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    A blocked-CAT procedure for CD-CAT
    (SAGE Publications Inc., 2020) Kaplan, Mehmet; de la Torre, Jimmy
    This article introduces a blocked-design procedure for cognitive diagnosis computerized adaptive testing (CD-CAT), which allows examinees to review items and change their answers during test administration. Four blocking versions of the new procedure were proposed. In addition, the impact of several factors, namely, item quality, generating model, block size, and test length, on the classification rates was investigated. Three popular item selection indices in CD-CAT were used and their efficiency compared using the new procedure. An additional study was carried out to examine the potential benefit of item review. The results showed that the new procedure is promising in that allowing item review resulted only in a small loss in attribute classification accuracy under some conditions. Moreover, using a blocked-design CD-CAT is beneficial to the extent that it alleviates the negative impact of test anxiety on examinees’ true performance.
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    Expert-based attribute identification and validation on fraction subtraction: A cognitively diagnostic assessment application
    (Sriwijaya University, 2018) Akbay, Lokman; Terzi, Ragip; Kaplan, Mehmet; Karaaslan, Katibe Gizem
    In this study, we describe the methodology used to identify and validate a set of expert-defined fraction subtraction related attributes. These attributes are expected to be mastered by 6th grade students toward proficiency in fraction subtraction. This research argues and demonstrates that state standards guiding subject instruction plays an important role in the identification of the domain related fundamental attributes. This study also illustrates complete implementation of cognitive diagnosis model framework, which is used to extract diagnostic information about students' specific strengths and weaknesses.
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    The impact of attribute size on the performance of item selection algorithms
    (Assoc Measurement & Evaluation Education & Psychology, Assoc Measurement & Evaluation Education & Psychology, 2016) Kaplan, Mehmet
    The use of cognitive diagnosis models (CDMs) and computerized adaptive testing (CAT) has been increasing in both education and other fields such as psychology. To date, most of the research in CAT has been done using item response theory models which provide summative scores. However, formative assessment techniques (e.g., CDMs) that provide more detailed information about individuals’ strengths and weaknesses have become popular in the recent years. The use of cognitive diagnosis computerized adaptive testing (CDCAT) can produce more diagnostic information with an efficient testing design. This paper aims to investigate the impact of attribute size on the performance of item selection indices in terms of average test lengths. The result of this study showed that increasing the attribute size resulted in longer average test lengths; however, using different CDMs did not change the average test lengths.
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    Trajectories and predictors of response in youth anxiety CBT: Integrative data analysis
    (Amer Psychological Assoc, 2019) Skriner, Laura C.; Chu, Brian C.; Kaplan, Mehmet; Bodden, Denise H. M.; Bogels, Susan M.; Kendall, Philip C.; Nauta, Maaike H.; Silverman, Wendy K.; Wood, Jeffrey J.; Barker, David H.; de la Torre, Jimmy; Saavedra, Lissette; Xie, Min-ge
    Objective: Integrative data analysis was used to combine existing data from nine trials of cognitive-behavioral therapy (CBT) for anxious youth (N = 832) and identify trajectories of symptom change and predictors of trajectories. Method: Youth-and parent-reported anxiety symptoms were combined using item-response theory models. Growth mixture modeling assessed for trajectories of treatment response across pre-, mid-, and posttreatment and 1-year follow-up. Pretreatment client demographic and clinical traits and treatment modality (individual-and family-based CBT) were examined as predictors of trajectory classes. Results: Growth mixture modeling supported three trajectory classes based on parent-reported symptoms: steady responders, rapid responders, and delayed improvement. A 4-class model was supported for youth-reported symptoms: steady responders, rapid responders, delayed improvement, and low-symptom responders. Delayed improvement classes were predicted by higher number of diagnoses (parent and youth report). Receiving family CBT predicted membership in the delayed improvement class compared to all other classes and membership in the steady responder class compared with rapid responders (youth report). Rapid responders were predicted by older age (parent report) and higher number of diagnoses (parent report). Low-symptom responders were more likely to be male (youth report). Conclusions: Integrative data analysis identified distinct patterns of symptom change. Diagnostic complexity, age, gender, and treatment modality differentiated response classes.