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| Cognitive Diagnostic Modeling× | תיאוריית תגובת פריט (IRT)× | |
|---|---|---|
| תחום≠ | Education | פסיכומטריה |
| משפחה | Latent structure | Latent structure |
| שנת המקור≠ | 2010 | 1952–1968 |
| הוגה השיטה≠ | Tatsuoka; DiBello, Roussos & Stout; Junker & Sijtsma; de la Torre | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| סוג≠ | Restricted latent class models for diagnosing mastery of discrete skills | Probabilistic measurement model |
| מקור מכונן≠ | Rupp, A. A., Templin, J., & Henson, R. A. (2010). Diagnostic Measurement: Theory, Methods, and Applications. Guilford Press. ISBN: 9781606235270 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| כינויים≠ | CDM, Diagnostic Classification Models, DCM, DINA / G-DINA Models | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| קשורות≠ | 4 | 5 |
| תקציר≠ | Cognitive diagnostic models (CDMs), also called diagnostic classification models, are restricted latent class models that report not a single ability score but a profile of which discrete skills or attributes a student has mastered. Each item is linked to the attributes it requires through a Q-matrix, and the model classifies every examinee into one of the possible binary mastery patterns. CDMs answer 'which specific skills does this student lack' rather than 'how much overall ability does this student have,' making them central to fine-grained diagnostic and formative assessment. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
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