Generating items during testing: Psychometric issues and models

Embretson, Susan E.

doi:10.1007/bf02294564

Cited by 118 publications

(135 citation statements)

References 35 publications

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“…A growing number of projects demonstrate the feasibility of the generative approach (e.g., 1990Bejar & Braun, 1997;Bejar & Yocom, 1991;Embretson, 1999;Hornke & Habon, 1986;Irvine, Dunn, & Anderson, 1990;Meisner, Luecht, & Reckase, 1993;Wolfe & Larson, 1990 Hornke & Habon (1986), and Irvine et al (1990) are especially noteworthy because they provided a conceptual and experimental basis for much subsequent work.…”

Section: Item Modelingmentioning

confidence: 99%

“…In the former case, each model is written to generate items that are isomorphic. Psychological principles are used to create variation in difficulty between, rather than within, models and to predict the response parameters for each model (e.g., Embretson's [1993Embretson's [ , 1999 is on producing items that are well described by a single set of parameters.…”

Section: Item Modelingmentioning

confidence: 99%

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A Feasibility Study of On‐the‐fly Item Generation in Adaptive Testing

Bejar

Lawless

Morley

et al. 2002

ETS Research Report Series

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The goal of this study was to assess the feasibility of an approach to adaptive testing based on item models. A simulation study was designed to explore the affects of item modeling on score precision and bias, and two experimental tests were administered -an experimental, on-the-fly, adaptive quantitative-reasoning test as well as a linear test. Results of the simulation study showed that under different levels of isomorphicity, there was no bias, but precision of measurement was eroded, especially in the middle range of the true-score scale. However, the comparison of adaptive test scores with operational Graduate Record Examinations (GRE) test scores matched the test-retest correlation observed under operational conditions. Analyses of item functioning on linear forms suggested a high level of isomorphicity across items within models. The current study provides a promising first step toward significant cost and theoretical improvement in test creation methodology for educational assessment.

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Section: Item Modelingmentioning

confidence: 99%

Section: Item Modelingmentioning

confidence: 99%

A Feasibility Study of On‐the‐fly Item Generation in Adaptive Testing

Bejar

Lawless

Morley

et al. 2002

ETS Research Report Series

View full text Add to dashboard Cite

show abstract

“…In a study using mathematical models and cognitive theory, Embretson (1999) found that predicted item parameters correlated only in the .70s and .80s with calibrated item parameters, while the correlation was below .50 when the model was based on item features. As reported in Gorin and Embretson (2013), most studies found that item difficulty models explained between 30% and 60% of the variance in predicted item difficulty.…”

Section: Ability Estimationmentioning

confidence: 99%

Untitled

2016

JCAT

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“…Embretson (1999) referred to this model as the 2PL constrained model in the context of modeling the cognitive complexity of test items. With flirt, the 2PL constrained model can be specified as follows:…”

Section: Item Covariatesmentioning

confidence: 99%

A modular approach for item response theory modeling with the R package flirt

Jeon

Rijmen

2015

Behav Res

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The new R package flirt is introduced for flexible item response theory (IRT) modeling of psychological, educational, and behavior assessment data. flirt integrates a generalized linear and nonlinear mixed modeling framework with graphical model theory. The graphical model framework allows for efficient maximum likelihood estimation. The key feature of flirt is its modular approach to facilitate convenient and flexible model specifications. Researchers can construct customized IRT models by simply selecting various modeling modules, such as parametric forms, number of dimensions, item and person covariates, person groups, link functions, etc. In this paper, we describe major features of flirt and provide examples to illustrate how flirt works in practice.

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Generating items during testing: Psychometric issues and models

Abstract: item generation, test design, IRT models, cognitive models, ability estimation, item uncertainty,

Cited by 118 publications

References 35 publications

A Feasibility Study of On‐the‐fly Item Generation in Adaptive Testing

A Feasibility Study of On‐the‐fly Item Generation in Adaptive Testing

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A modular approach for item response theory modeling with the R package flirt

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