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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
Citations
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ChatGPT for good? On opportunities and challenges of large language models for education
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Self-citationThirty years of research on online learning
Mayer, R. E. (2018) · Applied Cognitive Psychology · doi:10.1002/acp.3482 · Cited by 428
Research works printed but not linked: 1
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“…are adapting their curricula to transmit the latest skills related to Industry 5.0 [16], becoming promoters of the development of local–global innovation ecosystems [17], developing new skills to balance economic efficiency [18], and/or including concepts for the integration of ethics [17,19].”
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“Innovative pedagogical practices that focus on developing competence for the future workforce are also considered key directions for future research on AI & Education [6].”
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“For this reason, the integration of ChatGPT and other generative AI models into education must be carefully designed and implemented despite their promise for facilitating learning, teaching, assessment, and educational administration (Chiu, 2024; Jia et al., 2024).”
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“[2] and [3] highlight the potential of generative AI (GenAI) to foster learner autonomy, project-based engagement, and real-time adaptation.”
Zamora-Hernández, I., Rodríguez-Paz, M., González-Mendivil, J., et al. (2025) · International Conference on Education Technology and Computer · doi:10.1109/icetc66579.2025.11387367
“[1] emphasizes its capacity to support artifact creation and interdisciplinary thinking, while [2] and [3] highlight its value in enabling multilingual, immediate-feedback learning environments.”
Mahankale, N. R., & Tathavadekar, V. P. (2025) · International Journal of Latest Technology in Engineering Management & Applied Science · doi:10.51583/ijltemas.2025.140600048
Na, R., & Tayrattanachai, N.-O. (2025) · Forum for Linguistic Studies · doi:10.30564/fls.v7i6.8487
“Contemporary research on solfeggio teaching in Chinese institutions has identified various methodological considerations specific to students operating within a tonal linguistic environment [15] .”
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Synergistic Education and Network Optimization with Gen AI
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“Chiu (2024) underlined that disciplinary knowledge is essential for the appropriate use of GenAI.”
Media, media education, GAI and radical uncertainty
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“Chiu (2024) interviewed 51 students from three research-intensive universities.”
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“Samtidig understreket flere av artiklene viktigheten av både holdninger og opplæring blant pedagoger (Walter, 2024) og studenter (Chiu, 2024) for å bli klar for å arbeide i et samfunn der bruk av skriveroboter stadig blir mer aktuelt.”
Artificial Intelligence Technologies in Higher Education: Reality and Challenges
Abu‐Orabi, S. T. (2024) · International Conference on Developments in eSystems Engineering (DeSE) · doi:10.1109/dese63988.2024.10911936 · Cited by 2
“The qualitative study by Chiu [12] aims to investigate students’ perspectives on the impact of introducing generative artificial intelligence, such as ChatGPT, into higher education.”
Hyped or Transformational? AI in Higher Education
Kilis, S., & Murgatroyd, S. (2024) · REVISTA PARAGUAYA DE EDUCACIÓN A DISTANCIA (REPED) · doi:10.56152/reped2024-dossieria2-art1 · Cited by 3
“AI does not threaten teachers but rather supports them as a teaching assistant or learning agency for students (Bates et al., 2020; Chiu et al., 2023; Chiu, 2024).”
BackgroundAkhmetsapa, Uzunboylu, Zholtayeva, et al. (2024) · Pedagogy and Psychology · doi:10.51889/2960-1649.2024.59.2.011
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Feldman-Maggor, Y. (2026) · International Conference on Computer Supported Education · doi:10.5220/0014921200004021
“Conversely, both amplification and transformation may also enhance teaching strategies or enable entirely new learning modalities (Chiu et al., 2024; Shamir-Inbal et al., 2024).”
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“Higher education must prepare students to learn and teach with generative AI through new literacies, interdisciplinary practices, and authentic assessment [10].”
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“[10] The computer science provides instrument and technology in the financial area, so as to adapt to digital era, and jump to opportunity for digital-financial reform.”
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“This can optimize teaching processes, improve teaching efficiency and quality, and address the challenges faced by finance education[6].”
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“…Tayan et al. 2024; Vargas-Murillo et al. 2023; Wu 2024), reinforce critical thinking skills (Aithal and Aithal 2023; Hsiao, Klijn, and Chiu 2023; Rasul et al. 2023; Wu 2024), and develop uniquely human skills, often referred to as soft skills (Aithal and Aithal 2023; Chiu 2024; Rasul et al. 2023).”
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“Future research on the advancement of these literacies and their interrelationships needs to be done [17].”
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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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