Probing the relative importance of different attributes in L2 reading and listening comprehension items: An application of cognitive diagnostic models

2016 ◽  
Vol 34 (3) ◽  
pp. 337-355 ◽  
Author(s):  
Yeon-Sook Yi
2007 ◽  
Vol 67 (2) ◽  
pp. 239-257 ◽  
Author(s):  
Sandip Sinharay ◽  
Russell G. Almond

2019 ◽  
Vol 44 (4) ◽  
pp. 267-281 ◽  
Author(s):  
Justin Paulsen ◽  
Dubravka Svetina ◽  
Yanan Feng ◽  
Montserrat Valdivia

Cognitive diagnostic models (CDMs) are of growing interest in educational research because of the models’ ability to provide diagnostic information regarding examinees’ strengths and weaknesses suited to a variety of content areas. An important step to ensure appropriate uses and interpretations from CDMs is to understand the impact of differential item functioning (DIF). While methods of detecting DIF in CDMs have been identified, there is a limited understanding of the extent to which DIF affects classification accuracy. This simulation study provides a reference to practitioners to understand how different magnitudes and types of DIF interact with CDM item types and group distributions and sample sizes to influence attribute- and profile-level classification accuracy. The results suggest that attribute-level classification accuracy is robust to DIF of large magnitudes in most conditions, while profile-level classification accuracy is negatively influenced by the inclusion of DIF. Conditions of unequal group distributions and DIF located on simple structure items had the greatest effect in decreasing classification accuracy. The article closes by considering implications of the results and future directions.


2013 ◽  
Vol 45 (11) ◽  
pp. 1295-1304 ◽  
Author(s):  
Yan CAI ◽  
Dongbo TU ◽  
Shuliang DING

2015 ◽  
Vol 10 (1) ◽  
pp. 108-132 ◽  
Author(s):  
Maria Jesus Blasco Mayor

This study reports findings from an experiment that was conducted to investigate language proficiency as an indicator of future interpreting performance. The initial assumption was that Spanish undergraduate translation and interpreting students had an insufficient command of L2 skills to start interpreter training. We hypothesized that an intensive teaching module on L2 phonology and listening comprehension would improve their academic performance in interpreting. Several tests were used to evaluate participant L2 listening comprehension (TOEFL), L2 reading comprehension (TOEFL), L2 grammar (TOEFL), and L1 verbal fluency (WAIS-III). Only those related to L2 are reported here. A consecutive interpreting test was given at the end of the first interpretation module. The students’ self-perception regarding L2 issues was assessed using two questionnaires and an interview. The results suggest that L2 listening comprehension training aided in consecutive interpreting performance. Language proficiency was also found to correlate with interpreting scores. A base level of L2 proficiency for interpreting training is suggested. We conclude that L2 listening comprehension proficiency has a significant effect on undergraduate students’ interpreting ability and is therefore a suitable predictor for interpreting aptitude. Consequently, L2 listening skills should be included in the interpreting program curriculum, preferably before interpretation classes start.


2018 ◽  
Vol 43 (4) ◽  
pp. 255-271 ◽  
Author(s):  
Dongbo Tu ◽  
Shiyu Wang ◽  
Yan Cai ◽  
Jeff Douglas ◽  
Hua-Hua Chang

Attribute hierarchy is a common assumption in the educational context, where the mastery of one attribute is assumed to be a prerequisite to the mastery of another one. The attribute hierarchy can be incorporated through a restricted Q matrix that implies the specified structure. The latent class–based cognitive diagnostic models (CDMs) usually do not assume a hierarchical structure among attributes, which means all profiles of attributes are possible in a population of interest. This study investigates different estimation methods to the classification accuracy for a family of CDMs when they are combined with a restricted Q-matrix design. A simulation study is used to explain the misclassification caused by an unrestricted estimation procedure. The advantages of the restricted estimation procedure utilizing attribute hierarchies for increased classification accuracy are also further illustrated through a real data analysis on a syllogistic reasoning diagnostic assessment. This research can provide guidelines for educational and psychological researchers and practitioners when they use CDMs to analyze the data with a restricted Q-matrix design and make them be aware of the potentially contaminated classification results if ignoring attribute hierarchies.


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