The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Personalized e-learning system using Item Response Theory
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Citations
Cites
(1999) · Cited by 12,854
(1932) · Medical Entomology and Zoology · Cited by 9,568
Applications of Item Response Theory To Practical Testing Problems
Lord, F. M. (2012) · Routledge eBooks · doi:10.4324/9780203056615 · Cited by 5,007
Fundamentals of item response theory
(1992) · Choice Reviews Online · doi:10.5860/choice.29-4185 · Cited by 3,414
Fab: content-based, collaborative recommendation
Balabanović, M., & Shoham, Y. (1997) · Communications of the ACM · doi:10.1145/245108.245124 · Cited by 2,934
Probability and Statistics for Engineers and Scientists.
Beckman, R. J., Walpole, R. E., & Meyers, R. H. (1973) · Journal of the American Statistical Association · doi:10.2307/2284195 · Cited by 2,835
Authoritative sources in a hyperlinked environment
Kleinberg, J. M. (1998) · Symposium on Discrete Algorithms · doi:10.5555/314613.315045 · Cited by 1,814
Item Response Theory: Principles and Applications
Hambleton, R. K., & Swaminathan, H. (1984) · Medical Entomology and Zoology · Cited by 1,779
The basics of item response theory
Baker, F. B. (1985) · Cited by 1,362
Automatic personalization based on Web usage mining
Mobasher, B., Cooley, R., & Srivastava, J. (2000) · Communications of the ACM · doi:10.1145/345124.345169 · Cited by 1,223
Cited by
Intelligent tutoring systems and learning outcomes: A meta-analysis
Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014) · Journal of Educational Psychology · doi:10.1037/a0037123 · Cited by 840
Xie, H., Chu, H.-C., Hwang, G.-J., & Wang, C.-C. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.103599 · Cited by 713
Artificial intelligence innovation in education: A twenty-year data-driven historical analysis
Guan, C., Mou, J., & Jiang, Z. (2020) · International Journal of Innovation Studies · doi:10.1016/j.ijis.2020.09.001 · Cited by 665
A systematic literature review of personalized learning terms
Shemshack, A., & Spector, J. M. (2020) · Smart Learning Environments · doi:10.1186/s40561-020-00140-9 · Cited by 740
“For example, while Chen, Lee and Chen (2005) proposed a personalized system that provides learning paths (Nabizadeh, Gonçalves, Gama, Jorge and Rafsanjani, 2020) that can be adapted to various levels of difficulty of course materials (Zou and Xie, 2018) and various abilities of learners (p. 239).”
BackgroundBaylari, A., & Montazer, G. A. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.10.080 · Cited by 182
Metadata
- Authors
- Chen, C.-M., Lee, H.-M., & Chen, Y.-H.
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2005-04
- Volume
- 44
- Issue
- 3
- Pages
- 237-255
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W2162283255
- Cited by
- 482
- References
- 31
- FWCI
- 10.85
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, C.-M., Lee, H.-M., & Chen, Y.-H. (2005). Personalized e-learning system using Item Response Theory. Computers & Education. https://doi.org/10.1016/j.compedu.2004.01.006
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.
