Item Difficulty Modeling of Paragraph Comprehension Items

Autor/inn/en	Gorin, Joanna S.; Embretson, Susan E.
Titel	Item Difficulty Modeling of Paragraph Comprehension Items
Quelle	In: Applied Psychological Measurement, 30 (2006) 5, S.394-411 (18 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621606288554
Schlagwörter	Difficulty Level; Test Items; Modeling (Psychology); Paragraph Composition; Evaluation Research; Cognitive Psychology; Psychometrics; Technology; Reading Comprehension; Artificial Intelligence; Models; Item Analysis; Cognitive Processes; Item Response Theory; Regression (Statistics); Test Reliability; Correlation; Graduate Record Examinations + Suchen Sie Ihr Suchwort? Schwierigkeitsgrad; Test content; Testaufgabe; Modeling; Modelling; Modellierung; Evaluationsforschung; Kognitive Psychologie; Psychometry; Psychometrie; Technologie; Leseverstehen; Künstliche Intelligenz; Analogiemodell; Itemanalyse; Cognitive process; Kognitiver Prozess; Item-Response-Theorie; Regression; Regressionsanalyse; Testreliabilität; Korrelation
Abstract	Recent assessment research joining cognitive psychology and psychometric theory has introduced a new technology, item generation. In algorithmic item generation, items are systematically created based on specific combinations of features that underlie the processing required to correctly solve a problem. Reading comprehension items have been more difficult to model than other item types due to the complexities of quantifying text. However, recent developments in artificial intelligence for text analysis permit quantitative indices to represent cognitive sources of difficulty. The current study attempts to identify generative components for the Graduate Record Examination paragraph comprehension items through the cognitive decomposition of item difficulty. Text comprehension and decision processes accounted for a significant amount of the variance in item difficulties. The decision model variables contributed significantly to variance in item difficulties, whereas the text representation variables did not. Implications for score interpretation and future possibilities for item generation are discussed. (Contains 1 figure and 5 tables.) (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10