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Cited by 834Artificial Intelligence in EducationOnline Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

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

Ouyang, Fan, Zheng, Luyi, Jiao, Pengcheng·2022·Education and Information Technologies
DOI 10.1007/s10639-022-10925-9
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Crossref · 10.1007/s10639-022-10925-9

Cites

86 of 86 references verified0 citation errors · 0 not checkable

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Verification

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Citations

Cites

Show all 87 references

Research works printed but not linked: 4

  1. Holmes, W., Bialik, M., & Fadel, C. (2019). Artifificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign
  2. 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
  3. 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
  4. 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

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Metadata

Authors
Ouyang, F., Zheng, L., & Jiao, P.
Affiliations
Zhejiang University (CN)
Corresponding author
Ouyang, Fan
ORCID
Venue
Education and Information Technologies
Publisher
Springer Science and Business Media LLC
Published
2022-02-26
Volume
27
Issue
6
Pages
7893-7925
ISSN
  • 1360-2357 (ISSN-L)
  • 1573-7608
DOI
10.1007/s10639-022-10925-9
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
Licence
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

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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.

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