The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
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…
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
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
Cites
Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326
Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence
Cooper, G. (2023) · Journal of Science Education and Technology · doi:10.1007/s10956-023-10039-y · Cited by 1,263
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100118 · Cited by 1,181
Self-citationChatGPT for Education and Research: Opportunities, Threats, and Strategies
Rahman, M. M., & Watanobe, Y. (2023) · Applied Sciences · doi:10.3390/app13095783 · Cited by 1,080
Chiu, T. K. F. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2023.2253861 · Cited by 852
Self-citationPeres, R., Schreier, M., Schweidel, D., & Sorescu, A. (2023) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2023.03.001 · Cited by 535
Xia, Q., Chiu, T. K. F., Lee, M., Sanusi, I. T., Dai, Y., & Chai, C. S. (2022) · Computers & Education · doi:10.1016/j.compedu.2022.104582 · Cited by 469
Self-citationThirty years of research on online learning
Mayer, R. E. (2018) · Applied Cognitive Psychology · doi:10.1002/acp.3482 · Cited by 425
Research works printed but not linked: 1
- Chiu, 2021, Teacher professional development on Self-determination Theory-based design thinking in STEM education, Educational Technology & Society, 24, 153
Cited by
Sorted by citations
Items 301–400 of 537
Kazykhankyzy, L., Khalmatova, Z., Seıtova, M., Kılıç, E., & Çelik, H. E. (2026) · European Journal of Education · doi:10.1111/ejed.70746 · Cited by 1
Ng, A. W., & Cheung, C. F. (2026) · Sustainability · doi:10.3390/su18126086 · Cited by 3
Al-Ahmed, H., Dwaikat, N. Y., Hattab, M. K., & Khlaif, Z. N. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2673221 · Cited by 1
Artificial Intelligence as a Learning Companion in the Classroom
Sukmaningsih, J., Rofiq, M. A., Fikri, W. S. A., Maarif, M. F. A., & Saputra, W. N. E. (2026) · Buletin Edukasi Indonesia · doi:10.56741/iistr.bei.002279 · Cited by 1
Using degree apprenticeships to shape the future of traditional undergraduate degrees
Macaulay, E., Jackson, J., White, C., & Bevan, A. J. (2026) · Higher Education Skills and Work-based Learning · doi:10.1108/heswbl-07-2025-0290 · Cited by 1
Wang, N., Gan, S., & Du, L. (2026) · International Journal of Educational Development · doi:10.1016/j.ijedudev.2026.103582 · Cited by 1
Humble, N., & Mozelius, P. (2026) · Computers and Education Open · doi:10.1016/j.caeo.2026.100381 · Cited by 2
“On the other hand, there are research reporting on the potential benefits of 1) Personal tutoring [11,12], 2) AI-supported teachers [13 – 15]) and 3) Automated administration [16], for example by utilizing student data in interactive learning logs [17].”
The KATALYST Project: Transforming Teaching and Assessment with Generative AI
Bigler, D., Haug, J., Fischer, D. W., Manz, J., Lee, K., Becker, M., Hagel, G., & Klutke, P. (2026) · IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon67543.2026.11574384
“This leads to uncertainty regarding authorship, evaluation validity, and equal access to technology [2] [4] [5] [6].”
Бабенко, О. (2026) · International Medical Education · doi:10.3390/ime5020038 · Cited by 2
“While such individualized learning with generative AI may be bolstering students’ immediate motivation and engagement, it limits opportunities for peer collaboration and social interaction for students to develop interpersonal communication skills [13], which are key in team-based care [7].”
Paiwithayasiritham, C., Mingsiritham, K., Sinthaworn, W., & Busabong, C. (2026) · International Journal of Evaluation and Research in Education (IJERE) · doi:10.11591/ijere.v15i2.38385 · Cited by 1
“The present findings complement prior work that has emphasized the importance of ethics and trust in AI adoption [7], [8], [11], [17], [23] by showing that CLR acts as a more basic psychological mechanism for shaping trust when new users first encounter the technology consistent with previous…”
YouTube Content Production for Arabic Language Learning: Cross-National Study
Baharun, S., Hanifansyah, N., Habib, M. T., Arifin, A., Syaifullah, M., & Faqihah, N. A. (2026) · Online Learning In Educational Research (OLER) · doi:10.58524/oler.v6i1.982 · Cited by 5
“The process of learning has shifted from the simple reception of content to the production of multimodal texts, in which students have become producers rather than consumers (Chen et al., 2025; Chen & Liu, 2025; Chiu, 2024; Pellas, 2025).”
Exploring Student Perception on Gen AI Adoption in Higher Education: A Descriptive StudyPreprint
Singh, H., Singh, J., Singh, S., Singh, R. P., Shahid, S. I., Hassan, M., & Najaran, T. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2603.27777 · Cited by 1
“Students likewise expect a shift from easily automated traditional tasks toward authentic and interdisciplinary assessment for AI-rich workplaces (Chiu, 2024b; Sousa and Cardoso, 2025; Khlaif et al., 2025).”
Yoo, T.-A., Yang, H.-S., Kim, M., & Chung, J. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2646275 · Cited by 1
“However, there are also criticisms that due to technical limitations, AI cannot fully replace the need for “relatedness,” which encompasses human connection and emotional support (Chiu, 2024).”
Caccavale, F., Gargalo, C. L., Kager, J., Skowyra, M., Larsen, S., Gernaey, K. V., & Krühne, U. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2603.17773
“Moreover, traditional educational research may not be fully equipped to study AI in education (Chiu 2024).”
Nkosi, T. (2026) · Open Books and Proceedings · doi:10.38140/obp4-2026-06 · Cited by 1
“Supervisors must establish explicit guidelines for the use of AI tools so that these technologies support academic work rather than replace student effort (Chiu, 2024; Qutieshat, 2025; Ratnam et al., 2023; Walter, 2024).”
Dorji, K. (2026) · Asian Journal of Contemporary Education · doi:10.55493/5052.v10i1.5907 · Cited by 2
“Generative Artificial Intelligence (GenAI), a subset of artificial intelligence technologies, has emerged as a powerful tool capable of generating new content such as text, images, music, and code (Chiu, 2024).”
InfluentialFrom chalkboards to chatbots: generative AI impact on education in emerging economies
Virmani, N., Sharma, D., Sahu, A., & Garza‐Reyes, J. A. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2632172 · Cited by 3
Ugon, J., Pierce, C., Cain, A., & Laird, B. (2026) · Australasian Computing Education Conference · doi:10.1145/3786228.3786244 · Cited by 2
Al-Shamaileh, O., Hammady, R., Abdelrahman, M., & Mubin, O. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.100980 · Cited by 6
“…2024; Zeb et al., 2024) 34 Weighing Costs vs. Benefits (Adıguzel et al., 2023; Awad & Moosa, 2023; Bego, 2023; Caccavale et al., 2024; Chen et al., 2024; Chiu, 2024; Chiu et al., 2023; Lo, 2023; Crawford et al., 2024; Hasanein & Sobaih, 2023; Hidayat-ur-Rehman & Ibrahim, 2023; Frick, 2024; Sijing…”
Chen, H., & Pan, J. (2026) · Proceedings of the 2026 3rd International Conference on Informatics Education and Computer Technology Applications · doi:10.1145/3802133.3802300 · Cited by 1
“Empirical studies suggest that properly structured AI interactions can reduce communication anxiety and provide iterative practice [16] [17].”
Mapping the landscape: generative AI in higher education assessment (2020-2024) - a scoping review
Ng, S. H. S., Chan, H. Y., Wong, J. H. K., Sam, L. C. F., & Privitera, A. J. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2614079 · Cited by 9
Espino, L. C., Antonio, R., Constantino, R., et al. (2026) · International Journal of Technology in Education · doi:10.46328/ijte.5114 · Cited by 1
“Meaningful AI integration requires faculty training, curriculum redesign, and institutional readiness (Chan, 2023; Chiu, 2024).”
Evaluation of ChatGPT Study Mode: Results from an Expert Rating Regarding Self-Regulated Learning
Steinberg, E., Perels, F., Aubreville, M., & Dörrenbächer‐Ulrich, L. (2026) · Open Education Studies · doi:10.1515/edu-2025-0169
“Recommendations for students can also be viewed as recommendations for teachers, including discussing the strengths and limitations of Study Mode with students, as well as relevant policy and academic integrity rules (see also Chiu 2024).”
Attitudes and Perceptions of University Students Towards Using ChatGPT
Kavak, V. İ., & Kavak, E. (2025) · The Literacy Trek · doi:10.47216/literacytrek.1834394 · Cited by 1
Mapping research trends in innovative pedagogies: a bibliometric analysis
Awang, N. E., Zulkifli, H., & Hamzah, M. I. (2025) · International Journal of Evaluation and Research in Education (IJERE) · doi:10.11591/ijere.v14i6.34519 · Cited by 1
“The article by Chiu [14] reflects the urgency of integrating generative AI into educational systems, while Bizami et al. [43] explores how technology acceptance models influence teacher and student dynamics in modern learning environments.”
Higher Education and Research: AI Prescriptive
Mishra, A. D., Husain, A., Singh, Y. B., & Pandey, M. S. (2025) · Global AI Summit - International Conference on Artificial Intelligence and Emerging Technology (AI Summit) · doi:10.1109/aisummit66170.2025.11411316 · Cited by 1
“The author of the paper [1] suggested that future higher education evolve to train students for employment in a society driven by GenAI.”
Collaborative Interest Mining Network for Knowledge Graph-based Recommendation
Luo, J., Pan, Y., & Huang, G. (2025) · International Conference on Information and Knowledge Management · doi:10.1145/3746252.3761258 · Cited by 1
An Investigation of Chinese EFL Pre-Service Teachers' Use of of AI During Teaching Practicum
Xiao, Q.-M. (2025) · International Conference on Education Technology Management · doi:10.1109/icetm67477.2025.11413448 · Cited by 1
“…new paradigm offers unprecedented opportunities for promoting differentiated instruction, providing real-time formative assessment, facilitating adaptive learning trajectories, and generating actionable insights into student learning processes that were previously difficult to obtain at scale [3].”
Ariza, R. P., Ramos, Á. F. V., Chaves, P. L., & Gil‐Cordero, E. (2025) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2025.102059 · Cited by 2
Educação e regulação da inteligência artificial nas universidades públicas brasileiras
Pires, G. R., Moro, F., & Frigo, L. B. (2025) · Cuaderno activa · doi:10.53995/20278101.2042 · Cited by 1
Abunaser, F. M., Hamd, M. M., Bani-Oraba, A. M. N., Hamed, O., Alshiyab, M. Q. M., & Shebani, Z. (2025) · Sustainability · doi:10.3390/su17157092 · Cited by 4
Artificial Intelligence in Learning Design: Acceptance, Perceived Effectiveness, and Barriers
Pradana, H. D., Rusijono, R., Maureen, I. Y., & Youhanita, E. (2025) · Jurnal Penelitian dan Pengkajian Ilmu Pendidikan e-Saintika · doi:10.36312/e-saintika.v9i2.2688 · Cited by 2
Higher Education in the Age of AI: Chatgpt’s Impact on Students’ Academic Activities
Constantin, A., & Iacob, S.-E. (2025) · Proceedings of the International Conference on Business Excellence · doi:10.2478/picbe-2025-0256 · Cited by 1
“…on ChatGPT can limit critical thinking, creativity, and deep understanding because GPT’s ability to provide an answer in less than five seconds has caused students to have a preference for prompts consisting in content creation, (Fiialka et al., 2023; Chiu et al., 2024; Mogavi et al., 2024).”
Kınık, F. Ş. F. (2025) · Journal of Teacher Development and Education · doi:10.29329/journalted.42 · Cited by 1
Tan, Y., Zeng, X., & Tan, X. (2025) · 2025 5th International Conference on Artificial Intelligence and Education (ICAIE) · doi:10.1109/icaie64856.2025.11158707 · Cited by 1
“Based on a large language model, GAI tools provide support for students' personalized learning with powerful retrieval and content generation capabilities and multi-round conversational interaction [1].”
Kızılay, F. E., & Çelik, M. (2025) · WMU Journal of Maritime Affairs · doi:10.1007/s13437-025-00374-9 · Cited by 2
Zhao, S., & Tao, J. (2025) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste64638.2025.11091906 · Cited by 1
GenAI and effective reading among university students: Prospects, challenges, and future directions
Matto, G., Ponera, J. M., & Kyumana, V. (2025) · IJIE (Indonesian Journal of Informatics Education) · doi:10.20961/ijie.v8i2.97595 · Cited by 2
Basketball-Based Learning: An Innovative Method in English Language Learning in Elementary Schools
Hita, I., & Fatmawan, A. R. (2025) · JURNAL SOSIAL HUMANIORA · doi:10.30598/baileofisipvol2iss3pp350-364 · Cited by 1
“CAR was chosen because it allows researchers to directly identify learning problems, implement innovative solutions, and evaluate their impact in a real classroom setting (Chiu, 2024).”
Munar, L. S., Jiménez, D. A. G., Sotélo, J. A. L., & Cerón, J. V. P. (2025) · IEEE World Engineering Education Conference (EDUNINE) · doi:10.1109/edunine62377.2025.10981337 · Cited by 1
“This personalized approach helps students grasp complex engineering concepts better and apply them effectively in their projects [2].”
InfluentialManagement trends and implementation of AI in university management
Peñaloza, J. E. G., Bohórquez, A. F., & Balaguera, P. A. S. (2025) · Data & Metadata · doi:10.56294/dm2025866 · Cited by 1
Bal, S., & Tanışık, S. (2025) · ARTS Artuklu Sanat ve Beşeri Bilimler Dergisi · doi:10.46372/arts.1585826 · Cited by 2
The impact of ChatGPT on research and learning methods of university students in Ho Chi Minh City
Truong, T. D., Pham, H. Q., & Tran, Q. G. (2025) · HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - SOCIAL SCIENCES · doi:10.46223/hcmcoujs.soci.en.16.4.3835.2026
“Chiu (2024) and Taecharungroj (2023) have demonstrated that ChatGPT facilitates the development of soft skills, including writing, argumentation, and problem-solving, by providing detailed and guided feedback.”
GenAI Acceptance Modeling in Islamic Higher Education: An Integration of TAM and EVT Using PLS-SEM
Fernanda, J. W., Donasari, R., Anuraga, G., & Rahman, F. (2025) · Southeast Asian Journal of Islamic Education · doi:10.21093/sajie.v7i2.9815
“GenAI is one of the artificial intelligence technologies that can produce a variety of new and unique media, including text, graphics, audio, video, 3D models, and synthetic data (Peres et al., 2023; Chiu, 2024).”
Editorial: Impact of generative AI on teacher-student interaction
Garavaglia, A. (2024) · Research on Education and Media · doi:10.2478/rem-2024-0010 · Cited by 1
Future expectations for faculty roles at Yarmouk University in light of AI-based learning
Azam, M. F. M. A. (2024) · International Journal of ADVANCED AND APPLIED SCIENCES · doi:10.21833/ijaas.2024.11.003 · Cited by 2
Design Principles for a Higher Education Course Focusing on Lifelong Learning
Brodén, K., Johansson, J., Bergkvist, L., et al. (2024) · Electronic Journal of e-Learning · doi:10.34190/ejel.22.7.3517 · Cited by 1
Yalwa, A. S., Othman, M. S., Yusuf, L. M., & Almarshadi, M. S. (2026) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2026.0170531
“Higher levels of GenAI adoption were reported in countries such as China, the United States, and Australia, where strong institutional support, technological infrastructure, and access to AI tools have enabled early integration into programming education [1], [39], [9].”
Zhang, D.-W. (2025) · Creative Education Studies · doi:10.12677/ces.2025.134257 · Cited by 1
Tao, Y., Ryan, M., Bialy, F., & Zhang, X. (2026) · Research Square (preprint) · doi:10.21203/rs.3.rs-10029667/v1
Effects of Partial vs. Full Cognitive Offloading with Generative AI on Learning Retention
Alamri, J. M., & Alhalafawy, W. S. (2026) · International Journal of Technology in Education · doi:10.46328/ijte.8779
AI Literacy: Evaluation of an AI Literacy Course for Engineers
Benites, F., & Battegay, C. (2025) · 2025 IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon62633.2025.11016470 · Cited by 1
“In [9], the authors propose that higher education should update curricula to emphasize GenAI literacy, adaptability, and interdisciplinary approaches.”
HAICA: A framework for reasoning transparency in AI-enabled higher education assessment
Mustapha, J. C., Abdullah, M., & Kumar, G. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.103601
Jachak, S., Vispute, P., Sonar, S., Bhalerao, R., Rode, M., Shaikh, M., & Suryawanshi, M. (2026) · Next research. · doi:10.1016/j.nexres.2026.102569
Akınlar, A. (2026) · Erzincan Üniversitesi Eğitim Fakültesi Dergisi · doi:10.17556/erziefd.1932530
Al-Eissa, 1. H. H., & Aqeeli, 2. Z. M. (2026) · Journal of the Arabian Peninsula Center for Educational and Humanity Researches · doi:10.56793/pcra2213311
Vurderingspraksis i møte med generativ KI – en casestudie
Halse, L. L. (2026) · Magma · doi:10.23865/magma.v29.1595
“Si den språk mo del le ne kan pro du se re rea lis tisk og menneskelikt inn hold, har de blitt nyt ti ge verk tøy i en rek ke sam men hen ger, in klu dert ut dan ning (Chiu, 2024).”
Mendoza-Zenozain, E. A., & Córdova-Buiza, F. (2026) · Contemporary Educational Technology · doi:10.30935/cedtech/19597
AI-enabled assessment: framework, perspective and educational outcomes
Ogunleye, B., Olayinka, O., Zakariyyah, K. I., Ajao, O., & Sharma, H. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2747507
Maqsood, M., Ahmad, N., & Hussain, S. (2026) · Journal of Global Social Transformation · doi:10.71317/jgst.2.10(s).2026.817
Visions of Disciplinary and Education Futures with Generative AI
Solyst, J., Ko, A., & Shapiro, R. B. (2026) · Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1609/aies.v9i4.43315
“For example, some research advocates for a shift to interdisciplinarity and transdisciplinarity over disciplinary skills (Chiu 2024; Dianova and Schultz 2023).”
Sieciński, K., & Oliński, M. (2026) · Industry and Higher Education · doi:10.1177/09504222261498278
Addison, L. N., Elizabeth, L., & Fatqurhohman, F. (2026) · JINEA Journal of Innovation in Education and Learning · doi:10.66031/jinea.v2i3.712
“Existing reviews have examined AI in education broadly (Chen et al., 2020), AI-supported STEM education (Xu & Ouyang, 2022), intelligent tutoring systems (Lin et al., 2023), adaptive learning (Gligorea et al., 2023), and generative AI in higher education (Chiu, 2024).”
Jin, W., & Ge, Y. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1923587
“Recent research on generative artificial intelligence also examines student perceptions of potential benefits and risks (Chan and Hu, 2023; Chiu, 2024) as well as the collaborative relationship between humans and artificial intelligence (Atchley et al., 2024; Hwang and Lee, 2025).”
Higher education transformation through artificial intelligence: an empirical study in Saudi Arabia
GHUNAIM, H., & Masoud, M. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2722498
Collaborating in the age of GenAI: a mixed-methods study of model preferences
Perifanou, M. A., & Economides, A. A. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14167-x
“Recent progress in generative artificial intelligence (GenAI) large language models (LLMs) is creating new possibilities for education (Chiu, 2024; Kasneci et al., 2023).”
Generative AI in the Global South: a PLS-SEM analysis of student perceptions and intentions
Dzidzornu, A. A. K., & Xu, X. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14166-y
“Unlike conventional AI, which primarily focuses on pattern recognition and data processing, GenAI autonomously generates text, code, data, visuals, and music, fostering creativity and personalization in educational settings (Barrett & Pack, 2023 ; Chiu, 2024).”
Rizki, L. M., Kusumah, Y. S., Jupri, A., Priatna, B. A., Aridanthy, V., ., S., & Nurlita, M. (2026) · F1000Research · doi:10.12688/f1000research.180626.2
Zou, M., Pawlak, M., Kruk, M., & Wang, W. (2026) · Journal of Multilingual and Multicultural Development · doi:10.1080/01434632.2026.2734488 · Cited by 1
Adekoya, O. D., Ajonbadi, H. A., & Mordi, C. (2026) · British Journal of Educational Technology · doi:10.1111/bjet.70093
Fitriani, F. (2026) · JMM (Jurnal Masyarakat Mandiri) · doi:10.31764/jmm.v10i5.41681
“…represents the early phase of the development of research on Generative Artificial Intelligence in higher education after this technology began to be widely adopted in learning, research, and assessment activities (Batista et al., 2024; Chiu, 2024; Jensen et al., 2025; Ogunleye et al., 2024).”
InfluentialYang, Z., Yang, Y., & LIU, W. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1969743
“…should focus on translating broad institutional principles into assignment-specific expectations, including whether GenAI is permitted, which functions are acceptable, how use should be disclosed, and what evidence of independent student reasoning is required (Chiu, 2024; Faraon et al., 2025).”
Tilwani, S. A., Alhur, A., Spahiu, I., Assefa, Y., Moges, B. T., & Majeed, H. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2740687
Artificial Intelligence as A Pedagogical Assistant in Hindu Religious Learning
Sudarsini, N. N., Lestari, N., & Sugiharta, I. (2026) · Jurnal Penelitian Agama Hindu · doi:10.37329/jpah.v10i4.5703
“The transformation of education in the digital era has been accompanied by rapid developments in science and technology, including Artificial Intelligence (AI) (Chiu, 2024; Strielkowski et al., 2025).”
Artificial Intelligence-Based Blended Learning: A Mixed-Methods Study
Büyükbayraktar, F. N. (2026) · SAGE Open · doi:10.1177/21582440261500202
Pambudi, I., Majid, N. W. A., Barri, M. A. F., et al. (2026) · Recursive Journal of Informatics · doi:10.15294/rji.v4i2.64092
“Scholars examining the pedagogical promise of generative AI have emphasized its capacity to personalize instruction, scaffold problem-solving, and extend the range of tasks a learner can accomplish with appropriate support [6], [7].”
A Bibliometric Review of Global Research Trends in Pedagogy and Competence Based on Scopus Data
KAPBAROVA, G. M. (2026) · Yassawi Journal of Education Studies · doi:10.47526/3107-3123.420
Jones, K. (2026) · Journal of ExoTechnology and Education · doi:10.36615/d2zj6650
“By integrating design thinking with GenAI, students will learn to approach problems wholistically, consider user needs, and leverage AI capabilities to develop innovative solutions (Chiu, 2024; Saritepeci & Yildiz Durak, 2024).”
Prieto, M. S., González, D. G. M. D. P., & Rodrigues, T. F. (2026) · Journal of ExoTechnology and Education · doi:10.36615/cqapdr68
“This perspective supports recent calls for systemic approaches to AI integration that address organizational as well as pedagogical factors (Chiu, 2024).”
Hasan, H., Ardiansyah, M., Hermawan, N., Abeng, A. T., & Nuraisah, N. (2026) · Jurnal Pengabdian Masyarakat dan Riset Pendidikan · doi:10.31004/jerkin.v5i1.7892
“Pergeseran pemahaman ini penting, sebab riset Chiu (2024) maupun Chen dkk. (2025) menunjukkan bahwa pemanfaatan generative AI yang optimal justru terjadi ketika pengguna memahami ragam fungsi AI di luar sekadar menjawab pertanyaan langsung.”
Educators’ and students’ views on the impact of artificial intelligence in higher education
Ang, C. (2026) · Discover Education · doi:10.1007/s44217-026-02174-6
“Research has examined its influence on learning, teaching, assessment, academic integrity, staff practice, student experience, and institutional policy [8, 9].”
InfluentialHoncharuk, L. (2026) · Visnyk Taras Shevchenko National University of Kyiv Military-Special Sciences · doi:10.17721/1728-2217.2026.67.5-12
Advancing Engineering-Driven STEM Pedagogy with AI
Lu, J., & Zhou, X. (2026) · Research in Integrated STEM Education · doi:10.1163/27726673-bja00041
Dueraman, B., & Boonsuk, Y. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2026.2734840
The bright highlights and the dark shadows of artificial intelligence in higher education
Sejdiu, N. P., Rosner, M., & Sejdiu, S. (2026) · Open Research Europe · doi:10.12688/openreseurope.24951.1
Balat, Ş. (2026) · Black Sea Journal of Engineering and Science · doi:10.34248/bsengineering.1934728
AbouElgheit, E. (2026) · Learning Futures and Emerging Technologies · doi:10.1108/lfet-06-2026-0073
Generative AI and moral deskilling in vocational education: A dialectical agency perspective
Mai, A. Y., Syamsuddin, M. M., & Sairah, A. R. (2026) · Journal of Vocational Informatics and Computer Education · doi:10.66053/voice.v4i3.1221
“This is consistent with calls in the broader vocational literature for curricula and assessment that integrate digital competence with transversal reasoning and problem-solving skills rather than reward narrow technical output alone (Chiu, 2024; Kurnia et al., 2026).”
Presti, F. L., Tosto, C., Rivoltella, P. C., Allegra, M., & Gentile, M. (2026) · Education Sciences · doi:10.3390/educsci16091486
Amzalag, M., Zviel-Girshin, R., & Beimel, D. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1861548
Tezci, İ. H. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14146-2
“While the sense of control they afford may reduce anxiety and bol-1 ster self-efficacy, algorithmic uncertainty can trigger a novel form of anxiety termed “technostress” (Tarafdar et al., 2007; Chiu, 2024).”
Qu, J., Dai, L., & Yin, M. (2026) · PLoS ONE · doi:10.1371/journal.pone.0356183
“Correspondingly, scholars have argued that students need prompt-related competencies, AI literacy, and ethical understanding to translate access into meaningful learning benefits [25].”
Kamaruddin, K., Tahir, T. B., Sumardin, A., Iskandar, A., & Pratama, M. R. (2026) · Jurnal Minfo Polgan · doi:10.33395/jmp.v15i3.16709
Hao, X., Li, J., Huang, H., & Hao, B. (2026) · Sustainability · doi:10.3390/su18179084 · Cited by 1
Busthomi, M. Y. A., Nugraha, A. P., & Anwar, M. (2026) · International Journal of Post Axial Futuristic Teaching and Learning · doi:10.59944/postaxial.v4i3.1595
Rizki, L. M., Kusumah, Y. S., Jupri, A., Priatna, B. A., Aridanthy, V., ., S., & Nurlita, M. (2026) · F1000Research · doi:10.12688/f1000research.180626.1
Research trends in generative AI in higher education: A bibliometric and systematic review approach
Taqwa, M. R. A., Rahim, H. F., Muzata, K., et al. (2026) · Multidisciplinary Reviews · doi:10.31893/multirev.2027132
“Research results show that GenAI has great potential in providing feedback tailored to student needs (Escalante et al., 2023; Nikolic et al., 2023), creating a more adaptive digital environment (Chiu, 2024), and sparking ideas/concept exploration (Lee et al., 2024).”
AI as a co-driver for work-based education – an action learning and action research study
Quew-Jones, R. J., & Banger, S. (2026) · Action Learning Research and Practice · doi:10.1080/14767333.2026.2722116
“AI integration in management education offers opportunities and challenges (Valcea, Hamdani, and Wang 2024), reinforcing HEIs’ preparations for students in AI-driven work-places (Chiu 2024; Department for Education 2025).”
Singh, R. G., Chow, K. M., Dong, H., Wong, H., Fung, M., Myers, P. S., Wong, L. L. C., Lai, P., Ngai, C. S. B., Koon, A. C., et al. (2026) · Journal of English for Academic Purposes · doi:10.1016/j.jeap.2026.101729 · Cited by 2
Gang, Y., Jiang, R., & Shen, Q. (2026) · System · doi:10.1016/j.system.2026.104143
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
