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Cited by 73Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationEducational Technology and Pedagogy

Is Artificial Intelligence Really the Next Big Thing in Learning and Teaching in Higher Education? A Conceptual Paper

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O'Dea, Xianghan (Christine), O'Dea, Mike·2023·Journal of University Teaching and Learning Practice
DOI 10.53761/1.20.5.06
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Abstract

Artificial Intelligence in higher education (AIED) is becoming a more important research area with increasing developments and application of AI within the wider society. However, as yet AI based tools have not been widely adopted in higher education. As a result there is a lack of sound evidence available on the pedagogical impact of AI for learning and teaching. This conceptual paper thus seeks to bridge the gap and addresses the following question: is artificial intelligence really the new big thing that will revolutionise learning and teaching in higher education? Adopting the technological pedagogical content knowledge (TPACK) framework and the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical foundations, we argue that Artificial Intelligence (AI) technologies, at least in their current state of development, do not afford any real new advances for pedagogy in higher education. This is mainly because there does not seem to be valid evidence as to how the use of AI technologies and applications has helped students improve learning, and/or helped tutors make effective pedagogical changes. In addition, the pedagogical affordances of AI have not yet been clearly defined. The challenges that the higher education sector is currently experiencing relating to AI adoption are discussed at three hierarchical levels, namely national, institutional and personal levels. The paper ends with recommendations with regard to accelerating AI use in universities. This includes developing dedicated AI adoption strategies at the institutional level, updating the existing technology infrastructure and up-skilling academic tutors for AI.

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  • Educators' hesitation to adopt AI in education is justified by concerns over plagiarism, privacy issues, ethical considerations, and issues of privacy.

    “Educators' hesitation to adopt AI in education is justified by concerns over plagiarism, privacy issues, ethical considerations, and issues of privacy (Fui-Hoon Nah et al., 2023; Lodge et al., 2023; O'Dea and O'Dea, 2023; Rasul et al., 2023).”

    From Developing a conceptual framework for Artificial Intelligence (AI) literacy in higher education (2024) · cites this paper as O'Dea and O'Dea, 2023

  • There is still a lack of sound evidence on the pedagogical impact of AI technologies in HEIs, raising questions about their ability to improve learning outcomes or facilitate effective pedagogical changes.

    “Regarding the adoption of AI in HEIs, there is still a lack of sound evidence on the pedagogical impact of AI technologies, which raises questions about their ability to improve learning outcomes or facilitate effective pedagogical changes [37].”

    From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [37]

  • There is still apprehension about using AI in education despite the push from employers.

    “Despite the push from employers, there is still apprehension about using AI in education.”

    From Developing a conceptual framework for Artificial Intelligence (AI) literacy in higher education (2024) · cites this paper as O'Dea and O'Dea, 2023

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Authors
O'Dea, X. (., & O'Dea, M.
ORCID
O'Dea, Mike
Venue
Journal of University Teaching and Learning Practice
Publisher
Open Access Publishing Association
Published
2023-09-03
Volume
20
Issue
5
ISSN
1449-9789 (ISSN-L)
DOI
10.53761/1.20.5.06
OpenAlex
W4378628106
Cited by
73
References
107
Citations by year
2026: 21 · 2025: 30 · 2024: 20 · 2023: 2
FWCI
17.14
Type
journal article
Language
en
Open access
Locations
  • Journal of University Teaching and Learning Practice (publishedVersion)
  • Research Online (University of Wollongong) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Educational Technology and Pedagogy
Keywords
artificial intelligence in education, university teaching, AI adoption in universities, TPACK framework, UTAUT, AI adoption strategy, technological infrastructure, technology acceptance

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