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Drasgow, F. (2002). The work ahead: A psychometric infrastructure for computerized adaptive tests. In M. P. Potenza, Freemer, J. J., & Ward, W. C., Computer-based tests: Building the foundation for future assessment. Mahwah, N.J. USA: Lawrence Erlbaum Associates, Inc.
McBride, J. R., & Weiss, D. J.. (1974). A word knowledge item pool for adaptive ability measurement (Research Report 74-2). Minneapolis MN: Department of Psychology, Computerized Adaptive Testing Laboratory.
PDF icon mcb74-02.pdf (3.78 MB)
McBride, J. R. (1991). What lies ahead? Computer technology and its implications for personnel testing. In Keynote address. NATO Workshop on Computer-based Assessment of Military Personnel, Brussels, Belgium.
Sari, H. Ibrahim, & Raborn, A.. (2018). What Information Works Best?: A Comparison of Routing Methods. Applied Psychological Measurement, 42, 499-515. doi:10.1177/0146621617752990
Laurier, M. (1990). What can we do with computerized adaptive testing and what we cannot do? . In Paper presented at the annual meeting of the Regional Language Center Seminar.
Gialluca, K. A. (2011). Walking the Tightrope: Using Better Content Control to Improve CAT. In Annual Conference of the International Association for Computerized Adaptive Testing. presented at the 10/2011.
PDF icon IACAT 2011 Gialluca Content Control in CAT.pdf (131.56 KB)
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Finkelman, M. D. (2010). Variations on Stochastic Curtailment in Sequential Mastery Testing. Applied Psychological Measurement, 34, 27-45. doi:10.1177/0146621609336113
Hsu, C. - L., & Wang, W. - C.. (2015). Variable-Length Computerized Adaptive Testing Using the Higher Order DINA Model. Journal of Educational Measurement, 52, 125–143. doi:10.1111/jedm.12069
Hsu, C. - L., Wang, W. - C., & Chen, S. - Y.. (2013). Variable-Length Computerized Adaptive Testing Based on Cognitive Diagnosis Models. Applied Psychological Measurement, 37, 563-582. doi:10.1177/0146621613488642
Hornke, L. F., & Sauter, M. B.. (1980). A validity study of an adaptive test of reading comprehension. In . D. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 57-67). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.
PDF icon ho80-01.pdf (675.09 KB)
Jensema, C. J. (1974). The validity of Bayesian tailored testing. Educational and Psychological Measurement, 34, 757-756.
Sympson, J. B., & Moreno, K. E.. (1985). Validity of adaptive testing: A summary of research results. In Paper presented at the annual meeting of the American Psychological Association.
Huff, K. L., & Sireci, S. G.. (2001). Validity issues in computer-based testing. Educational Measurement: Issues and Practice, 20(3), 16-25.
Kingsbury, G. G., & Weiss, D. J.. (1981). A validity comparison of adaptive and conventional strategies for mastery testing (Research Report 81-3). Minneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.
PDF icon ki81-03.pdf (1.81 MB)
Olsen, J. B., & Bunderson, C. V.. (2007). Validity and decision issues in selecting a CAT measurement model. In . D. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.
PDF icon cat07olsen.pdf (976.11 KB)
Steinberg, L., Thissen, D., & Wainer, H.,. (1990). Validity. In . H. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 187-231). Hillsdale NJ: Erlbaum.
Segall, D. O., Moreno, K. E., Kieckhaefer, W. F., Vicino, F. L., & McBride, J. R.. (1997). Validation of the experimental CAT-ASVAB system. In . W. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation. Washington, DC: American Psychological Association.
Nandakumar, R., & Roussos, L. A.. (1997). Validation of CATSIB To investigate DIF of CAT data. In annual meeting of the American Educational Research Association. Chicago, IL. USA.
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Thompson, N. A. (2009). Utilizing the generalized likelihood ratio as a termination criterion. In . D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.
PDF icon cat09thompson.pdf (193.51 KB)
Sie, H., Finkelman, M. D., Riley, B., & Smits, N.. (2015). Utilizing Response Times in Computerized Classification Testing. Applied Psychological Measurement, 39, 389-405. doi:10.1177/0146621615569504
De Beer, M. (2002). Utility of Learning Potential Computerised Adaptive Test (LPCAT) scores in predicting academic performance of bridging students: A comparison with other predictors. In Paper presented at the 5th Annual Society for Industrial and Organisational Psychology Congress. Pretoria, South Africa.
Fan, M., & Hsu, Y.. (1996). Utility of Fisher information, global information and different starting abilities in mini CAT. In Paper presented at the Annual Meeting of the National Council on Measurement in Education. New York NY.
Wise, S. L. (2014). The Utility of Adaptive Testing in Addressing the Problem of Unmotivated Examinees. Journal of Computerized Adaptive Testing, 2(1), 1-17. doi:10.7333/1401-02010001
Raîche, G.. (1994). Utilisation de la simulation en tant que méthodologie de recherche [Simulation methodology in research]. In . Association pour la recherche au collégial (Ed.) : L'en-quête de la créativité [In quest of creativity]. Proceeding of the 6th Congress of the ARC. Montréal: Association pour la recherche au collégial (ARC).
Lau, C. A., Abdel-Fattah, A. A., & Spray, J. A.. (1996). Using unidimensional IRT models for dichotomous classification via CAT with multidimensional data. In Poster session presented at the annual meeting of the American Educational Research Association. Boston MA.
Williamson, D. M., & Bejar, I. I.. (2002). Using testlet response theory to evaluate the equivalence of automatically generated multiple-choice items. In Symposium conducted at the annual meeting of the National Council on Measurement in Eucation. New Orleans LA.
Finkelman, M. D. (2008). On using stochastic curtailment to shorten the SPRT in sequential mastery testing. Journal of Educational and Behavioral Statistics, 33, 442.
Huitzing, H. A. (2004). Using Set Covering with Item Sampling to Analyze the Infeasibility of Linear Programming Test Assembly Models. Applied Psychological Measurement, 28, 355-375. doi:10.1177/0146621604266152
van der Linden, W. J., Scrams, D. J., & Schnipke, D. L.. (1998). Using response-time constraints to control for differential speededness in adaptive testing (Research Report 98-06). Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis.
van der Linden, W. J., & van Krimpen-Stoop, E. M. L. A.. (2000). Using response times to detect aberrant behavior in computerized adaptive testing (Research Report 00-09). Enschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis.
van der Linden, W. J., & van Krimpen-Stoop, E. M. L. A.. (2001). Using response times to detect aberrant behavior in computerized adaptive testing. In Paper presented at the annual meeting of the National Council on Measurement in Education. Seattle WA.
van der Linden, W. J. (2008). Using response times for item selection in adaptive testing. Journal of Educational and Behavioral Statistics, 33, 5–20.
H., Q., Staniewska, D., Reckase, M., & Woo, A.. (2016). Using Response Time to Detect Item Preknowledge in Computer?Based Licensure Examinations. Educational Measurement: Issues and Practice., 35(1). doi:http://dx.doi.org/10.1111/emip.12102
Wei, H., & Lin, J.. (2015). Using Out-of-Level Items in Computerized Adaptive Testing. International Journal of Testing, 15(1). doi:http://dx.doi.org/10.1080/15305058.2014.979492
Yao, L., Pommerich, M., & Segall, D. O.. (2014). Using Multidimensional CAT to Administer a Short, Yet Precise, Screening Test. Applied Psychological Measurement, 38, 614-631. doi:10.1177/0146621614541514
Millman, J. (1984). Using microcomputers to administer tests: An alternate point of view. Educational Measurement: Issues and Practice, 3(2), 20-21.
Ward, W. C. (1984). Using microcomputers to administer tests. Educational Measurement: Issues and Practice, 3(2), 16-20.

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