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Future research recommendations for transforming higher education with generative AI
Open accessAbstract
Higher education is crucial for producing ethical citizens and professionals globally. The introduction of generative AI (GenAI), such as ChatGPT, has posed opportunities and challenges to the traditional model of education. However, the current conversations primarily focus on policy development and assessment, with limited research on the future of higher education. GenAI's impact on learning outcomes, pedagogy, and assessment is crucial for reforming and advancing the workforce. This qualitative study aims to investigate student perspectives on GenAI's impact on higher education. The study uses an initial conceptual framework driven by a systematic literature review to investigate the opportunities and challenges of AI in education. This framework serves as an initial data collection and analysis framework. A sample of 51 students from three research-intensive universities was selected for this study. Thematic analysis identified three themes and 10 subthemes. The findings suggest that future higher education should be transformed to train students to be future-ready for employment in a society powered by GenAI. They suggest new learning outcomes—skills in learning and teaching with GenAI, AI literacy—and emphasize the significance of interdisciplinarity and maker learning, with assessment focusing on in-class and hands-on activities. They recommend six future research directions – competence for future workforce and its self-assessment measures, AI literacy or competency…
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In the citing paper
“AI has prompted instructors to re-think the foundation of assessment, whether the traditional assessment types are still fit for purpose, and ultimately, the purpose of teaching, learning and the very existence of higher education (Chiu, 2024a; Irving-Walton, 2026).”
From Assessment-focused governance mode? Mapping Generative AI policies across 76 UK higher education institutions: Policy framework and recommendations (2026) · cites this paper as Chiu, 2024a
In the citing paper
“It suggests that introducing GenAI can shift the focus from transferring knowledge to processing knowledge and from disciplinary learning to interdisciplinary learning (Chiu, 2024).”
From Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania (2024) · cites this paper as Chiu, 2024
In the citing paper
“Increasing student con fi dence in utilising GenAI is thus an important consideration regarding student equity (Chiu, 2024; Ng et al., 2021).”
From Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module (2025) · cites this paper as Chiu, 2024
In the citing paper
“Understanding how GenAI tools function as well as their capabilities and limitations can help students use these tools responsibly and effectively (Chiu, 2024; Southworth et al., 2023).”
From Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module (2025) · cites this paper as Chiu, 2024
In the citing paper
“Meanwhile, whereas universities might have their own GenAI policies, students might not read or understand these documents (Chiu, 2024) or, in other cases, fi nd them lacking and ambiguous (Jisc, 2024).”
From Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module (2025) · cites this paper as Chiu, 2024
In the citing paper
“As an important adjunct, scholars have also pointed out the importance of addressing broader societal and ethical considerations of AI (Chiu, 2024; Hornberger et al., 2023).”
From Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module (2025) · cites this paper as Chiu, 2024
In the citing paper
“Other studies, however, point to considerable variance in students ' understanding of inappropriate or unethical use of GenAI (Chan, 2023b), again highlighting the need both for clear institutional guidance and policy, as well as explicit pedagogical focus on this area (Chiu, 2024; Kong et al., 2024; Walter, 2024).”
From Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module (2025) · cites this paper as Chiu, 2024
In the citing paper
“This is an approach that is in keeping with recent work positioning prompt engineering and pedagogical AI design as central academic competences for the GenAI era (Chiu, 2024; Mollick & Mollick, 2024).”
From Effects of Partial vs. Full Cognitive Offloading with Generative AI on Learning Retention (2026) · cites this paper as Chiu, 2024
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Cited by
Sorted by citations
A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education
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Metadata
- Authors
- Chiu, T. K. F.
- Affiliations
- Chinese University of Hong Kong (HK)
- Corresponding author
- Chiu, Thomas K.F.
- ORCID
- Chiu, Thomas K.F.
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2024-06
- Volume
- 6
- Pages
- 100197
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4390278281
- Cited by
- 511
- References
- 49
- Citations by year
- 2026: 207 · 2025: 196 · 2024: 108
- FWCI
- 119.97
- Type
- journal article
- Language
- en
- Update notices
- erratum (2024-06-01)
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Education › Digital Transformation of Higher Education
- Keywords
- generative AI in higher education, student perceptions, AI literacy, AI literacy assessment, interdisciplinary teaching, pedagogy, career readiness, future skills, ChatGPT, research recommendations
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