By Wim J. van der Linden, Cees A.W. Glas
Modern computing device expertise has spread out a number of new chances for optimizing the management of academic and mental exams. In machine adaptive trying out (CAT), exams are instantly adapted to the talent point of the person examinees. at present, approximately all large-scale trying out courses within the western international are already adaptive or within the strategy of turning into so. Written by way of energetic CAT researchers from Europe and North the US, the chapters provide a accomplished creation to the newest advancements within the conception and perform of CAT. The e-book can be utilized either as a simple reference at the state-of-the-art in CAT and a necessary source in graduate classes on try out conception. The theoretical chapters during this booklet disguise such issues as merchandise choice and talent estimation, merchandise pool improvement and upkeep, merchandise calibration and version healthy, and testlet-based adaptive checking out. the sensible chapters describe the operational points of latest large-scale CAT programs.
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Additional info for Computerized Adaptive Testing: Theory and Practice
M. A. (1999). Reducing bias in CAT trait estimation: A comparison of approaches. Applied Psychological Measurement, 23, 263-278. Wang, T. &, Vispoel, W. P. (1998). Properties of ability estimation methods in computerized adaptive testing. Journal of Educational Measurement, 35, 109135. Warm, T. A. (1989). Weighted likelihood estimation of ability in item response theory with tests of finite length. Psychometrika, 54, 427-450. Weiss, D. J. (1982). Improving measurement quality and efficiency with adaptive testing.
Meets all constraints) and has an optimal value for the objective function in (1) at the true ability of the examinee. Since the true ability is unknown, all one can hope for is an item-selection mechanism with a result approximating this ideal case. The proposed adaptive testing scheme has this feature; it yields feasible adaptive tests converging to the optimal value for the information function at the true ability of the examinees. This claim can be shown to hold as follows. The algorithm realizes all constraints simultaneously for each shadow test.
P. F. Item-selection criteria for adaptive testing. Journal of Educational and Behavioral Statistics, 22, 203-226. , & Braswell, J. (1991). Building algebra testlets: A comparison of hierarchical and linear structures. Journal of Educational Measurement, 28, 311-323. , Hanson, B. -M. A. (1999). Reducing bias in CAT trait estimation: A comparison of approaches. Applied Psychological Measurement, 23, 263-278. Wang, T. &, Vispoel, W. P. (1998). Properties of ability estimation methods in computerized adaptive testing.