Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： Doctors have to use different medical technologies to diagnose different kinds of illness effectively. Similarly, teachers have to use well designed tests to provide an accurate evaluation of students with different cognitive structures. To provide such an evaluation, we recommend to adopt the Cognitive Diagnostic Assessment (CDA). CDA could measure specific cognitive structures and processing skills of students so as to provide information about their cognitive strengths and weaknesses. In general, the typical design procedure of a CDA test is as follow: firstly, identify the target attributes and their hierarchical relationships; secondly, design a Q matrix (which characterizes the design of test construct and content); finally, construct test items. Within that designing framework, two forms of test are available: the traditional test and the computerized adaptive test (CAT). The former is a kind of test that has a fixed-structure for all participants with different cognitive structures, the latter is tailored to each participant’s cognitive structure. Researchers have not, however, considered the specific test design for different cognitive structures when using these two test forms. As a result, the traditional test requires more items to gain a precise evaluation of a group of participants with mixed cognitive structures, and a cognitive diagnosis computer adaptive test (CD-CAT) has low efficiency of the item bank usage due to the problems in assembling a particular item bank. The key to overcome these hurdles is to explore the appropriate design tailored for participants with different cognitive structures. As discussed above, a reasonable diagnosis test should be specific for the cognitive structure of target examinees so to perform classification precisely and efficiently. This is in line with CAT. In CAT, an ideal item bank serves as a cornerstone in achieving this purpose. In this regard, Reckase (2003, 2007 & 2010) came up with an approach named p-optimality in designing an optimal item bank. Inspired by the p-optimality and working according to the characteristics of CDA, we proposed a method to design the test for different cognitive structures. We conducted a Monte Carlo simulation study to explore the different test design modes for different cognitive structures under six attribute hierarchical structures (Linear, Convergent, Divergent, Unstructured, Independent and Mixture). The results show that: (1) the optimal test design modes for different cognitive structures are different under the same hierarchical structure in test length, initial exploration stage (Stage 0), accurately estimation stage (Stage 1); (2) the item bank for cognitive diagnosis computer adaptive test (CD-CAT) we built, according to the different cognitive structures’ optimal test design modes, has a superior performance on item pool usage than other commonly used item banks no matter whether the fixed-length test or the variable-length test is used. We provide suggestions for item bank assembling basing on results from these experiments.
Subjects: Psychology >> Psychological Measurement submitted time 2022-05-12
Abstract：
Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT) combines the advantages of cognitive diagnosis and CAT, which could improve the efficiency and accuracy of CD-CAT. CD-CAT can be divided into two types: dichotomous and polytomous. Presently, the majority of researches on CD-CAT are based on dichotomous CD-CAT. However, among the practical tests in psychology and education, there are many polytomous items, which can be further divided into nominal polytomous and ordinal polytomous items according to whether there is an order or grade between every response category. Nominal polytomous items are items whose response categories are independent and without orders or grades between every response category. Although researchers have developed (ordinal) polytomous CDMs and corresponding CD-CAT, few nominal CDMs and CD-CAT are based on nominal responses.
This study introduces seven commonly used item selection methods in dichotomous CD-CAT into NCD-CAT (CD-CAT based on nominal response models). PMR (pattern match ratio) and test efficiency index are evaluated under different conditions between these item selection methods. Here are details of two simulation studies below. Study 1 compared the performance of NR_PWKL, NR_PWCDI, NR_PWACDI, NR_MPWKL, NR_SHE, NR_MI, and NR_GDI methods under different test lengths (5, 10, 15, 20) and item pool qualities (high and low) in NCD-CAT. Results showed that: (1) the PMRs of NR_PWCDI, NR_PWACDI, NR_MPWKL, NR_SHE, and NR_MI are higher than or equal to that of NR_PWKL, especially in short tests. (2) as test length gets longer, that PMR advantage is missing, which is the same as the results of Zheng and Chang (2016). (3) compared to test length, item quality has a greater impact on PMR. For instance, with item quality descending, the PMR declined about 30% among all conditions. Study 2 is an experiment on variable-length NCD-CAT that was conducted to compare the performance of each item selection method under the conditions of three maximum posterior probabilities (0.8, 0.85, 0.9) and two item qualities (high and low). The results showed that: (1)under all experimental conditions the average test lengths of NR_PWCDI, NR_PWACDI, NR_MPWKL, NR_SHE, and NR_MI are shorter than that of NR_PWKL; the difference is more than 0.738. (2)affected by item quality, the average length of NR_GDI is smaller than that of NR_PWKL under high-quality conditions and larger than it under low-quality conditions.
To sum up, this study compared the performance of 7 commonly used item selection methods of dichotomous CD-CAT in NCD-CAT with different conditions (fixed and variable length). The simulation study showed that under most conditions, the NR_PWCDI, NR_PWACDI, NR_MPWKL, NR_SHE, and NR_MI methods performed well when compared to baseline algorithm NR_PWKL. This study has expanded the alternatives of item selection methods in NCD-CAT.
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