Cognitive diagnostic model of best choice: a study of reading comprehension

Ravand, Hamdollah; Robitzsch, Alexander

doi:10.1080/01443410.2018.1489524

Cited by 41 publications

(43 citation statements)

References 47 publications

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“…Classification accuracy ( P a ) and consistency ( P c ) are two important indicators for evaluating the reliability and validity of classification results. According to Ravand and Robitzsch (2018) , values of at least 0.8 for the P a index and 0.7 for the P c index can be considered acceptable classification rates. As shown in Table 11 , both pattern- and attribute-level classification accuracy and consistency were within the acceptable range.…”

Section: Development Of the Instrument For Longitudinal Learning Diagmentioning

confidence: 99%

The Development of an Instrument for Longitudinal Learning Diagnosis of Rational Number Operations Based on Parallel Tests

Tang

Zhan

2020

Front. Psychol.

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The precondition of the measurement of longitudinal learning is a high-quality instrument for longitudinal learning diagnosis. This study developed an instrument for longitudinal learning diagnosis of rational number operations. In order to provide a reference for practitioners to develop the instrument for longitudinal learning diagnosis, the development process was presented step by step. The development process contains three main phases, the Q-matrix construction and item development, the preliminary/pilot test for item quality monitoring, and the formal test for test quality control. The results of this study indicate that (a) both the overall quality of the tests and the quality of each item are good enough and that (b) the three tests meet the requirements of parallel tests, which can be used as an instrument for longitudinal learning diagnosis to track students’ learning.

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Section: Development Of the Instrument For Longitudinal Learning Diagmentioning

confidence: 99%

The Development of an Instrument for Longitudinal Learning Diagnosis of Rational Number Operations Based on Parallel Tests

Tang

Zhan

2020

Front. Psychol.

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“…Cognitive diagnostic models have primarily been used to serve two main purposes: (a) to classify examinees into similar skill mastery profiles on the basis of their observed response patterns and (b) to identify whether there is a compensatory or noncompensatory interaction between the postulated attributes underlying a given skill (Ravand & Robitzsch, 2018). A wide array of CDMs with different theories or assumptions about the way of interaction between attributes (see Ravand & Baghaei, 2019, for a review) have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Diagnosing EFL learners’ writing ability: a diagnostic classification modeling analysis

2019

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Cognitive diagnostic models (CDMs) have recently received a surge of interest in the field of second language assessment due to their promise for providing fine-grained information about strengths and weaknesses of test takers. For the same reason, the present study used the additive CDM (ACDM) as a compensatory and additive model to diagnose Iranian English as a foreign language (EFL) university students' L2 writing ability. To this end, the performance of 500 university students on a writing task was marked by four EFL teachers using the Empirically derived Descriptor-based Diagnostic (EDD) checklist. Teachers, as content experts, also specified the relationships among the checklist items and five writing sub-skills. The initial Q-matrix was empirically refined and validated by the GDINA package. Then, the resultant ratings were analyzed by the ACDM in the CDM package. The estimation of the skill profiles of the test takers showed that vocabulary use and content fulfillment are the most difficult attributes for the students. Finally, the study found that the skills diagnosis approach can provide informative and valid information about the learning status of students.

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“…On the other hand, CDMs can provide highly reliable examinee estimates with small sample sizes (Bradshaw & Cohen, 2010). As a rule of thumb, it is suggested that the number of items and sample size should exceed the number of latent classes (e.g., Huebner, 2010;Ravand & Robitzsch, 2018). In this study, there were 16 latent classes which was less than number of items (i.e., 22) and sample size (i.e., 282).…”

Section: Resultsmentioning

confidence: 77%

“…According to Table 8, Attributes 1 and 3 were estimated at 99% certainty and Attribute 2 and Attribute 4 were estimated at 97% and 96% certainty, respectively. Although there is no systematic investigation on the effect of sample size on CDM classification accuracy, some researchers (e.g., Tatsuoka, 1983;Lei & Li, 2016) stated that CDM classification accuracy increases with the sample size (Ravand & Robitzsch, 2018). On the other hand, CDMs can provide highly reliable examinee estimates with small sample sizes (Bradshaw & Cohen, 2010).…”

Section: Resultsmentioning

confidence: 99%

A diagnostic assessment to middle school students’ proportional reasoning

Arıcan

2019

Turkish Journal of Education

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This study investigated Turkish middle school students' proportional reasoning and provided a diagnostic assessment of their strengths and weaknesses on the ratio and proportion concepts. A proportional reasoning test with 22 multiple-choice items was developed from the context of the loglinear cognitive diagnosis model. The test was developed around four core cognitive skills (attributes) that required in solving middle school ratio and proportion problems. These skills included understanding ratios, directly, inversely, and nonproportional relationships. The test was applied to 282 seventh grade students, and the collected data were analyzed using the Mplus software. The analysis showed that approximately 62% of the students were able to recognize directly proportional relationships. Whereas, roughly 48% of them were able to recognize inversely proportional relationships. Moreover, while 25% of the students did not master any of the four cognitive skills, 39.1% mastered all four of these skills. In addition, many students had difficulty distinguishing proportional relationships from nonproportional relationships. Diagnostic feedbacks on the students' strengths and weaknesses were provided based on the findings.

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Cognitive diagnostic model of best choice: a study of reading comprehension

Cited by 41 publications

References 47 publications

The Development of an Instrument for Longitudinal Learning Diagnosis of Rational Number Operations Based on Parallel Tests

The Development of an Instrument for Longitudinal Learning Diagnosis of Rational Number Operations Based on Parallel Tests

Diagnosing EFL learners’ writing ability: a diagnostic classification modeling analysis

A diagnostic assessment to middle school students’ proportional reasoning

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