-IDLE emerges as a developmentally structured and motivationally layered process rather than a static set of beliefs.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506865
Database: ERIC
FullText Text:
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  Data: Disciplinary and Educational Level Differences in AI-Mediated Informal Digital Learning of English (AI-IDLE): A Qualitative Epistemic Network Analysis
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Chenghao+Wang%22">Chenghao Wang</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0009-5655-3740">0009-0009-5655-3740</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lanfang+Sun%22">Lanfang Sun</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-3990-7051">0000-0002-3990-7051</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jiahao+Yan%22">Jiahao Yan</searchLink><br /><searchLink fieldCode="AR" term="%22Bin+Zou%22">Bin Zou</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4863-0998">0000-0002-4863-0998</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Computer+Assisted+Learning%22"><i>Journal of Computer Assisted Learning</i></searchLink>. 2026 42(3).
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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: Y
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  Data: 18
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  Data: 2026
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22English+%28Second+Language%29%22">English (Second Language)</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Graduate+Students%22">Graduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Doctoral+Students%22">Doctoral Students</searchLink><br /><searchLink fieldCode="DE" term="%22Intellectual+Disciplines%22">Intellectual Disciplines</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+Level+Differences%22">Grade Level Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Informal+Education%22">Informal Education</searchLink>
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  Label: Geographic Terms
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/jcal.70244
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0266-4909<br />1365-2729
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: As generative artificial intelligence (GenAI) becomes more deeply integrated into AI-mediated informal digital learning of English (AI-IDLE), understanding how learners organise their acceptance of these tools is increasingly important. Existing research has largely relied on variable-centred approaches, offering limited insight into how acceptance beliefs are configured across learner groups. Objectives: This study examines how learners' acceptance of GenAI beyond the classroom is structurally organised and how these configurations vary across educational levels and disciplinary backgrounds. Methods: Grounded in the Integrated Model of Technology Acceptance (IMTA), the study employed Epistemic Network Analysis (ENA) to model four acceptance networks: overall IMTA, perceived enjoyment (PE), perceived usefulness (PU) and negative use experience. Semi-structured online interviews were conducted with 24 Chinese university students (BA, MA, PhD; humanities and social sciences, STEM) and theory-driven coding was used to construct and compare network structures. Results and Conclusions: Findings revealed a developmental reconfiguration of acceptance. BA learners' IMTA networks were experience-oriented (PE, PEU), whereas postgraduate learners showed more utility-driven configurations integrating PU and behavioural intention. PE networks showed disciplinary differences and some developmental variation, shifting from accompaniment-centred structures towards confidence-oriented patterns. PU displayed the clearest educational differentiation, progressing from affordance-based evaluations to goal-aligned and critically engaged use. In contrast, negative-use networks showed structural stability across educational levels but differed by discipline. Overall, GenAI acceptance in AI-IDLE emerges as a developmentally structured and motivationally layered process rather than a static set of beliefs.
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  Data: 2026
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  Data: EJ1506865
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      – SubjectFull: Artificial Intelligence
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      – SubjectFull: Electronic Learning
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      – SubjectFull: English (Second Language)
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      – SubjectFull: China
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