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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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“According to Chiu (2024), ChatGPT and other intelligent devices have the ability to act as thinking partners that help students develop critical and reflective thinking skills.”
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Elizalde, A. F. C., Ramirez, O. C. G., Cueva, E. L. L., & Asanza, W. B. R. (2025) · Estudios y Perspectivas Revista Científica y Académica · doi:10.61384/r.c.a..v5i2.1200 · Cited by 1
The Opinions of Academics on the Usage of Artificial Intelligence Tools in Primary Schools
Ölçer, S., Cesur, B., KURŞUN, Z., Çetinkale, E., & Gök, B. (2025) · Educational Academic Research · doi:10.33418/education.1515939 · Cited by 1
The GenAI Generation: Student Views of Awareness, Preparedness, and Concern
Siraj, M., Duke, J., & Plötz, T. (2025) · SoutheastCon · doi:10.1109/southeastcon63549.2026.11476077 · Cited by 2
“Scholars recommend embedding AI literacy, practical applications, and interdisciplinary, project-based learning to better align academic preparation with workforce demands [8].”
Analysis of college students' attitude towards using AI in their academic works
Hermosura, L. F. (2025) · World Journal of Advanced Research and Reviews · doi:10.30574/wjarr.2025.26.1.1527 · Cited by 2
“Furthermore, there is an acknowledged need to prepare students and educators for work in a society enriched by generative AI, with novel learning outcomes such as AI literacy and a focus on interdisciplinarity and activity-based assessment [7].”
Effectiveness of Digital Training for Educational Staff in Management Information Systems
Abdullah, S., Baharuddin, B., & Tanal, A. N. (2025) · International Journal of Asian Education · doi:10.46966/ijae.v6i1.475 · Cited by 2
“However, such systems' effectiveness largely depends on the educational staff's competency in utilizing digital tools and adapting to technological changes (Chiu, 2024; Kim & Jung, 2022; M’mboga Akala, 2021 ).”
Impacto de la Inteligencia Artificial en la transformación digital y aprendizaje educativo.
Reyes, A. R. T., Macas, F. V. C., González, S. A. V., & Ramos, I. D. R. B. (2025) · EcoSur Innovación Tecnología y Desarrollo Sostenible de América Latina · doi:10.61582/k266es50 · Cited by 5
Castillo, V. S., & Jiménez-Pérez, G. A. (2025) · Eco Matemático · doi:10.22463/17948231.4658 · Cited by 2
Garro-Mena, L. (2024) · REDU Revista de Docencia Universitaria · doi:10.4995/redu.2024.21989 · Cited by 2
WIP: What are AI Bachelor Degrees About? A Comparative Analysis
He, Z., Pang, P. C., & Lam, C. K. (2024) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10893136 · Cited by 1
“There has been much research on the applications of AI in higher education [13], such as the application of AI technology in teaching [14], teaching AI in STEM [15], and AI software enhancing educational outcomes [16][17].”
Enhancing Higher Education Pedagogy with ChatGPT: Leveraging the Power of Generative AI
Sain, Z. H., Baharun, H., & Abdullah, N. B. (2024) · Journal Emerging Technologies in Education · doi:10.70177/jete.v2i3.1189 · Cited by 6
“Chiu (2024) suggests that the future of higher education should transform to ensure students and educators are trained in learning and teaching with generative AI, thereby developing and enhancing AI literacy skills.”
BackgroundHelp or Hindrance? Examining the role of generative AI in shaping students' entrepreneurial mindsets
Ma, C., 重和, 樋., Chen, S.-H., & Liu, W. (2026) · The International Journal of Management Education · doi:10.1016/j.ijme.2026.101483 · Cited by 2
Towards a Flipped Learning Ecosystem: A Generative Artificial Intelligence-Enabled Framework
ElGamal, H. (2025) · European Journal of Open Distance and E-Learning · doi:10.65043/eurodl.151 · Cited by 1
Gómez, S., Rebolledo, E. K. S., & Cano, J. M. (2025) · Educação e Pesquisa · doi:10.1590/s1678-4634202551294421es · Cited by 2
Ding, Q., Ye, J., Wang, N., & Liu, L. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2726354
Empowering educators: A pilot study on AI literacy in K–12 professional development
Nelson, K., Du, S., Marshall, D. T., Bowers, S., & Ali, A. (2026) · Online Learning · doi:10.24059/olj.v30i3.5251 · Cited by 1
Balart, T., Raju, G. M., & Shryock, K. J. (2026) · Algorithms · doi:10.3390/a19080703 · Cited by 1
“Chiu [43] argues that preparing students for a GenAI-influenced future requires new learning outcomes related to AI literacy, interdisciplinary learning, and future professional competence.”
Awang, A., & Razak, M. H. A. (2026) · Journal of governance and development · doi:10.32890/jgd2026.22.2.2 · Cited by 1
“While students are proficient in using AI tools, they often lack critical evaluation skills, ethical awareness, and the ability to assess the validity of information (Chiu, 2024; Dwivedi et al., 2023).”
Liu, K., Zhang, J., Guan, H., Zheng, C., & Yang, X. (2026) · Information · doi:10.3390/info17080742 · Cited by 1
Alotaibi, A., Aseery, A., Alfayez, A. A., Bashatah, L., & Aseri, S. (2026) · British Educational Research Journal · doi:10.1002/berj.70256 · Cited by 2
Cheah, Y. H., Hsu, H.-P., Lu, J., & Alsaka, R. (2026) · Journal of Research on Technology in Education · doi:10.1080/15391523.2026.2704778 · Cited by 1
Kumar, J. A., Salim, Z., Annamalai, N., Dhaliwal, J., & Singh, A. D. (2026) · Quality & Quantity · doi:10.1007/s11135-026-02982-w · Cited by 1
Dilinika, J. M. S. (2026) · Education for Information · doi:10.1177/01678329261468180 · Cited by 1
Кремень, В. Г., Spirin, O. M., ЛЯШЕНКО, О. І., Lytvynova, S., Мальований, Ю. І., Pinchuk, O., Sokolyuk, O. M., & Semerikov, S. O. (2026) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2026.100648
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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