View in EDS

A Correlational Study of AI Usage, Motivation, Self-Efficacy, and Learning Engagement in Education: Based on Expectancy-Value Theory

Saved in:
Bibliographic Details
Title: A Correlational Study of AI Usage, Motivation, Self-Efficacy, and Learning Engagement in Education: Based on Expectancy-Value Theory
Language: English
Authors: Qi Chai (ORCID 0009-0006-1721-3100)
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: 12
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Correlation, Artificial Intelligence, Self Efficacy, Learner Engagement, Second Language Learning, English (Second Language), Learning Motivation, Student Motivation, Foreign Countries, Technology Uses in Education, Influence of Technology, Psychological Patterns, Emotional Response
Geographic Terms: China
DOI: 10.1111/ejed.70633
ISSN: 0141-8211
1465-3435
Abstract: The rapid integration of artificial intelligence (AI) tools into educational settings has reshaped language learning practices; however, empirical evidence explaining how AI usage interacts with learners' motivational beliefs and self-perceptions to influence engagement and enjoyment remains limited, particularly in EFL contexts. Although prior studies have examined technology adoption or learner motivation separately, few have situated AI-assisted learning within a comprehensive motivational framework such as Expectancy-Value Theory. Addressing this gap, the present study investigated the relationships among AI usage, motivation, self-efficacy, learning engagement, and learning enjoyment among 563 Chinese EFL learners. Guided by Expectancy-Value Theory, the study further explored the predictive roles of AI usage, motivation, and self-efficacy in shaping learners' engagement and enjoyment. Data were collected through validated questionnaires measuring AI tool usage frequency, motivation, enjoyment, self-efficacy, and engagement. Correlation analyses demonstrated significant positive associations among all variables. Multiple regression and structural equation modelling (SEM) analyses revealed that motivation was the strongest predictor of both engagement and enjoyment, followed by self-efficacy and AI usage. The findings indicate that AI integration alone does not automatically enhance learning outcomes; rather, its effectiveness depends on how it aligns with learners' expectancy beliefs and task values. By extending Expectancy-Value Theory to AI-mediated EFL learning environments, this study contributes to the theoretical understanding of motivational processes in technology-enhanced education and offers pedagogical implications for educators and curriculum designers aiming to foster sustained engagement and positive emotional experiences through AI-supported instruction.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1507067
Database: ERIC
FullText Text:
  Availability: 0
Header DbId: eric
DbLabel: ERIC
An: EJ1507067
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A Correlational Study of AI Usage, Motivation, Self-Efficacy, and Learning Engagement in Education: Based on Expectancy-Value Theory
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Qi+Chai%22">Qi Chai</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0006-1721-3100">0009-0006-1721-3100</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22European+Journal+of+Education%22"><i>European Journal of Education</i></searchLink>. 2026 61(2).
– Name: Avail
  Label: Availability
  Group: Avail
  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
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 12
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2026
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink><br /><searchLink fieldCode="DE" term="%22Learner+Engagement%22">Learner Engagement</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22English+%28Second+Language%29%22">English (Second Language)</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Motivation%22">Learning Motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Motivation%22">Student Motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Influence+of+Technology%22">Influence of Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+Patterns%22">Psychological Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Emotional+Response%22">Emotional Response</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/ejed.70633
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0141-8211<br />1465-3435
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The rapid integration of artificial intelligence (AI) tools into educational settings has reshaped language learning practices; however, empirical evidence explaining how AI usage interacts with learners' motivational beliefs and self-perceptions to influence engagement and enjoyment remains limited, particularly in EFL contexts. Although prior studies have examined technology adoption or learner motivation separately, few have situated AI-assisted learning within a comprehensive motivational framework such as Expectancy-Value Theory. Addressing this gap, the present study investigated the relationships among AI usage, motivation, self-efficacy, learning engagement, and learning enjoyment among 563 Chinese EFL learners. Guided by Expectancy-Value Theory, the study further explored the predictive roles of AI usage, motivation, and self-efficacy in shaping learners' engagement and enjoyment. Data were collected through validated questionnaires measuring AI tool usage frequency, motivation, enjoyment, self-efficacy, and engagement. Correlation analyses demonstrated significant positive associations among all variables. Multiple regression and structural equation modelling (SEM) analyses revealed that motivation was the strongest predictor of both engagement and enjoyment, followed by self-efficacy and AI usage. The findings indicate that AI integration alone does not automatically enhance learning outcomes; rather, its effectiveness depends on how it aligns with learners' expectancy beliefs and task values. By extending Expectancy-Value Theory to AI-mediated EFL learning environments, this study contributes to the theoretical understanding of motivational processes in technology-enhanced education and offers pedagogical implications for educators and curriculum designers aiming to foster sustained engagement and positive emotional experiences through AI-supported instruction.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2026
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1507067
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1507067
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/ejed.70633
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
    Subjects:
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Self Efficacy
        Type: general
      – SubjectFull: Learner Engagement
        Type: general
      – SubjectFull: Second Language Learning
        Type: general
      – SubjectFull: English (Second Language)
        Type: general
      – SubjectFull: Learning Motivation
        Type: general
      – SubjectFull: Student Motivation
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Influence of Technology
        Type: general
      – SubjectFull: Psychological Patterns
        Type: general
      – SubjectFull: Emotional Response
        Type: general
      – SubjectFull: China
        Type: general
    Titles:
      – TitleFull: A Correlational Study of AI Usage, Motivation, Self-Efficacy, and Learning Engagement in Education: Based on Expectancy-Value Theory
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Qi Chai
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 0141-8211
            – Type: issn-electronic
              Value: 1465-3435
          Numbering:
            – Type: volume
              Value: 61
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: European Journal of Education
              Type: main
ResultId 1