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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

연속, 이진, 및 서 수 숨겨진 공간 통합된 표현에 대 한 새로운 OscatsSpace 및 OscatsPoint 클래스. 단일 Oscatsmodel에 OscatsContModel 및 Oscatsdiscrmodel의 통일 새 숨겨진 공간 표현을 기준으로 합니다. 복잡 한 시뮬레이션 연구 모델의 어떤 임의의 수 있도록 Oscatsitem의 일반화. 한 층 화 항목 선택 알고리즘의 구현. 새로 구현 된 모델 (PC, GPC, 및 GR). 새로운 예제, 파이썬에서 사용자 지정 알고리즘의 구현을 포함 합니다.
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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