2020
DOI: 10.1177/2158244020931068
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Hierarchical Diagnostic Classification Modeling of Reading Comprehension

Abstract: The Hierarchical Diagnostic Classification Model (HDCM) reflects on the sequences of the presentation of the essential materials and attributes to answer the items of a test correctly. In this study, a foreign language reading comprehension test was analyzed employing HDCM and the generalized deterministic-input, noisy and gate (G-DINA) model to determine and compare respondents’ mastery profiles in the test’s predefined skills and to illustrate the relationships among the attributes involved in the test to ca… Show more

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Cited by 4 publications
(6 citation statements)
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“…Within the traditional LCDM framework, attributes are assumed to be unstructured in the sense that directional or hierarchical relationships among attributes are not assumed nor specified [16]. However, as [15] notes, hierarchical structures naturally arise in psychological and educational contexts (e.g., [32][33][34]).…”
Section: Lcdm Structural Model and Attribute Hierarchiesmentioning
confidence: 99%
“…Within the traditional LCDM framework, attributes are assumed to be unstructured in the sense that directional or hierarchical relationships among attributes are not assumed nor specified [16]. However, as [15] notes, hierarchical structures naturally arise in psychological and educational contexts (e.g., [32][33][34]).…”
Section: Lcdm Structural Model and Attribute Hierarchiesmentioning
confidence: 99%
“…Within the traditional LCDM framework, attributes are assumed to be unstructured in the sense that directional or hierarchical relationships among attributes are not assumed nor specified . However as Rupp, Templin, and Henson (2010) note, hierarchical structures naturally arise in psychological and educational contexts (e.g., Ma, Wang, & Xiao, 2023;Tabatabaee-Yazdi, 2020;Zhang & Wang, 2020).…”
Section: Lcdm Structural Model and Attribute Hierarchiesmentioning
confidence: 99%
“…According to the correlation between attributes, CDMs are classified into two types: (1) conjunctive or non-compensatory models, and (2) disjunctive or compensatory models. If the performance of one or more of the attributes can compensate for the non-performance of other attributes, compensatory models (Disjunctive) are used Tabatabaee-Yazdi, 2020). Conversely, if the performance of one or more of the attributes cannot compensate for the non-performance of other attributes, non-compensatory models (Conjunctive), are used.…”
Section: Types Of Cdmsmentioning
confidence: 99%
“…Conversely, if the performance of one or more of the attributes cannot compensate for the non-performance of other attributes, non-compensatory models (Conjunctive), are used. Thus, in order to achieve a high probability of a correct answer, performance of all the required attributes is needed Tabatabaee-Yazdi, 2020).…”
Section: Types Of Cdmsmentioning
confidence: 99%
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