পদ্ধতির তুলনা করুন

	DINA মডেল	রুল স্পেস মেথডোলজি
ক্ষেত্র	মনোমিতি	মনোমিতি
পরিবার	Latent structure	Latent structure
উদ্ভবের বছর	2001	1983
প্রবর্তক	Brian Junker, Klaas Sijtsma	Kikumi K. Tatsuoka
ধরন	Discrete latent class model	IRT-based diagnostic classification
মৌলিক উৎস	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 Unpublished doctoral dissertation, University of Illinois at Urbana-Champaign.
অপর নাম	DINA	RSM
সম্পর্কিত	4	5
সারসংক্ষেপ	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.