The DOI matches its Crossref record; 86 of the 87 references it cites were found in a registry or an index.
Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020
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
“The findings show that performance prediction, resource recommendation, automatic assessment, and improvement of learning experiences are the four main functions of AI applications in online higher education.”
From Artificial intelligence in higher education: the state of the field (2023) · cites this paper as Ouyang et. al. (2022)
In the citing paper
“Extant systematic reviews on HE highlighted the use of AIEd for prediction (viz., Chu etal., 2022; Hinojo-Lucena etal., 2019; Ouyang etal., 2022; Zawacki-Richter etal., 2019).”
From Artificial intelligence in higher education: the state of the field (2023) · cites this paper as Ouyang et al., 2022
In the citing paper
“Based on such emotional signals, AI can adapt the learning environment, such as by using motivational messages or simplifying the task at moments of frustration of the learner, or gamifying when the learner is bored [216].”
From Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis (2024) · cites this paper as [216]
In the citing paper
“higher education settings are not only about promoting cognitive skills and knowledge but also play a significant role in developing learners' socio-affective skills, which are crucial for their overall well-being ([35,37]).”
Citations
Cites
(1978) · Medical Entomology and Zoology · Cited by 53,488
Three Approaches to Qualitative Content Analysis
Hsieh, H.-F., & Shannon, S. E. (2005) · Qualitative Health Research · doi:10.1177/1049732305276687 · Cited by 44,601
Graneheim, U. H., & Lundman, B. (2004) · Nurse Education Today · doi:10.1016/j.nedt.2003.10.001 · Cited by 20,772
Bibliometric Methods in Management and Organization
Zupic, I., & Čater, T. (2015) · Organizational Research Methods · doi:10.1177/1094428114562629 · Cited by 7,495
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 · cited 3×
“…are still in the 1 3 preliminary and exploratory stage, AI is proved to be positive to enhance online instruction and learning quality by offering accurate prediction, assessment and engaging students with online materials and environments (Yang et al., 2020; Zawacki-Richter et al., 2019).”
BackgroundResultWohlin, C. (2014) · Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering · doi:10.1145/2601248.2601268 · Cited by 4,234 · cited 1×
“After the screening of the full articles, the snowballing approach was performed based on the guidelines to find the articles that were not extracted by using the search strings (Wohlin, 2014).”
MethodHollan, J., Hutchins, E., & Kirsh, D. (2000) · ACM Transactions on Computer-Human Interaction · doi:10.1145/353485.353487 · Cited by 2,300
Vision, challenges, roles and research issues of Artificial Intelligence in Education
Hwang, G.-J., Xie, H., Wah, B. W., & Gašević, D. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100001 · Cited by 1,435
A Review of Artificial Intelligence (AI) in Education from 2010 to 2020
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021) · Complexity · doi:10.1155/2021/8812542 · Cited by 1,364 · cited 1×
“For instance, existing review work has summarized the trends of AIEd (Tang et al., 2021; Xie et al., 2019; Zhai et al., 2021), applications (Alyahyan & Düştegör, 2020; Hooshyar et al., 2016; Liz-Domínguez et al., 2019; Shahiri et al., 2015), theoretical paradigms (Ouyang & Jiao, 2021) and AI…”
BackgroundApplication 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
Research works printed but not linked: 4
- Holmes, W., Bialik, M., & Fadel, C. (2019). Artifificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign
- Law, N. W. Y. (2019). Human development and augmented intelligence. In The 20th international conference on artificial intelligence in education (AIED 2019). Springer. Retrieved on 2021/1/1 from https://www.sciencedirect.com/science/refhub/S2666-920X(21)00014-undefined/sref31
- Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., Prisma Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097.t001 · DOI
- Selwyn, N. (2016). Is technology good for education? Polity Press. Retrieved on 2021/1/10 from http://au.wiley.com/WileyCDA/WileyTitle/productCd-0745696465.html
Cited by
Sorted by citations
Items 801–834 of 834
AI and Emerging Technologies in Transnational Higher Education
Gupta, D., Xoliyorovich, N. X., Azizbek, I., Sotvoldiev, F., Rafikova, F., Karlibaeva, R., & Islamkulov, A. K. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-3653-2.ch001
Reconceptualizing Assessment in Higher Education
Saha, S., & Singh, M. K. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9089-5.ch001
Shi, X., Dai, T., & Zhang, G. (2026) · Journal of Teaching Innovation and Practice · doi:10.65170/jtip.v2i1.53
Liu, S., Sun, H., & Liang, Q. (2026) · Education Sciences · doi:10.3390/educsci16091544
Oliveira, T., Yaegashi, S. F. R., & Duarte, J. C. V. (2026) · Educação em Revista · doi:10.1590/0102-4698-64032t
Oliveira, T., Yaegashi, S. F. R., & Duarte, J. C. V. (2026) · Educação em Revista · doi:10.1590/0102-4698-64032
González, L. J. B. (2026) · Educational Regent Multidisciplinary Journal · doi:10.63969/gfmnyn91
Zhang, W., Gu, S., Lu, D., & Li, M. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2732232
Efficacy and ease of use of AI applications among teachers in Serbian HEIs
Šević, A., Slijepčević, M., Šević, N. P., & Nikolić, T. M. (2026) · Marketing · doi:10.5937/mkng2603191s
Literacy Demands Placed on Students in Student–GenAI Entanglements in Higher Education
Sun, Z., Dohn, N. B., & Rehm, M. (2026) · Postdigital Science and Education · doi:10.1007/s42438-026-00697-7
Enhancing Children’s Artistic Skills through AI-Generated Visual Feedback
ŞEN, Ş. N., & Şen, M. (2026) · The Elementary School Journal · doi:10.1086/743344
Pastoral AI ethics for chatbots in religious education
Papakostas, C. (2026) · Ethics and Information Technology · doi:10.1007/s10676-026-09924-y · Cited by 4
Mena, G. M. D. C. G., Elizabeth, L. A. J. E. L. A. J., Elizabeth, M. R. Y. E. M. R. Y., & Andrés, M. V. J. A. M. V. J. (2026) · Revista Multidisciplinar Ciencia y Descubrimiento · doi:10.63816/hm0cw931
Marín, F. J. S., & Legaz, A. J. C. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1947527
Sun, Y., & Li, Y. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1963259
Towards a new AI-TPACK framework: Evidence from China
Xueyi, C. H. E. N., Yu, B., Liu, X., & An, Z. (2026) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2026.100686
Lees, P., Davis-Crane, N., & Taylor, C. (2026) · Research in Post-Compulsory Education · doi:10.1080/13596748.2026.2739104
Xiong, X. B., Cao, S., Gao, T., Xu, G. Y., Hou, Y., & Li, H. (2026) · ECNU Review of Education · doi:10.1177/20965311261486478
Wang, X., & Niu, J. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1955267 · Cited by 1
Enhancing Online Education Through Hybrid Neural Networks and Deep Ensemble Models
Li, J. (2026) · International Journal of Knowledge Management · doi:10.4018/ijkm.424130
Nabiev, D. (2026) · VESTNIK OF ASTRAKHAN STATE TECHNICAL UNIVERSITY SERIES ECONOMICS · doi:10.24143/2073-5537-2026-3-78-85
Wu, S., & Sumettikoon, P. (2026) · Education Sciences · doi:10.3390/educsci16101680
Fernández, J. G., Sevilmiş, A., Sánchez, S. A., & Tsitskari, E. (2026) · Sport Business and Management An International Journal · doi:10.1108/sbm-01-2026-0020
Feeling or thinking? User aversion to AI customer service in online education
He, Y., & Huang, L. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1956842
Tiep, P. Q., & Huong, N. T. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-41314-7_21
Digital Skills Among Graphic Design Students: A Comparative Mixed-Methods Study
Buitrago, H. Y. M. (2026) · Campos en Ciencias Sociales · doi:10.15332/25006681.11864
Imam, M. (2026) · Smart innovation, systems and technologies · doi:10.1007/978-3-032-11456-3_19
Ntuli, M. L., Mpofana, N., Paulse, M., Mazibuko, G. N., & Govender, S. (2026) · JMIR Research Protocols · doi:10.2196/92990
Freitas, J., de Abreu, M. M., & Junior, L. P. P. (2026) · Revista de Gestão · doi:10.1108/rege-02-2026-0027
Mardame, S., Ramadhani, S. R., Sinaga, J., & Hevlie Winda Nazry, S. (2026) · DEIKTIS Jurnal Pendidikan Bahasa dan Sastra · doi:10.53769/deiktis.v6i4.4328
Ahmed, E. M. S., Eliewa, W. G. A., Eid, S. R., Ali, S. O., & Hassan, E. S. A. E. E. (2026) · Nursing Research and Practice · doi:10.1155/nrp/2885750
Guo, B. (2026) · International Conference on Intelligent Education and Computer Technology (IECT) · doi:10.1145/3845354.3845431
Zhong, X. (2026) · International Conference on Intelligent Education and Computer Technology (IECT) · doi:10.1145/3845354.3845549
Metadata
- Authors
- Ouyang, F., Zheng, L., & Jiao, P.
- Affiliations
- Zhejiang University (CN)
- Corresponding author
- Ouyang, Fan
- Venue
- Education and Information Technologies
- Published
- 2022-02-26
- Volume
- 27
- Issue
- 6
- Pages
- 7893-7925
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4214643205
- Semantic Scholar
- 811c64131e009de84f0d92da6cc96e824a291bd5
- Cited by
- 831
- References
- 87
- Citations by year
- 2026: 198 · 2025: 263 · 2024: 251 · 2023: 112 · 2022: 7
- FWCI
- 19.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Education and Information Technologies (publishedVersion)
- Funders
- National Natural Science Foundation of China (62177041)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- artificial intelligence in education, online higher education, online learning, learning analytics, learning outcome prediction, student satisfaction prediction, resource recommendation, automated assessment, deep learning, genetic algorithm, student engagement, academic performance
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
