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OSCATS (Open-Source Computerized Adaptive Testing System) implements Item Response Theory (IRT) and cognitively diagnostic (latent classification) models and item selection algorithms used in Computerized Adaptive Testing (CAT). OSCATS facilitates the development of CATs and simulations of CATs by providing ready-to-use code for running the CAT item selection and ability/classification estimation in an extensible, modular framework. The library is written in object-oriented C using GObject, and has bindings to Python, Perl, PHP, and Java.

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2011-11-05 08:23
0.6

Clases de OscatsSpace nueva y OscatsPoint para una representación unificada de ordinales, binarios y continuas latentes espacios. Unificación de la OscatsContModel y OscatsDiscrModel en un OscatsModel único basado en la nueva representación del espacio latente. Generalización de OscatsItem para permitir a un número arbitrario de modelos para estudios de simulación compleja. Implementación del algoritmo de selección estratificado un elemento. Modelos recién implementados (PC, GPC y GR). Nuevos ejemplos, incluida la aplicación de un algoritmo personalizado en Python.
New OscatsSpace and OscatsPoint classes for a unified representation of continuous, binary, and ordinal latent spaces. Unification of the OscatsContModel and OscatsDiscrModel into a single OscatsModel based on the new latent space representation. Generalization of OscatsItem to allow any arbitrary number of models for complex simulation studies. Implementation of the a-Stratified item selection algorithm. Newly implemented models (PC, GPC, and GR). New examples, including implementation of a custom algorithm in Python.

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