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A Model and Heuristic For Solving Very Large Item Selection Problems
Open accessAbstract
A model for solving very large item selection problems is presented. The model builds on previous work in binary programming applied to test con struction. Expert test construction practices are applied to situations in which all specifications for item selection cannot necessarily be met. A heuristic for selecting items that satisfy the constraints in the model also is presented. The heuristic is particu larly useful for situations in which the size of the test construction problem exceeds the limits of current implementations of linear programming algorithms. A variety of test construction problems involving real test specifications and item data from actual test assemblies were investigated using the model and the heuristic.
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Cited by
Computerized Adaptive Testing: Theory and Practice
(2000) · Springer eBooks · doi:10.1007/0-306-47531-6 · Cited by 697
Choi, Y., & McClenen, C. (2020) · Applied Sciences · doi:10.3390/app10228196 · Cited by 90
Survey of Computerized Adaptive Testing: A Machine Learning Perspective
Zhuang, Y., Liu, Q., Bi, H., Huang, Z., Huang, W., Li, J., Yu, J., Liu, Z., Hu, Z., Hong, Y., et al. (2026) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2026.3672850 · Cited by 9
“The Weighted Deviation Model [98] manages the degree of overlap, maintaining rep-resentativeness and preventing question overexposure.”
Metadata
- Authors
- Swanson, L., & Stocking, M. L.
- Venue
- Applied Psychological Measurement
- Publisher
- SAGE Publications
- Published
- 1993-06
- Volume
- 17
- Issue
- 2
- Pages
- 151-166
- ISSN
- 0146-6216 (ISSN-L)
- 1552-3497
- OpenAlex
- W2050840393
- Cited by
- 180
- References
- 0
- FWCI
- 11.21
- Type
- journal article
- Language
- en
- Open access
- green
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- Swanson, L., & Stocking, M. L. (1993). A Model and Heuristic For Solving Very Large Item Selection Problems. Applied Psychological Measurement. https://doi.org/10.1177/014662169301700205
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