Gender Perceptions of Generative AI in Higher Education

Saved in:
Bibliographic Details
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
Description
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.
ISSN:2050-7003
1758-1184
DOI:10.1108/JARHE-02-2024-0109