Properties and performance of the one-parameter log-linear cognitive diagnosis model
Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increase...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Education |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/feduc.2024.1287279/full |
| _version_ | 1797348561372839936 |
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| author | Lientje Maas Matthew J. Madison Matthieu J. S. Brinkhuis |
| author_facet | Lientje Maas Matthew J. Madison Matthieu J. S. Brinkhuis |
| author_sort | Lientje Maas |
| collection | DOAJ |
| description | Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due to useful measurement properties like sum score sufficiency and invariance properties. We demonstrate its equivalence with the Latent Class/Rasch Model and discuss interpretational consequences. The model is further examined in a DCM framework. We demonstrate the sum score sufficiency property and we derive an expression for the cut score for mastery classification. It is shown by means of a simulation study that the 1-PLCDM is fairly robust to model constraint violations in terms of classification accuracy and reliability. This robustness in combination with useful measurement properties and ease of interpretation can make the model attractive for stakeholders to apply in various assessment settings. |
| first_indexed | 2024-03-08T12:07:47Z |
| format | Article |
| id | doaj.art-77310aca93d041b9a9506282e51bd6c2 |
| institution | Directory Open Access Journal |
| issn | 2504-284X |
| language | English |
| last_indexed | 2024-03-08T12:07:47Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Education |
| spelling | doaj.art-77310aca93d041b9a9506282e51bd6c22024-01-23T04:30:28ZengFrontiers Media S.A.Frontiers in Education2504-284X2024-01-01910.3389/feduc.2024.12872791287279Properties and performance of the one-parameter log-linear cognitive diagnosis modelLientje Maas0Matthew J. Madison1Matthieu J. S. Brinkhuis2Department of Methodology and Statistics, Utrecht University, Utrecht, NetherlandsDepartment of Educational Psychology, University of Georgia, Athens, GA, United StatesDepartment of Information and Computing Sciences, Utrecht University, Utrecht, NetherlandsDiagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due to useful measurement properties like sum score sufficiency and invariance properties. We demonstrate its equivalence with the Latent Class/Rasch Model and discuss interpretational consequences. The model is further examined in a DCM framework. We demonstrate the sum score sufficiency property and we derive an expression for the cut score for mastery classification. It is shown by means of a simulation study that the 1-PLCDM is fairly robust to model constraint violations in terms of classification accuracy and reliability. This robustness in combination with useful measurement properties and ease of interpretation can make the model attractive for stakeholders to apply in various assessment settings.https://www.frontiersin.org/articles/10.3389/feduc.2024.1287279/fulldiagnostic classification modelscut scoressum score sufficiencyscore interpretationcognitive diagnostic assessment |
| spellingShingle | Lientje Maas Matthew J. Madison Matthieu J. S. Brinkhuis Properties and performance of the one-parameter log-linear cognitive diagnosis model Frontiers in Education diagnostic classification models cut scores sum score sufficiency score interpretation cognitive diagnostic assessment |
| title | Properties and performance of the one-parameter log-linear cognitive diagnosis model |
| title_full | Properties and performance of the one-parameter log-linear cognitive diagnosis model |
| title_fullStr | Properties and performance of the one-parameter log-linear cognitive diagnosis model |
| title_full_unstemmed | Properties and performance of the one-parameter log-linear cognitive diagnosis model |
| title_short | Properties and performance of the one-parameter log-linear cognitive diagnosis model |
| title_sort | properties and performance of the one parameter log linear cognitive diagnosis model |
| topic | diagnostic classification models cut scores sum score sufficiency score interpretation cognitive diagnostic assessment |
| url | https://www.frontiersin.org/articles/10.3389/feduc.2024.1287279/full |
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