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Item Response Theory
Veldkamp, B. P., van der Linden, W. J., & Ariel, A.. (2002). Mathematical-programming approaches to test item pool design (No. RR 02-09) (pp. 93-108). Twente, The Netherlands: University of Twente, Faculty of Educational Science and Technology.
Guzmán, E., Conejo, R., & García-Hervás, E.. (2005). An Authoring Environment for Adaptive Testing. Educational Technology & Society, 8(3), 66-76.
item selection
van Groen, M., Eggen, T., & Veldkamp, B.. (2011). Item Selection Methods based on Multiple Objective Approaches for Classification of Respondents into Multiple Levels. In Annual Conference of the International Association for Computerized Adaptive Testing. presented at the 10/2011.
PDF icon IACAT 2011 van Groen Eggen Veldkamp Item Selection.pdf (593.82 KB)
Tang, K. L. (1996). A comparison of the traditional maximum information method and the global information method in CAT item selection. In annual meeting of the National Council on Measurement in Education. New York, NY USA.
Finkelman, M., & Wang, C.. (2019). Time-Efficient Adaptive Measurement of Change. Journal of Computerized Adaptive Testing, 7(2), 15-34. doi:10.7333/1909-0702015
van Buuren, N., Straat, H., Eggen, T., & Fox, J. - P.. (2017). Adaptive Item and Feedback Selection in Personalized Learning with a Network Approach. In IACAT 2017 Conference. presented at the 08/2017, Niigata, Japan: Niigata Seiryo University.
item selection strategies
Chandra, I. (2017). Item Selection Strategies for Developing CAT in Indonesia. In IACAT 2017 Conference. presented at the 08/2017, Niigata Japan: Niiagata Seiryo University. Retrieved from https://www.youtube.com/watch?v=2KuFrRATq9Q
item-selection strategies
Revuelta, J. (2004). Estimating ability and item-selection strategy in self-adapted testing: A latent class approach. Journal of Educational and Behavioral Statistics, 29, 379-396.
Keynote
Kingsbury, G., & Zara, T.. (2017). From Blueprints to Systems: An Integrated Approach to Adaptive Testing. In IACAT 2017 Conference. presented at the 08/2017, Niigata, Japan: Niigata Seiryo University. Retrieved from https://drive.google.com/open?id=1CBaAfH4ES7XivmvrMjPeKyFCsFZOpQMJ
knowledge-based model construction
Levy, R., Behrens, J. T., & Mislevy, R. J.. (2023). An Extended Taxonomy of Variants of Computerized Adaptive Testing. Journal of Computerized Adaptive Testing, 10(1). doi:10.7333/2302-100101
Kullback-Leibler divergence
Belov, D. I. (2014). Detecting Item Preknowledge in Computerized Adaptive Testing Using Information Theory and Combinatorial Optimization. Journal of Computerized Adaptive Testing, 2(3), 37-58. doi:10.7333/1410-0203037
Kullback-Leibler information
van Buuren, N., & Eggen, T. J. H. M.. (2017). Latent-Class-Based Item Selection for Computerized Adaptive Progress Tests. Journal of Computerized Adaptive Testing, 5(2), 22-43. doi:10.7333/1704-0502022
Kullback–Leibler information
Finkelman, M. D., Weiss, D. J., & Kim-Kang, G.. (2010). Item Selection and Hypothesis Testing for the Adaptive Measurement of Change. Applied Psychological Measurement, 34(4), 238-254. doi:10.1177/0146621609344844
language testing
Yuyu, L., Chenglin, Z., & Jie, R.. (2017). MHK-MST Design and the Related Simulation Study. In IACAT 2017 Conference. presented at the 08/2017, Niigata, Japan: Niigata Seiryo University.
Imai, S. (2017). Is CAT Suitable for Automated Speaking Test?. In IACAT 2017 Conference. presented at the 08/2017, Niigata, Japan: Niigata Seiryo University.
Large-Scale tests
Bulut, O., & Cormier, D.. (2017). A Large-Scale Progress Monitoring Application with Computerized Adaptive Testing. In IACAT 2017 Conference. presented at the 08/2017, Niigata, Japan: Niigata Seiryo University. Retrieved from https://drive.google.com/open?id=1uGbCKenRLnqTxImX1fZicR2c7GRV6Udc
Latent class analysis
van Buuren, N., & Eggen, T. J. H. M.. (2017). Latent-Class-Based Item Selection for Computerized Adaptive Progress Tests. Journal of Computerized Adaptive Testing, 5(2), 22-43. doi:10.7333/1704-0502022
Licensure
Gershon, R. C. (2005). Computer adaptive testing. Journal of Applied Measurement, 6, 109-27.
Licensure, Pharmacy/history/*legislation & jurisprudence
Newton, D. W., Boyle, M., & Catizone, C. A.. (2008). The NAPLEX: evolution, purpose, scope, and educational implications. American Journal of Pharmaceutical Education, 72, 33. presented at the Apr 15.
likelihood ratio
Finkelman, M. D., Weiss, D. J., & Kim-Kang, G.. (2010). Item Selection and Hypothesis Testing for the Adaptive Measurement of Change. Applied Psychological Measurement, 34(4), 238-254. doi:10.1177/0146621609344844
Likert scales
Hol, A. M., Vorst, H. C. M., & Mellenbergh, G. J.. (2008). Computerized Adaptive Testing of Personality Traits. Zeitschrift für Psychologie / Journal of Psychology, 216(1), 12-21. doi:10.1027/0044-3409.216.1.12
PDF icon Computerized Adaptive Testing of Personality Traits.pdf (518.72 KB)
Linear Models
Morin, M. (2017). Adapting Linear Models for Optimal Test Design to More Complex Test Specifications. In IACAT 2017 Conference. presented at the 08/2017, Niigata, Japan: Niigata Seiryo University.
PDF icon ga02812.pdf (131.16 KB)
Linear programming
Edmonds, J., & Armstrong, R. D.. (2009). A mixed integer programming model for multiple stage adaptive testing. European Journal of Operational Research, 193, 342-350.
Literacy
Balajthy, E. (2002). Information technology and literacy assessment. Reading and Writing Quarterly, 18, 369-373.
local equating
van der Linden, W. J. (2006). Equating scores from adaptive to linear tests. Applied Psychological Measurement, 30, 493-508.
log-odds scoring
van Buuren, N., & Eggen, T. J. H. M.. (2017). Latent-Class-Based Item Selection for Computerized Adaptive Progress Tests. Journal of Computerized Adaptive Testing, 5(2), 22-43. doi:10.7333/1704-0502022

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