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Cognitive diagnosis models for baseline testing of educational standards in math. / Groß, Julia; Robitzsch, Alexander; George, Ann Cathrice.

In: Journal of Applied Statistics, Vol. 43, No. 1, 2016, p. 229-243.

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Groß, Julia ; Robitzsch, Alexander ; George, Ann Cathrice. / Cognitive diagnosis models for baseline testing of educational standards in math. In: Journal of Applied Statistics. 2016 ; Vol. 43, No. 1. pp. 229-243.

BibTeX

@article{953ed66683e94f8cb33ecfc349cbecb8,
title = "Cognitive diagnosis models for baseline testing of educational standards in math",
abstract = "Cognitive diagnosis models received growing attention in recent psychometric literature in view of the potentiality for fine-grained analysis of examinees{\textquoteright} latent skills. Although different types and aspects of these models have been investigated in some detail, application to real-life data had so far been sparse. This paper aims at addressing different topics with respect to model building from a practitioner's perspective. The objective is to draw conclusions about examinees{\textquoteright} performance on the Austrian baseline testing of educational standards in math 2009. Although there is a variety of models at hand, the focus is set on the easy to interpret deterministic input, noisy {\textquoteleft}and{\textquoteright} gate model. A possible course of action with respect to model fit is outlined in detail and some conclusions with respect to test results are discussed.",
keywords = "Educational assessment/measurements, cognitive diagnosis model, model building, classification, mathematics achievement, eighth graders",
author = "Julia Gro{\ss} and Alexander Robitzsch and George, {Ann Cathrice}",
year = "2016",
doi = "10.1080/02664763.2014.1000841",
language = "English",
volume = "43",
pages = "229--243",
journal = "Journal of Applied Statistics",
issn = "0266-4763",
publisher = "Routledge",
number = "1",

}

RIS

TY - JOUR

T1 - Cognitive diagnosis models for baseline testing of educational standards in math

AU - Groß, Julia

AU - Robitzsch, Alexander

AU - George, Ann Cathrice

PY - 2016

Y1 - 2016

N2 - Cognitive diagnosis models received growing attention in recent psychometric literature in view of the potentiality for fine-grained analysis of examinees’ latent skills. Although different types and aspects of these models have been investigated in some detail, application to real-life data had so far been sparse. This paper aims at addressing different topics with respect to model building from a practitioner's perspective. The objective is to draw conclusions about examinees’ performance on the Austrian baseline testing of educational standards in math 2009. Although there is a variety of models at hand, the focus is set on the easy to interpret deterministic input, noisy ‘and’ gate model. A possible course of action with respect to model fit is outlined in detail and some conclusions with respect to test results are discussed.

AB - Cognitive diagnosis models received growing attention in recent psychometric literature in view of the potentiality for fine-grained analysis of examinees’ latent skills. Although different types and aspects of these models have been investigated in some detail, application to real-life data had so far been sparse. This paper aims at addressing different topics with respect to model building from a practitioner's perspective. The objective is to draw conclusions about examinees’ performance on the Austrian baseline testing of educational standards in math 2009. Although there is a variety of models at hand, the focus is set on the easy to interpret deterministic input, noisy ‘and’ gate model. A possible course of action with respect to model fit is outlined in detail and some conclusions with respect to test results are discussed.

KW - Educational assessment/measurements

KW - cognitive diagnosis model

KW - model building

KW - classification

KW - mathematics achievement

KW - eighth graders

U2 - 10.1080/02664763.2014.1000841

DO - 10.1080/02664763.2014.1000841

M3 - Journal article

VL - 43

SP - 229

EP - 243

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

SN - 0266-4763

IS - 1

ER -

ID: 624394