Сравнение методов

	Cognitive Diagnostic Modeling	Many-Facet Rasch Measurement
Область	Education	Education
Семейство	Latent structure	Latent structure
Год появления	2010	1989
Автор метода	Tatsuoka; DiBello, Roussos & Stout; Junker & Sijtsma; de la Torre	John Michael Linacre
Тип	Restricted latent class models for diagnosing mastery of discrete skills	Rasch model extension adding rater and other facets to person and item
Основополагающий источник	Rupp, A. A., Templin, J., & Henson, R. A. (2010). Diagnostic Measurement: Theory, Methods, and Applications. Guilford Press. ISBN: 9781606235270	Linacre, J. M. (1989). Many-Facet Rasch Measurement. MESA Press. ISBN: 9780941938020
Другие названия	CDM, Diagnostic Classification Models, DCM, DINA / G-DINA Models	MFRM, Many-Faceted Rasch Model, Facets Model, Linacre Facets Model
Связанные	4	4
Сводка	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.	Many-facet Rasch measurement (MFRM) extends the basic Rasch model to assessments mediated by raters. Beyond examinee ability and item difficulty, it adds explicit parameters for rater severity and for any other facet of the rating situation — task, occasion, rating criterion — placing them all on one common logit scale. Developed by John Michael Linacre, MFRM lets analysts estimate and adjust for the fact that some raters are systematically harsh and others lenient, producing 'fair' ability estimates that do not penalize an examinee for happening to draw a severe judge.