01341nas a2200133 4500008003900000245010900039210006900148300001200217490000700229520088900236100001801125700001901143856004501162 2019 d00aItem Selection Criteria With Practical Constraints in Cognitive Diagnostic Computerized Adaptive Testing0 aItem Selection Criteria With Practical Constraints in Cognitive  a335-3570 v793 aFor item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized weighted deviation global discrimination index (SWDGDI), and subsequently formulated the constrained progressive index (CP\_SWDGDI) by casting the SWDGDI in a progressive algorithm. A simulation study revealed that the SWDGDI method was effective in balancing attribute coverage and the CP\_SWDGDI method was able to simultaneously balance attribute coverage and item pool usage while maintaining acceptable estimation precision. This research also demonstrates the advantage of a relatively low number of attributes in CD-CAT applications.1 aLin, Chuan-Ju1 aChang, Hua-Hua uhttps://doi.org/10.1177/001316441879063401331nas a2200121 4500008003900000245010900039210006900148300002100217520088900238100001801127700001901145856004501164 2018 d00aItem Selection Criteria With Practical Constraints in Cognitive Diagnostic Computerized Adaptive Testing0 aItem Selection Criteria With Practical Constraints in Cognitive  a00131644187906343 aFor item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized weighted deviation global discrimination index (SWDGDI), and subsequently formulated the constrained progressive index (CP\_SWDGDI) by casting the SWDGDI in a progressive algorithm. A simulation study revealed that the SWDGDI method was effective in balancing attribute coverage and the CP\_SWDGDI method was able to simultaneously balance attribute coverage and item pool usage while maintaining acceptable estimation precision. This research also demonstrates the advantage of a relatively low number of attributes in CD-CAT applications.1 aLin, Chuan-Ju1 aChang, Hua-Hua uhttps://doi.org/10.1177/001316441879063402154nas a2200145 4500008004100000245005100041210005100092260005500143520166100198653002301859653002001882100001901902700001301921856007401934 2017 eng d00aItem Parameter Drifting and Online Calibration0 aItem Parameter Drifting and Online Calibration aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Item calibration is a part of the most important topics in item response theory (IRT). Since many largescale testing programs have switched from paper and pencil (P&P) testing mode to computerized adaptive testing (CAT) mode, developing methods for efficiently calibrating new items have become vital. Among many proposed item calibration processes in CAT, online calibration is the most cost-effective. This presentation introduces an online (re)calibration design to detect item parameter drift for computerized adaptive testing (CAT) in both unidimensional and multidimensional environments. Specifically, for online calibration optimal design in unidimensional computerized adaptive testing model, a two-stage design is proposed by implementing a proportional density index algorithm. For a multidimensional computerized adaptive testing model, a four-quadrant online calibration pretest item selection design with proportional density index algorithm is proposed. Comparisons were made between different online calibration item selection strategies. Results showed that under unidimensional computerized adaptive testing, the proposed modified two-stage item selection criterion with the proportional density algorithm outperformed the other existing methods in terms of item parameter calibration and item parameter drift detection, and under multidimensional computerized adaptive testing, the online (re)calibration technique with the proposed four-quadrant item selection design with proportional density index outperformed other methods.

Session Video

10aonline calibration10aParameter Drift1 aChang, Hua-Hua1 aGuo, Rui uhttp://www.iacat.org/item-parameter-drifting-and-online-calibration-0