Sammenlign metoder

	DINA-modellen	Rule Space Methodology
Fagområde	Psykometri	Psykometri
Familie	Latent structure	Latent structure
Oprindelsesår	2001	1983
Ophavsperson	Brian Junker, Klaas Sijtsma	Kikumi K. Tatsuoka
Type	Discrete latent class model	IRT-based diagnostic classification
Oprindelig kilde	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 Unpublished doctoral dissertation, University of Illinois at Urbana-Champaign.
Aliasser	DINA	RSM
Relaterede	4	5
Resumé	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.