The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Educational Data Mining and Learning Analytics
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Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
The proof and measurement of association between two things
Spearman, C. (1904) · The American Journal of Psychology · doi:10.2307/1412159 · Cited by 8,039
Finding Groups in Data: An Introduction to Cluster Analysis
Kaufman, L., & Rousseeuw, P. J. (1990) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316801 · Cited by 7,344
Causation, Prediction, and Search
Spirtes, P., Glymour, C., & Scheines, R. (2001) · doi:10.7551/mitpress/1754.001.0001 · Cited by 4,521
Strobl, C., Malley, J., & Tutz, G. (2009) · Psychological Methods · doi:10.1037/a0016973 · Cited by 2,583
Knowledge tracing: Modeling the acquisition of procedural knowledge
Corbett, A. T., & Anderson, J. R. (1995) · User Modelling and User-Adapted Interaction · doi:10.1007/bf01099821 · Cited by 2,324
Educational Data Mining: A review of the state of the art
Romero, C., & Ventura, S. (2010) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2010.2053532 · Cited by 2,251
Schmidt, R. A., & Bjork, R. A. (1992) · Psychological Science · doi:10.1111/j.1467-9280.1992.tb00029.x · Cited by 1,582
The interplay of evidence and consequences in the validation of performance assessments
Messick, S. (1994) · Educational Researcher · doi:10.3102/0013189x023002013 · Cited by 1,315
Cited by
Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review
Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., & Tudorache, P. (2023) · Education Sciences · doi:10.3390/educsci13121216 · Cited by 980
Utilising learning analytics to support study success in higher education: a systematic review
Ifenthaler, D., & Yau, J. Y.-K. (2020) · Educational Technology Research and Development · doi:10.1007/s11423-020-09788-z · Cited by 659
Big Data and analytics in higher education: Opportunities and challenges
Daniel, B. (2015) · British Journal of Educational Technology · doi:10.1111/bjet.12230 · Cited by 610
Stupid tutoring systems, intelligent humans
Baker, R. S. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0105-0 · Cited by 425
Self-citationAzevedo, R. (2015) · Educational Psychologist · doi:10.1080/00461520.2015.1004069 · Cited by 418
Metadata
- Authors
- Baker, R. S., & Inventado, P. S.
- Venue
- Learning Analytics
- Publisher
- Springer New York
- Published
- 2014
- Pages
- 61-75
- OpenAlex
- W1898103075
- Cited by
- 1,029
- References
- 16
- FWCI
- 150.75
- Type
- book chapter
- Language
- en
- Open access
- closed
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- Baker, R. S., & Inventado, P. S. (2014). Educational Data Mining and Learning Analytics. Learning Analytics. https://doi.org/10.1007/978-1-4614-3305-7_4
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.