Item Diffficulty Modeling of Paragraph Comprehension Items

Gorin, Joanna S.; Embretson, Susan E.

doi:10.1177/0146621606288554

Cited by 78 publications

(83 citation statements)

References 40 publications

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“…In the AnalyticalReasoning stimuli, "if" clauses are regularly used and could be expected to increase the difficulty of a text (both with respect to logical reasoning and sentence complexity). Based on work by Drum, Calfee, and Cook (1981); Embretson and Wetzel (1987); and Gorin and Embretson (2006).…”

Section: Cardinality Of Entitiesmentioning

confidence: 99%

Selecting Testlet Features With Predictive Value for the Testlet Effect

Paap

Veldkamp

2015

Sage Open

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High-stakes tests often consist of sets of questions (i.e., items) grouped around a common stimulus. Such groupings of items are often called testlets. A basic assumption of item response theory (IRT), the mathematical model commonly used in the analysis of test data, is that individual items are independent of one another. The potential dependency among items within a testlet is often ignored in practice. In this study, a technique called tree-based regression (TBR) was applied to identify key features of stimuli that could properly predict the dependence structure of testlet data for the Analytical Reasoning section of a high-stakes test. Relevant features identified included Percentage of "If" Clauses, Number of Entities, Theme/Topic, and Predicate Propositional Density; the testlet effect was smallest for stimuli that contained 31% or fewer "if" clauses, contained 9.8% or fewer verbs, and had Media or Animals as the main theme. This study illustrates the merits of TBR in the analysis of test data.

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Section: Cardinality Of Entitiesmentioning

confidence: 99%

Selecting Testlet Features With Predictive Value for the Testlet Effect

Paap

Veldkamp

2015

Sage Open

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“…Following modern theoretical models, reading is considered an active and creative process of so called 'text image generation ' (van Dijk, Kintsch 1983, Kintsch 1988, Leontyev 1997) that includes a) (re-)encoding (also called 'decoding'), and b) elaboration of connection (coherence) between words and relating of word units in a logically coherent structure, i.e. text base (Gorin, Embretson 2006). According to Walter Kintsch and Teun A.van Dijk (1978), text processing can be interpreted as an iteration of the construction and integration processes.…”

Section: Introductionmentioning

confidence: 99%

Narrative production weakness in Russian dyslexics: Linguistic or procedural limitations?

Корнев

Balčiūnienė

2015

ERYa

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Abstract. The study deals with the impact of non-linguistic factors on narrative production in Russian-speaking dyslexic children. The experimental group consisted of 12 children (age 9-10) with dyslexia and the control group comprised 12 peers without any developmental disorders. The sample was counterbalanced from the perspective of narrative mode, story complexity, and task order. One of the classic methodologies for narrative analysis, i.e. story grammar, was extended in our study by a novel dynamic approach, enabling us to evaluate procedural features of narrative production.The results of our study highlight limitations in dyslexic narrative language underlined by two different causes. The first one can be defined as inefficiency in developing logical (temporal/causal) relationships between events; the other is difficulties in structuring an episode description. The high flexibility and dynamic changes in the episode structure in dyslexics anticipated the evidence that limitations in dyslexic narrative language are related to the deficit in procedural functions rather than to the primary language limitations; however, linguistic shortcomings in dyslexic narrative production still remain.Our experience with the dynamic approach to narrative assessment lends support to its value as a research tool. The novel dynamic approach to episode completeness analysis proved to be an effective and informative method that might highlight new mechanisms of narration and thus extend the classic narrative analysis by the addition of qualitative information.* Keywords: first language acquisition, language pathology, Russian * The research was carried out with the financial support of the Russian Foundation for Humanities, grant No. 14-04-00509 Formirovanie jazykovyh podsistem u detej s normoj i otstavaniem v razvitii reči: korpusnoe i èksperimental'noe issledovanie tekstov [Development of linguistic sub-systems in typically-developing and language-impaired children: Corpus-based and experimental study].

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“…This line of research has been built on the investigation (mainly through semi-structured interviews and verbal selfreports) into the strategies used by subjects to solve reading comprehension items (Farr, Pritchard & Smitten, 1990;DeMauro, Merritty & Adams, 1994;Powers & Wilson, 1995;Rupp, Ferne & Choi, 2006). In addition, the attempt to predict item difficulty level has generated a large number of studies where the basic interest has been to identify cognitive and linguistic predictors (Drum, Calfee & Cook, 1981;Stahl & Jacobson, 1986;Davey, 1988;Kirsch & Mosenthal, 1990;Freedle & Kostin, 1991;Freedle & Kostin, 1992;Daneman & Hannon, 2001;Sheehan & Ginther, 2001;Gorin & Embretson, 2006;Ozuru, Rowe, O'Reilly & McNamara, 2008;Leroy, Helmreich & Cowie, 2010). These last studies have primarily used a quantitative approach, making use of traditional statistical techniques such as multiple regression and ANOVA; however, various studies can also be found where the LLTM is used to estimate the predictive power of certain characteristics of logical reasoning and reading comprehension items (Embretson & Wetzel, 1987;Sheehan & Mislevy, 1990;Gorin, 2005;Sonnleitner, 2008;Attoresi, Picón, Abal, Aguerri & Galibert, 2009;Gilbert, Picón, Lozzia, Aguerri & Attorresi, 2010;Poinstingl, 2009).…”

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confidence: 99%

Prediction of the difficulty level in a standardized reading comprehension test: contributions from cognitive psychology and psychometrics

Brizuela¹,

Montero-Rojas²

2014

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[Predicción del nivel de dificultad en una prueba estandarizada de comprensión de lectura: aportes desde la psicometría y la psicología cognitiva]by/por AbstractThis research seeks to identify possible predictors of the difficulty level of reading comprehension items used in a standardized psychometric test for university admission. Several potential predictors of difficulty were proposed, namely, propositional density, negations, grammatical structure, vocabulary difficulty, presence of enhancement elements (words highlighted typographically), item abstraction level and degree of similarity between correct option and relevant text to resolve the item. By Linear Logistic Test Model (Fisher, 1973) it was found that the number of propositions, the syntactic structure, and fundamentally, the presence of difficult words contributed to the prediction of the item difficulty level. ResumenEsta investigación busca identificar posibles variables predictoras del nivel de dificultad de los ítems de comprensión de lectura utilizados en una prueba psicométrica estandarizada para la admisión a una institución universitaria. Se propusieron varios posibles predictores del nivel de dificultad, a saber: densidad proposicional, negaciones, estructura sintáctica, dificultad del vocabulario, presencia elementos de realce (palabras resaltadas tipográficamen-te), abstracción del ítem y grado de similitud entre opción correcta y texto relevante para resolver el ítem. Mediante el Modelo Logístico Lineal de Rasgo Latente se encontró que la cantidad de proposiciones, la estructura sintáctica y, fundamentalmente, la presencia de léxico difícil de comprender contribuyeron a la predicción del nivel de dificultad.

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Item Diffficulty Modeling of Paragraph Comprehension Items

Cited by 78 publications

References 40 publications

Selecting Testlet Features With Predictive Value for the Testlet Effect

Selecting Testlet Features With Predictive Value for the Testlet Effect

Narrative production weakness in Russian dyslexics: Linguistic or procedural limitations?

Prediction of the difficulty level in a standardized reading comprehension test: contributions from cognitive psychology and psychometrics

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