AI technologies for education: Recent research & future directions
Open accessAbstract
From unique educational perspectives, this article reports a comprehensive review of selected empirical studies on artificial intelligence in education (AIEd) published in 1993–2020, as collected in the Web of Sciences database and selected AIEd-specialized journals. A total of 40 empirical studies met all selection criteria, and were fully reviewed using multiple methods, including selected bibliometrics, content analysis and categorical meta-trends analysis. This article reports the current state of AIEd research, highlights selected AIEd technologies and applications, reviews their proven and potential benefits for education, bridges the gaps between AI technological innovations and their educational applications, and generates practical examples and inspirations for both technological experts that create AIEd technologies and educators who spearhead AI innovations in education. It also provides rich discussions on practical implications and future research directions from multiple perspectives. The advancement of AIEd calls for critical initiatives to address AI ethics and privacy concerns, and requires interdisciplinary and transdisciplinary collaborations in large-scaled, longitudinal research and development efforts.
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Current gaps in GenAI in education research include addressing ethical and privacy concerns, integrating GenAI with educational theories and practices, and exploring fairness, accountability, and transparency.
“These studies suggest current gaps in GenAI in education research include addressing ethical and privacy concerns, integrating GenAI with educational theories and practices, and exploring fairness, accountability, and transparency [72–74].”
From Generative AI in Higher Education: Balancing Innovation and Integrity (2025) · cites this paper as [74]
Section 4.4 identifies ethics and privacy as unresolved issues in AI in education, and section 4.2 calls for integrating educational theory and practice into AI development. The paper addresses AI in education broadly, not specifically generative AI, and the cited passages do not identify fairness, accountability, and transparency as research gaps. (LLM, conf=0.86)
Experimental — accuracy not yet measuredA separate stream of reviews surveys GenAI's administrative, technical, and outcome-focused uses in teaching.
“A separate stream of reviews surveys GenAI's administrative, technical, and outcome-focused uses in teaching [35-38].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [38]
Section 4.2, Practical implications for AIEd (page not supplied), discusses AI applications for educators and administrators, including learning materials, assessment, feedback, and evaluation. But the review addresses AI in education broadly, not specifically generative AI, so it does not support the claim's GenAI qualification. (LLM, conf=0.85)
Experimental — accuracy not yet measuredExisting faculty development initiatives frequently emphasise tool awareness rather than supporting ethical, reflective, and process-oriented engagement with AI.
“Existing faculty development initiatives frequently emphasise tool awareness rather than supporting ethical, reflective, and process-oriented engagement with AI.”
From Ethical engagement with artificial intelligence in faculty research education: evaluation of the New Knowledge Help (NKH) approach (2026) · cites this paper as [10]
Sections 4.4 and 5 call for attention to AI ethics, and section 4.2 urges educator participation in AI development. Neither those passages nor searches for faculty development and professional development address what existing initiatives emphasise or how frequently they prioritise tool awareness over ethical, reflective, or process-oriented engagement. Page numbers were not available in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measuredCurrent faculty development programmes often introduce tools in isolation to emphasise general familiarity, rather than positioning AI as a general tool to be used across various phases of research.
“Current programmes often introduce tools in isolation to emphasise general familiarity, rather than positioning AI as a general tool to be used across various phases of research from idea generation to research dissemination [5, 7, 10].”
From Ethical engagement with artificial intelligence in faculty research education: evaluation of the New Knowledge Help (NKH) approach (2026) · cites this paper as [10]
The Abstract and §4.2 discuss AI applications in teaching and learning, while §4.3 discusses directions for AIEd research. None addresses how faculty development programmes introduce AI tools or whether they cover the research process from idea generation to dissemination. Searches for faculty training, isolated tools, and research-workflow stages found no supporting passage. (LLM, conf=0.76)
Experimental — accuracy not yet measuredMachines are far from human intelligence and emotions and cannot undertake the role of teachers.
“These outcomes highlight the fact that machines are far from human intelligence and emotions and cannot undertake the role of teachers (González-Calatayud et al., 2021;Zhang & Aslan, 2021).”
From A systematic review of literature reviews on artificial intelligence in education (AIED): a roadmap to a future research agenda (2024) · cites this paper as Zhang & Aslan, 2021
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Cites
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-019-0171-0 · Cited by 7,242 · see citing works
Kaplan, A., & Haenlein, M. (2019) · Business Horizons · doi:10.1016/j.bushor.2018.08.004 · Cited by 3,140 · see citing works
The Ethics of AI Ethics: An Evaluation of Guidelines
Hagendorff, T. (2020) · Minds and Machines · doi:10.1007/s11023-020-09517-8 · Cited by 1,911 · see citing works
Conducting Educational Design Research
McKenney, S. E., & Reeves, T. C. (2018) · Routledge eBooks · doi:10.4324/9781315105642 · Cited by 1,537 · see citing works
Application and theory gaps during the rise of artificial intelligence in education
Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100002 · Cited by 1,003 · see citing works
AI-enabled adaptive learning systems: A systematic mapping of the literature
Kabudi, T., Pappas, I., & Olsen, D. H. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100017 · Cited by 734 · see citing works
A Collection of Definitions of IntelligencePreprint
Legg, S., & Hütter, M. (2007) · arXiv (Cornell University) · doi:10.48550/arxiv.0706.3639 · Cited by 565 · see citing works
Thelwall, M. A. (2008) · Journal of Information Science · doi:10.1177/0165551507087238 · Cited by 542 · see citing works
Can artificial intelligence transform higher education?
Bates, T., Cobo, C., Mariño, O., & Wheeler, S. (2020) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-020-00218-x · Cited by 490 · see citing works
Fryer, L. K., Ainley, M., Thompson, A., Gibson, A., & Sherlock, Z. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.05.045 · Cited by 448 · see citing works
Hinojo-Lucena, F.-J., Aznar-Díaz, I., Cáceres-Reche, M.-P., & Romero-Rodríguez, J.-M. (2019) · Education Sciences · doi:10.3390/educsci9010051 · Cited by 400 · see citing works
The Ethics of AI Ethics: An Evaluation of Guidelines
Hagendorff, T. (2020) · PhilPapers (PhilPapers Foundation) · Cited by 394 · see citing works
Incorporating Ethics into Artificial Intelligence
Etzioni, A., & Etzioni, O. (2017) · The Journal of Ethics · doi:10.1007/s10892-017-9252-2 · Cited by 388 · see citing works
Gao, F., Luo, T., & Zhang, K. (2012) · British Journal of Educational Technology · doi:10.1111/j.1467-8535.2012.01357.x · Cited by 364 · see citing works
Self-citationTang, K.-Y., Chang, C.-Y., & Hwang, G.-J. (2021) · Interactive Learning Environments · doi:10.1080/10494820.2021.1875001 · Cited by 314 · see citing works
Applications of AI in education
Beck, J. E., Stern, M. K., & Haugsjaa, E. (1996) · XRDS Crossroads The ACM Magazine for Students · doi:10.1145/332148.332153 · Cited by 254 · see citing works
Zhu, M., Liu, O. L., & Lee, H.-S. (2020) · Computers & Education · doi:10.1016/j.compedu.2019.103668 · Cited by 229 · see citing works
Hung, J.-L., & Zhang, K. (2011) · Journal of Computing in Higher Education · doi:10.1007/s12528-011-9044-9 · Cited by 222 · see citing works
Self-citationWhy Not Robot Teachers: Artificial Intelligence for Addressing Teacher Shortage
Edwards, B. I., & Cheok, A. D. (2018) · Applied Artificial Intelligence · doi:10.1080/08839514.2018.1464286 · Cited by 220 · see citing works
Chui, K. T., Fung, D. C.-L., Lytras, M. D., & Lam, T. M. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.06.032 · Cited by 197 · see citing works
Hwang, G.-J., Sung, H.-Y., Chang, S.-C., & Huang, X.-C. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100003 · Cited by 183 · see citing works
Arpacı, İ. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.09.005 · Cited by 160 · see citing works
Intelligent agent supported personalization for virtual learning environments
Dongming Xu, A., & Wang, H. (2005) · Decision Support Systems · doi:10.1016/j.dss.2005.05.033 · Cited by 133 · see citing works
Preparing students for future learning with Teachable Agents
Chin, D. B., Dohmen, I. M., Cheng, B. H., Oppezzo, M. A., Chase, C. C., & Schwartz, D. L. (2010) · Educational Technology Research and Development · doi:10.1007/s11423-010-9154-5 · Cited by 119 · see citing works
Virtual worlds vs books and videos in history education
Ijaz, K., Bogdanovych, A., & Trescak, T. (2017) · Interactive Learning Environments · doi:10.1080/10494820.2016.1225099 · Cited by 106 · see citing works
Artificial intelligence-definition and practice
Simmons, A. B., & Chappell, S. G. (1988) · IEEE Journal of Oceanic Engineering · doi:10.1109/48.551 · Cited by 105 · see citing works
Lee, H., Pallant, A., Pryputniewicz, S., Lord, T., Mulholland, M., & Liu, O. L. (2019) · Science Education · doi:10.1002/sce.21504 · Cited by 100 · see citing works
Polite web-based intelligent tutors: Can they improve learning in classrooms?
McLaren, B. M., DeLeeuw, K. E., & Mayer, R. E. (2011) · Computers & Education · doi:10.1016/j.compedu.2010.09.019 · Cited by 98 · see citing works
Where is Education Heading and How About AI
Andriessen, J. E. B., & Sandberg, J. A. C. (1999) · Cited by 96 · see citing works
Walkington, C., & Bernacki, M. L. (2018) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-018-0168-1 · Cited by 91 · see citing works
SmartTutor: An intelligent tutoring system in web-based adult education
Cheung, B., Hui, L. C. K., Zhang, J., & Yiu, S. (2003) · Journal of Systems and Software · doi:10.1016/s0164-1212(02)00133-4 · Cited by 90 · see citing works
Artificial intelligence in education and assessment methods
Braiki, B. A., Harous, S., Zaki, N., & Alnajjar, F. (2020) · Bulletin of Electrical Engineering and Informatics · doi:10.11591/eei.v9i5.1984 · Cited by 79 · see citing works
Keshav, N. U., Salisbury, J. P., Vahabzadeh, A. B. N., & Sahin, N. T. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.8534 · Cited by 71 · see citing works
The Effect of Metacognitive Scaffolding for Learning by Teaching a Teachable Agent
Matsuda, N., Weng, W., & Wall, N. G. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-019-00190-2 · Cited by 71 · see citing works
Dias, S. B., Hadjileontiadou, S. J., Hadjileontiadis, L. J., & Diniz, J. A. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.05.048 · Cited by 69 · see citing works
Moridis, C. N., & Economides, A. A. (2009) · Computers & Education · doi:10.1016/j.compedu.2009.04.002 · Cited by 59 · see citing works
Challenges and Opportunities in Game Artificial Intelligence Education Using Angry Birds
Yoon, D.-M., & Kim, K.-J. (2015) · IEEE Access · doi:10.1109/access.2015.2442680 · Cited by 58 · see citing works
Mogil, J. S., Simmonds, K. P., & Simmonds, M. J. (2008) · Pain · doi:10.1016/j.pain.2008.11.012 · Cited by 56 · see citing works
The Use of Argument Maps as an Assessment Tool in Higher Education
Rapanta, C., & Walton, D. (2016) · International Journal of Educational Research · doi:10.1016/j.ijer.2016.03.002 · Cited by 55 · see citing works
Young Children Can Learn Scientific Reasoning with Teachable Agents
Chin, D. B., Dohmen, I. M., & Schwartz, D. L. (2013) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2013.24 · Cited by 54 · see citing works
Munawar, S., Toor, S. K., Aslam, M., & Hamid, M. (2018) · EURASIA Journal of Mathematics, Science and Technology Education · doi:10.29333/ejmste/85036 · Cited by 54 · see citing works
TRANSDISCIPLINARY APPROACH OF SCIENCE, TECHNOLOGY, ENGINEERING AND MATHEMATICS EDUCATION
Flogie, A., & Aberšek, B. (2015) · Journal of Baltic Science Education · doi:10.33225/jbse/15.14.779 · Cited by 54 · see citing works
Automatic Chinese Factual Question Generation
Liu, M., Rus, V., & Liu, L. (2017) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2016.2565477 · Cited by 52 · see citing works
McCarthy, K. S., Likens, A. D., Johnson, A. M., Guerrero, T. A., & McNamara, D. S. (2018) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-018-0164-5 · Cited by 50 · see citing works
Leony, D., Muñoz-Merino, P. J., Pardo, A., & Delgado Kloos, C. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.03.030 · Cited by 45 · see citing works
An approach to develop intelligent learning environments by means of immersive virtual worlds
Griol, D., Molina, J. M., & Callejas, Z. (2014) · Journal of Ambient Intelligence and Smart Environments · doi:10.3233/ais-140255 · Cited by 44 · see citing works
Loup‐Escande, É., Frenoy, R., Poplimont, G., Thouvenin, I., Gapenne, O., & Mégalakaki, O. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.05.006 · Cited by 42 · see citing works
Xiao, Y., & Hu, J. (2019) · International Journal of English Linguistics · doi:10.5539/ijel.v9n4p1 · Cited by 42 · see citing works
Gulz, A., Londos, L., & Haake, M. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00193-4 · Cited by 39 · see citing works
Artificial intelligence in education: evolution of the teaching—learning relationship
Garito, M. A. (1991) · British Journal of Educational Technology · doi:10.1111/j.1467-8535.1991.tb00050.x · Cited by 36 · see citing works
Instructing a Teachable Agent with Low or High Self-Efficacy – Does Similarity Attract?
Tärning, B., Silvervarg, A., Gulz, A., & Haake, M. (2018) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-018-0167-2 · Cited by 36 · see citing works
THE EXPLORATION OF A MACHINE LEARNING APPROACH FOR THE ASSESSMENT OF LEARNING STYLES CHANGES
Wei, Y., Yang, Q., Chen, J., & Hu, J. (2018) · Control and Intelligent Systems · doi:10.2316/journal.201.2018.3.201-2979 · Cited by 34 · see citing works
Artificial intelligence as a discursive practice: the case of embodied software agent systems
Zdenek, S. (2003) · AI & Society · doi:10.1007/s00146-003-0284-8 · Cited by 31 · see citing works
Mechanix: A natural sketch interface tool for teaching truss analysis and free-body diagrams
Atilola, O., Valentine, S., Kim, H.-H., Turner, D., McTigue, E. M., Hammond, T., & Linsey, J. (2014) · Artificial intelligence for engineering design analysis and manufacturing · doi:10.1017/s0890060414000079 · Cited by 31 · see citing works
AI in Informal Science Education: Bringing Turing Back to Life to Perform the Turing Test
Gonzalez, A. J., Hollister, J. R., DeMara, R. F., Leigh, J., Lanman, B., Lee, S.-Y., Parker, S., Walls, C., Parker, J., Wong, J., et al. (2017) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-017-0144-1 · Cited by 31 · see citing works
Modeling and Predicting the Active Video-Viewing Time in a Large-Scale E-Learning System
Xie, T., Zheng, Q., Zhang, W., et al. (2017) · IEEE Access · doi:10.1109/access.2017.2717858 · Cited by 30 · see citing works
Cutumisu, M., Chin, D. B., & Schwartz, D. L. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12796 · Cited by 29 · see citing works
Artificial Intelligence, Ethics, and Enhanced Data Stewardship
Abrams, M. E., Abrams, J., Cullen, P. B., & Goldstein, L. (2019) · IEEE Security & Privacy · doi:10.1109/msec.2018.2888778 · Cited by 28 · see citing works
From privacy to anti-discrimination in times of machine learning
Hagendorff, T. (2019) · Ethics and Information Technology · doi:10.1007/s10676-019-09510-5 · Cited by 28 · see citing works
An Advanced eLearning Environment Developed for Engineering Learners
Σαμαράκου, Μ., Fylladitakis, E. D., Früh, W., Hatziapostolou, A., & Gelegenis, J. (2015) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v10i3.4484 · Cited by 26 · see citing works
The Effect of Individualized Instruction System on the Academic Achievement Scores of Students
Bahçeci, F., & Gürol, M. (2016) · Education Research International · doi:10.1155/2016/7392125 · Cited by 24 · see citing works
Machine Learning in Gifted Education: A Demonstration Using Neural Networks
Hodges, J., & Mohan, S. (2019) · Gifted Child Quarterly · doi:10.1177/0016986219867483 · Cited by 24 · see citing works
Tang, Y., Li, Z., Wang, G., & Hu, X. (2021) · Interactive Learning Environments · doi:10.1080/10494820.2021.2010100 · Cited by 24 · see citing works
MOOCs and open education in the Global South: Challenges, successes, and opportunities
Bromber, R. F. (2020) · Distance Education · doi:10.1080/01587919.2020.1727290 · Cited by 22 · see citing works
Cognition-Based Context-Aware Cloud Computing for Intelligent Robotic Systems in Mobile Education
Zheng, J., Zhang, Q., Xu, S., et al. (2018) · IEEE Access · doi:10.1109/access.2018.2867880 · Cited by 21 · see citing works
What Is Artificial Intelligence Anyway
Kurzweil, R. (1985) · American Scientist · Cited by 20 · see citing works
Building an Educational Platform Using NLP: A Case Study in Teaching Finance
Montalvo, S., Palomo, J., & Montalvo, S. (2020) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.3217/jucs-024-10-1403 · Cited by 20 · see citing works
Köse, U., & Arslan, A. (2016) · International journal of engineering education · Cited by 19 · see citing works
Lego NXT information on test dimensionality using Kolb’s innovative learning cycle
Shih, B., Chang, C., Chen, Y.-H., Chen, C.-Y., & Liang, Y.-D. (2012) · Natural Hazards · doi:10.1007/s11069-012-0318-y · Cited by 18 · see citing works
A new fuzzy logic based career guidance system: WEB-CGS
Peker, M., Gürüler, H., Şen, B., et al. (2017) · Tehnicki vjesnik - Technical Gazette · doi:10.17559/tv-20151105201325 · Cited by 16 · see citing works
Optimists’ Creed: Brave New Cyberlearning, Evolving Utopias (Circa 2041)
Burleson, W., & Lewis, A. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0096-x · Cited by 14 · see citing works
Automation and education: III. Technology and the instructional process
Finn, J. D. (1960) · Educational Technology Research and Development · doi:10.1007/bf02713371 · Cited by 13 · see citing works
An e-Learning System for Extracting Text Comprehension and Learning Style Characteristics.
Σαμαράκου, Μ., Tsaganou, G., & Papadakis, A. E. (2018) · Educational Technology & Society · Cited by 13 · see citing works
Cung, B., Xu, D., Eichhorn, S., & Warschauer, M. (2019) · American Journal of Distance Education · doi:10.1080/08923647.2019.1582404 · Cited by 12 · see citing works
Learning Persian grammar with the aid of an intelligent feedback generator
Mirzaeian, V. R., Kohzadi, H., & Azizmohammadi, F. (2015) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2015.09.012 · Cited by 11 · see citing works
Preparing industry-ready engineers with virtual reality: recent research and future directions
Zhang, K., & Aslan, A. B. (2020) · International Journal of Smart Technology and Learning · doi:10.1504/ijsmarttl.2020.112130 · Cited by 7 · see citing works
Self-citationIntelligent Educational Assistant based on Multiagent System and Context-Aware Computing
dos Santos, F. R., & Mustaro, P. N. (2018) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2018.090437 · Cited by 6 · see citing works
Gamifying an Artificial Intelligence Course in Engineering Education
Mayoral, J. R. M., & Manresa-Yee, C. (2016) · International journal of engineering education · Cited by 5 · see citing works
Kelly, A. E., Sleeman, D. H., & Gilhooly, K. J. (1993) · International Journal of Man-Machine Studies · doi:10.1006/imms.1993.1034 · Cited by 4 · see citing works
Ahmed, S., Razzaq, A., Zeeshan, S., et al. (2018) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2018.090334 · Cited by 4 · see citing works
MOOCs and Open Education in the Global South
Zhang, K., Bonk, C. J., Reeves, T. C., et al. (2019) · Routledge eBooks · doi:10.4324/9780429398919-1 · Cited by 4 · see citing works
Self-citationAn Augmented-Reality-Based Intelligent Mobile Application for Open Computer Education
Köse, U. (2017) · Advances in educational technologies and instructional design book series · doi:10.4018/978-1-5225-2110-5.ch008 · Cited by 2 · see citing works
Preparing industry-ready engineers with virtual reality: recent research and future directions
Zhang, K., & Aslan, A. B. (2020) · International Journal of Smart Technology and Learning · doi:10.1504/ijsmarttl.2020.10034259 · Cited by 1 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 3
- Aiken, R. M., & Epstein, R. G. (2000). Ethical guidelines for AI in education: Starting a conversation. International Journal of Artificial Intelligence in Education, 11, 163-176.
- Romero, C., & Ventura, S. (2013). In Data mining in education. Wiley interdisciplinary reviews: Data mining and knowledge discovery (Vol. 3, pp. 12-27), 1.
- Roschelle, J., Lester, J., & Fusco, J. (Eds.). (2020). AI and the future of learning: Expert panel report [Report]. Digital Promise. https://circls.org/reports/ai-report.
Cited by
Sorted by citations
Bhutoria, A. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100068 · Cited by 677 · see citing works
Chatbots in Education and Research: A Critical Examination of Ethical Implications and Solutions
Kooli, C. (2023) · Sustainability · doi:10.3390/su15075614 · Cited by 666 · see citing works
A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education
Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00468-z · Cited by 493 · see citing works
Artificial intelligence in teaching and teacher professional development: A systematic review
Tan, X., Cheng, G., & Ling, M. H. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100355 · Cited by 420 · see citing works
Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis
Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00420-7 · Cited by 413 · see citing works
Artificial intelligence in early childhood education: A scoping review
Su, J., & Yang, W. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100049 · Cited by 357 · see citing works
Artificial intelligence applications in Latin American higher education: a systematic review
Salas-Pilco, S. Z., & Yang, Y. (2022) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-022-00326-w · Cited by 330 · see citing works
Tiwari, C. K., Bhat, M. A., Khan, S. T., Subramaniam, R., & Khan, M. A. I. (2024) · Interactive Technology and Smart Education · doi:10.1108/itse-04-2023-0061 · Cited by 315 · see citing works
Human-centred learning analytics and AI in education: A systematic literature review
Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100215 · Cited by 281 · see citing works
Generative AI in Higher Education: Balancing Innovation and Integrity
Francis, N. J., Jones, S., & Smith, D. P. (2025) · British Journal of Biomedical Science · doi:10.3389/bjbs.2024.14048 · Cited by 295 · see citing works
“These studies suggest current gaps in GenAI in education research include addressing ethical and privacy concerns, integrating GenAI with educational theories and practices, and exploring fairness, accountability, and transparency [72 – 74].”
Cain, W. (2024) · TechTrends · doi:10.1007/s11528-023-00896-0 · Cited by 232 · see citing works
Shahzad, M. F., Xu, S., & Zahid, H. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-12949-9 · Cited by 204 · see citing works
Zheng, L., Niu, J., Zhong, L., & Gyasi, J. F. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2021.2015693 · Cited by 183 · see citing works
Al-Abdullatif, A. M. (2024) · Education Sciences · doi:10.3390/educsci14111209 · Cited by 169 · see citing works
- Retracted
Sharma, S., Mittal, P., Kumar, M., & Bhardwaj, V. (2025) · Discover Sustainability · doi:10.1007/s43621-025-01094-z · Cited by 165 · see citing works
Li, T., Ji, Y., & Zhan, Z. (2024) · Asia Pacific Journal of Education · doi:10.1080/02188791.2024.2305163 · Cited by 133 · see citing works
Guo, S., Zheng, Y., & Zhai, X. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12491-8 · Cited by 117 · see citing works
Hwang, W.-Y., Nurtantyana, R., Purba, S. W. D., Hariyanti, U., Indrihapsari, Y., & Surjono, H. D. (2023) · Journal of Educational Computing Research · doi:10.1177/07356331221137253 · Cited by 104 · see citing works
Gustilo, L., Ong, E., & Lapinid, M. R. (2024) · International Journal for Educational Integrity · doi:10.1007/s40979-024-00153-8 · Cited by 89 · see citing works
The Emerging Role of Artificial Intelligence in STEM Higher Education: A Critical Review
Nagaraj, B. K., A, K., R, S. B., S, A., Sachdev, H. K., & N, S. K. (2023) · International Research Journal of Multidisciplinary Technovation · doi:10.54392/irjmt2351 · Cited by 86 · see citing works
Chen, A., Zhang, Y., Jia, J., Liang, M., Cha, Y., & Lim, C. P. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.13064 · Cited by 67 · see citing works
Tang, Q., Deng, W., Huang, Y., Wang, S., & Zhang, H. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70027 · Cited by 55 · see citing works
Marzano, D. (2026) · Technology, Knowledge and Learning · doi:10.1007/s10758-025-09853-7 · Cited by 51 · see citing works
Influence of artificial intelligence tools on higher order thinking skills: a meta-analysis
Ilgun Dibek, M., Sahin Kursad, M., & Erdogan, T. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2024.2402028 · Cited by 45 · see citing works
A Synthesis of AI in higher education: Shaping the future
Jacques, P. H., Moss, H. K., & Garger, J. (2024) · Journal of Behavioral and Applied Management · doi:10.21818/001c.122146 · Cited by 43 · see citing works
Gaber, S. A., Shahat, H. A., Alkhateeb, I. A., Al Hasan, S. A., Alqatam, M. A., Almughyirah, S. M., & Kamel, M. K. (2023) · International Journal of Learning, Teaching and Educational Research · doi:10.26803/ijlter.22.7.25 · Cited by 39 · see citing works
Lin, X., & Tan, H. (2025) · Systems · doi:10.3390/systems13100840 · Cited by 22 · see citing works
Kowitlawakul, Y., Tan, J. J. M., Suebnukarn, S., Nguyen, H. D., Poo, D. C. C., Chai, J., Kamala, D. M., & Wang, W. (2024) · CIN: Computers, Informatics, Nursing · doi:10.1097/cin.0000000000001103 · Cited by 10 · see citing works
Anderson, O. S., Laubepin, F. A., & August, E. T. (2024) · Pedagogy in Health Promotion · doi:10.1177/23733799241246954 · Cited by 8 · see citing works
Seung, Y., Basham, J. D., Kim, T., & Lohoefener, J. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70144 · Cited by 7 · see citing works
Samala, A. D., & Rawas, S. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2025.2554987 · Cited by 5 · see citing works
Gulen, H. N., & Kucuk, S. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14020-1 · Cited by 3 · see citing works
Naeem, N.-I.-K., Naeem, Z.-E.-F., & Anwer, A. (2026) · BMC Medical Education · doi:10.1186/s12909-026-09405-2
“Current programmes often introduce tools in isolation to emphasise general familiarity, rather than positioning AI as a general tool to be used across various phases of research from idea generation to research dissemination [5, 7, 10].”
- Authors
- Zhang, K., & Aslan, A. B.
- Affiliations
- Wayne State University (US)
- Eastern Michigan University (US)
- Corresponding author
- Zhang, Ke
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2021
- Volume
- 2
- Pages
- 100025
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W3167554351
- Cited by
- 923
- References
- 83
- Citations by year
- 2026: 195 · 2025: 299 · 2024: 285 · 2023: 107 · 2022: 30 · 2021: 7
- FWCI
- 97.33
- Type
- journal article
- Language
- en
- 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, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- artificial intelligence in education, AI ethics, privacy concerns, interdisciplinary collaboration, transdisciplinary research, future research directions
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