Σύγκριση μεθόδων

	Μοντέλο DINA	Μεθοδολογία Χώρου Κανόνων
Πεδίο	Ψυχομετρία	Ψυχομετρία
Οικογένεια	Latent structure	Latent structure
Έτος προέλευσης	2001	1983
Δημιουργός	Brian Junker, Klaas Sijtsma	Kikumi K. Tatsuoka
Τύπος	Discrete latent class model	IRT-based diagnostic classification
Θεμελιώδης πηγή	Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25(3), 258-272.	Hartz, S. M. (2002). A Bayesian framework for the unified treatment of assessing dimensionality, assessing local dependence, and estimating ability for unidimensional and multidimensional item response data. Unpublished doctoral dissertation, University of Illinois at Urbana-Champaign.
Εναλλακτικές ονομασίες	DINA	RSM
Συναφείς	4	5
Σύνοψη	The DINA Model (Deterministic Inputs, Noisy Outputs) is a cognitive diagnostic model developed by Junker and Sijtsma (2001) that classifies examinees into latent skill classes based on their item response patterns. DINA assumes a deterministic relationship between skill mastery and correct responses, with probabilistic error accounting for guessing and slips.	Rule Space Methodology (RSM) is a diagnostic classification approach developed by Tatsuoka (1983) that uses Item Response Theory and geometric methods to classify examinees into knowledge states based on their response patterns. Unlike classical scoring, RSM identifies which specific skills or competencies an examinee possesses or lacks, enabling targeted educational interventions.