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Gender Perceptions of Generative AI in Higher Education

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Title: Gender Perceptions of Generative AI in Higher Education
Language: English
Authors: Hosam Al-Samarraie (ORCID 0000-0002-9861-8989), Samer Muthana Sarsam, Ahmed Ibrahim Alzahrani, Arunangsu Chatterjee, Bronwen J. Swinnerton
Source: Journal of Applied Research in Higher Education. 2025 17(5):1944-1958.
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: 15
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Gender Differences, Telecommunications, Handheld Devices, College Students, Student Attitudes
DOI: 10.1108/JARHE-02-2024-0109
ISSN: 2050-7003
1758-1184
Abstract: Purpose: This study explored the themes and sentiments of online learners regarding the use of Generative Artificial Intelligence (AI) or "generative AI" technology in higher education. Design/methodology/approach: English-language tweets were subjected to topic modelling and sentiment analysis. Three prevalent themes were identified and discussed: curriculum development opportunities, lifelong learning prospects and challenges associated with generative AI use. Findings: The results also indicated a range of topics and emotions towards generative AI in education, which were predominantly positive but also varied across male and female users. Originality/value: The findings provide insights for educators, policymakers and researchers on the opportunities and challenges associated with the integration of generative AI in educational settings. This includes the importance of identifying AI-supported learning and teaching practices that align with gender-specific preferences to offer a more inclusive and tailored approach to learning.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1497179
Database: ERIC
FullText Text:
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  Data: Gender Perceptions of Generative AI in Higher Education
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  Data: <searchLink fieldCode="AR" term="%22Hosam+Al-Samarraie%22">Hosam Al-Samarraie</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9861-8989">0000-0002-9861-8989</externalLink>)<br /><searchLink fieldCode="AR" term="%22Samer+Muthana+Sarsam%22">Samer Muthana Sarsam</searchLink><br /><searchLink fieldCode="AR" term="%22Ahmed+Ibrahim+Alzahrani%22">Ahmed Ibrahim Alzahrani</searchLink><br /><searchLink fieldCode="AR" term="%22Arunangsu+Chatterjee%22">Arunangsu Chatterjee</searchLink><br /><searchLink fieldCode="AR" term="%22Bronwen+J%2E+Swinnerton%22">Bronwen J. Swinnerton</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Applied+Research+in+Higher+Education%22"><i>Journal of Applied Research in Higher Education</i></searchLink>. 2025 17(5):1944-1958.
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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: 15
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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="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunications%22">Telecommunications</searchLink><br /><searchLink fieldCode="DE" term="%22Handheld+Devices%22">Handheld Devices</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink>
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  Data: 10.1108/JARHE-02-2024-0109
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  Data: 2050-7003<br />1758-1184
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: This study explored the themes and sentiments of online learners regarding the use of Generative Artificial Intelligence (AI) or "generative AI" technology in higher education. Design/methodology/approach: English-language tweets were subjected to topic modelling and sentiment analysis. Three prevalent themes were identified and discussed: curriculum development opportunities, lifelong learning prospects and challenges associated with generative AI use. Findings: The results also indicated a range of topics and emotions towards generative AI in education, which were predominantly positive but also varied across male and female users. Originality/value: The findings provide insights for educators, policymakers and researchers on the opportunities and challenges associated with the integration of generative AI in educational settings. This includes the importance of identifying AI-supported learning and teaching practices that align with gender-specific preferences to offer a more inclusive and tailored approach to learning.
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  Data: 2026
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  Data: EJ1497179
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      – Type: doi
        Value: 10.1108/JARHE-02-2024-0109
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 1944
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Higher Education
        Type: general
      – SubjectFull: Gender Differences
        Type: general
      – SubjectFull: Telecommunications
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      – SubjectFull: Handheld Devices
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      – SubjectFull: College Students
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      – SubjectFull: Student Attitudes
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      – TitleFull: Gender Perceptions of Generative AI in Higher Education
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            NameFull: Samer Muthana Sarsam
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            NameFull: Ahmed Ibrahim Alzahrani
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            NameFull: Arunangsu Chatterjee
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            NameFull: Bronwen J. Swinnerton
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              Type: published
              Y: 2025
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