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Would Students Accept Virtual Agents for Academic Advising? A Fit, Viability, and Risk Perspective

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Title: Would Students Accept Virtual Agents for Academic Advising? A Fit, Viability, and Risk Perspective
Language: English
Authors: Samar Ibrahim, Ghazala Bilquise, Sa’Ed M. Salhieh
Source: Interactive Technology and Smart Education. 2026 23(2):374-407.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 34
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Man Machine Systems, Higher Education, Computer Simulation, Academic Advising, Intention, Student Attitudes, Gender Differences, Student Characteristics, Grade Level Differences, Risk Assessment, Computer Attitudes, Foreign Countries
Geographic Terms: United Arab Emirates
DOI: 10.1108/ITSE-10-2025-0293
ISSN: 1741-5659
1758-8510
Abstract: Purpose: The use of service-oriented artificial intelligence-powered virtual agents (VAs) in higher education is expanding, particularly in academic advising. However, their adoption is hindered by challenges such as a lack of transparency, trust, system capability and organisational readiness. This study aims to investigate the factors influencing students' behavioural intention to adopt academic advising VAs in Higher education. Design/methodology/approach: This study applies an extended Fit-Viability Model (FVM) to investigate the fit requirements and viability of the advising VA system. The model incorporates perceived risk as a key predictor and examines the moderating role of demographic variables for this model. Survey data were collected from 239 students and analysed using partial least squares structural equation modelling to test the extended FVM framework. Findings: The findings showed that both perceived fit and perceived risk significantly impact students' behavioural intention to use advising VAs. Moreover, the study revealed that gender influences the relationship between risk and student intention, highlighting demographic influences on adoption. Practical implications: This study provides practical implications for academic institutions seeking to enhance student adoption of advising VAs by addressing system fit and risk concerns. Theoretically, it contributes to adoption research by extending the FVM model with risk considerations and demographic moderators, offering a more comprehensive framework for future studies. Originality/value: Unlike prior academic advising studies that rely primarily on acceptance-based models, this study extends the FVM by incorporating perceived risk and demographic moderators.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1507522
Database: ERIC
FullText Text:
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  Data: Would Students Accept Virtual Agents for Academic Advising? A Fit, Viability, and Risk Perspective
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  Data: <searchLink fieldCode="AR" term="%22Samar+Ibrahim%22">Samar Ibrahim</searchLink><br /><searchLink fieldCode="AR" term="%22Ghazala+Bilquise%22">Ghazala Bilquise</searchLink><br /><searchLink fieldCode="AR" term="%22Sa%27Ed+M%2E+Salhieh%22">Sa’Ed M. Salhieh</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Interactive+Technology+and+Smart+Education%22"><i>Interactive Technology and Smart Education</i></searchLink>. 2026 23(2):374-407.
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  Data: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
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  Data: Y
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  Data: 34
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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="%22Man+Machine+Systems%22">Man Machine Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Simulation%22">Computer Simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Advising%22">Academic Advising</searchLink><br /><searchLink fieldCode="DE" term="%22Intention%22">Intention</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+Level+Differences%22">Grade Level Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+Assessment%22">Risk Assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Attitudes%22">Computer Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22United+Arab+Emirates%22">United Arab Emirates</searchLink>
– Name: DOI
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  Data: 10.1108/ITSE-10-2025-0293
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1741-5659<br />1758-8510
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: The use of service-oriented artificial intelligence-powered virtual agents (VAs) in higher education is expanding, particularly in academic advising. However, their adoption is hindered by challenges such as a lack of transparency, trust, system capability and organisational readiness. This study aims to investigate the factors influencing students' behavioural intention to adopt academic advising VAs in Higher education. Design/methodology/approach: This study applies an extended Fit-Viability Model (FVM) to investigate the fit requirements and viability of the advising VA system. The model incorporates perceived risk as a key predictor and examines the moderating role of demographic variables for this model. Survey data were collected from 239 students and analysed using partial least squares structural equation modelling to test the extended FVM framework. Findings: The findings showed that both perceived fit and perceived risk significantly impact students' behavioural intention to use advising VAs. Moreover, the study revealed that gender influences the relationship between risk and student intention, highlighting demographic influences on adoption. Practical implications: This study provides practical implications for academic institutions seeking to enhance student adoption of advising VAs by addressing system fit and risk concerns. Theoretically, it contributes to adoption research by extending the FVM model with risk considerations and demographic moderators, offering a more comprehensive framework for future studies. Originality/value: Unlike prior academic advising studies that rely primarily on acceptance-based models, this study extends the FVM by incorporating perceived risk and demographic moderators.
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  Data: 2026
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  Label: Accession Number
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  Data: EJ1507522
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        Value: 10.1108/ITSE-10-2025-0293
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 34
        StartPage: 374
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Man Machine Systems
        Type: general
      – SubjectFull: Higher Education
        Type: general
      – SubjectFull: Computer Simulation
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      – SubjectFull: Academic Advising
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      – SubjectFull: Intention
        Type: general
      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Gender Differences
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
      – SubjectFull: Grade Level Differences
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      – SubjectFull: Risk Assessment
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      – SubjectFull: Computer Attitudes
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      – SubjectFull: Foreign Countries
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      – SubjectFull: United Arab Emirates
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      – TitleFull: Would Students Accept Virtual Agents for Academic Advising? A Fit, Viability, and Risk Perspective
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            NameFull: Ghazala Bilquise
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            NameFull: Sa’Ed M. Salhieh
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