Abstract
Cognitive diagnostic computerized adaptive testing (CD-CAT) aims to take full advantage of both cognitive diagnosis (CD) and CAT. Cognitive diagnostic models (CDMs) attempt to classify students into several attribute profiles so as to evaluate their strengths and weaknesses while the CAT system selects items from the item pool to realize that goal as efficiently as possible. Most of the current research focuses on developing the item selection strategies and uses a fixed-length termination rule in CAT. Nevertheless, a variable-length termination rule is more appropriate than the fixed-length rule in order to bring out the full potential of CD-CAT. The current study discussed the inherent issue of instability over different numbers of attributes with the previous termination rules (the Tatsuoka rule and the two-criterion rule), proposed three termination rules from the information theory perspective, and revealed the connection between the previous methods and one of the information-based termination rules that will be discussed, further demonstrating the instability issue. Two simulation studies were implemented to evaluate the performance of these methods. Simulation results indicated that the SHE rule demonstrated strong stability across different numbers of attributes and different CDMs and should be recommended for application.
Highlights
The goal of cognitive diagnosis is to obtain the students’ status of mastering specific attributes measured by items in psychological and educational assessment
One main application of cognitive diagnosis models (CDMs) that has been published by many researches is in combination with computerized adaptive testing (CAT), which can be termed as cognitive diagnostic computerized adaptive testing (CD-CAT; Cheng, 2009; Huebner, 2010)
Due to the large number of attributes, it might take a lot of items for some examinees to finish the test, so the maximum number of items an examinee can take in a cognitive diagnosis (CD)-CAT test was set to 100, which was 10% of the total number of items
Summary
The goal of cognitive diagnosis is to obtain the students’ status of mastering specific attributes measured by items in psychological and educational assessment. Various cognitive diagnosis models (CDMs) have been developed to evaluate the attribute profiles or latent classes for each student, which designates whether each of the measured attributes or skills has been mastered (Tatsuoka, 1983; Mislevy et al, 2000; Junker and Sijtsma, 2001; Rupp et al, 2010). The major benefit of CAT is that a tailored test can be generated for each individual via selecting items from the item pool according to their responses to previous items. CAT will get the same precision of ability estimation as a traditional paper and pencil test by using fewer items. It is obvious that CD-CAT may have a performance comparable to Item Response Theory (IRT)-CAT
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