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AI versus tradition: shaping the future of higher education

Isabella Margarethe Venter Orcid Logo, Rénette Julia Blignaut Orcid Logo, Desireé Cranfield Orcid Logo, Andrea Tick Orcid Logo, Soha El Achi Orcid Logo

Journal of Applied Research in Higher Education, Volume: 17, Issue: 7, Pages: 151 - 167

Swansea University Author: Desireé Cranfield Orcid Logo

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DOI (Published version): 10.1108/jarhe-12-2024-0702

Abstract

Purpose—This research aims to investigate the use of conversational artificial intelligence in academic practice through the lens of activity theory, which emphasises the mediation of human actions by tools within a social context. Additionally, it seeks to determine if and how the results of qualit...

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Published in: Journal of Applied Research in Higher Education
ISSN: 2050-7003 1758-1184
Published: Emerald 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa69189
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last_indexed 2025-05-09T07:03:58Z
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spelling 2025-05-08T12:48:13.4328629 v2 69189 2025-03-31 AI versus tradition: shaping the future of higher education 3f8fe4194470d374d18e4738089a6ab1 0000-0002-3082-687X Desireé Cranfield Desireé Cranfield true false 2025-03-31 CBAE Purpose—This research aims to investigate the use of conversational artificial intelligence in academic practice through the lens of activity theory, which emphasises the mediation of human actions by tools within a social context. Additionally, it seeks to determine if and how the results of qualitative analysis differ when using traditional qualitative analysis software tools compared to using artificial intelligence tools.Design/methodology/approach—A pragmatic approach to the research design was used. The data collection phase included a survey, with open- and closed-ended questions, and was distributed to academics in four countries (South Africa, Hungary, Lebanon, and Wales). The data analysis phase included a mixed methods approach integrating and interpreting both types of data to leverage the strengths of both qualitative and quantitative insights. Furthermore, traditional qualitative analysis methods, and artificial intelligence tools were used for the analysis phase, allowing for a comprehensive understanding of the interactions between academics and these tools.Findings—Younger academics used conversational artificial intelligence more for research than teaching, with academics from the science faculty using it more for teaching, and business management lectures using it more for research. While viewed positively, concerns arose about ethics and educational alignment. This research shows how conversational artificial intelligence supports qualitative analysis by saving time and suggesting new directions.Originality—Using an “activity theory” theoretical lens, with a pragmatic approach, the research explores how conversational artificial intelligence tools impact academic practices. The study enriches theoretical discourse and offers practical recommendations for education. Journal Article Journal of Applied Research in Higher Education 17 7 151 167 Emerald 2050-7003 1758-1184 higher education, large language models, digital skills, digital ethics, conversational artificial intelligence, qualitative research 1 5 2025 2025-05-01 10.1108/jarhe-12-2024-0702 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University Another institution paid the OA fee 2025-05-08T12:48:13.4328629 2025-03-31T15:42:43.9063992 Faculty of Humanities and Social Sciences School of Management - Business Management Isabella Margarethe Venter 0000-0001-6554-8024 1 Rénette Julia Blignaut 0000-0002-3150-6624 2 Desireé Cranfield 0000-0002-3082-687X 3 Andrea Tick 0000-0002-3139-6509 4 Soha El Achi 0009-0006-2589-4962 5 69189__34203__19957d939b6441cb9aa6b3d4adb7490a.pdf 69189.VoR.pdf 2025-05-08T12:42:29.0733948 Output 1688667 application/pdf Version of Record true © 2025, Isabella Margarethe Venter, Rénette Julia Blignaut, Desireé Joy Cranfield, Andrea Tick and Soha El Achi. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. true eng http://creativecommons.org/licences/by/4.0/legalcode
title AI versus tradition: shaping the future of higher education
spellingShingle AI versus tradition: shaping the future of higher education
Desireé Cranfield
title_short AI versus tradition: shaping the future of higher education
title_full AI versus tradition: shaping the future of higher education
title_fullStr AI versus tradition: shaping the future of higher education
title_full_unstemmed AI versus tradition: shaping the future of higher education
title_sort AI versus tradition: shaping the future of higher education
author_id_str_mv 3f8fe4194470d374d18e4738089a6ab1
author_id_fullname_str_mv 3f8fe4194470d374d18e4738089a6ab1_***_Desireé Cranfield
author Desireé Cranfield
author2 Isabella Margarethe Venter
Rénette Julia Blignaut
Desireé Cranfield
Andrea Tick
Soha El Achi
format Journal article
container_title Journal of Applied Research in Higher Education
container_volume 17
container_issue 7
container_start_page 151
publishDate 2025
institution Swansea University
issn 2050-7003
1758-1184
doi_str_mv 10.1108/jarhe-12-2024-0702
publisher Emerald
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
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description Purpose—This research aims to investigate the use of conversational artificial intelligence in academic practice through the lens of activity theory, which emphasises the mediation of human actions by tools within a social context. Additionally, it seeks to determine if and how the results of qualitative analysis differ when using traditional qualitative analysis software tools compared to using artificial intelligence tools.Design/methodology/approach—A pragmatic approach to the research design was used. The data collection phase included a survey, with open- and closed-ended questions, and was distributed to academics in four countries (South Africa, Hungary, Lebanon, and Wales). The data analysis phase included a mixed methods approach integrating and interpreting both types of data to leverage the strengths of both qualitative and quantitative insights. Furthermore, traditional qualitative analysis methods, and artificial intelligence tools were used for the analysis phase, allowing for a comprehensive understanding of the interactions between academics and these tools.Findings—Younger academics used conversational artificial intelligence more for research than teaching, with academics from the science faculty using it more for teaching, and business management lectures using it more for research. While viewed positively, concerns arose about ethics and educational alignment. This research shows how conversational artificial intelligence supports qualitative analysis by saving time and suggesting new directions.Originality—Using an “activity theory” theoretical lens, with a pragmatic approach, the research explores how conversational artificial intelligence tools impact academic practices. The study enriches theoretical discourse and offers practical recommendations for education.
published_date 2025-05-01T05:21:41Z
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