Inside Sourcefinder: Predicting the Acceptability Status of Candidate Reading-Comprehension Source Documents. Research Report. ETS RR-06-24

Autor/inn/en	Sheehan, Kathleen M.; Kostin, Irene; Futagi, Yoko; Hemat, Ramin; Zuckerman, Daniel
Titel	Inside Sourcefinder: Predicting the Acceptability Status of Candidate Reading-Comprehension Source Documents. Research Report. ETS RR-06-24
Quelle	In: ETS Research Report Series, (2006), (60 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2330-8516
Schlagwörter	Quantitative Daten; Automation; Prediction; Reading Comprehension; Classification; Regression (Statistics); Probability; Natural Language Processing; Test Items; Test Construction; Verbal Tests; College Entrance Examinations; Graduate Study; Statistical Analysis; Models; Maximum Likelihood Statistics; Graduate Record Examinations + Suchen Sie Ihr Suchwort? Vorhersage; Leseverstehen; Classification system; Klassifikation; Klassifikationssystem; Regression; Regressionsanalyse; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Natürliche Sprache; Test content; Testaufgabe; Testaufbau; Mündliche Prüfung; Aufnahmeprüfung; Aufbaustudium; Graduiertenstudium; Hauptstudium; Statistische Analyse; Analogiemodell
Abstract	This paper describes the development, implementation, and evaluation of an automated system for predicting the acceptability status of candidate reading-comprehension stimuli extracted from a database of journal and magazine articles. The system uses a combination of classification and regression techniques to predict the probability that a given document will be deemed acceptable for use in completing a specified passage-creation assignment by at least one test developer. The text features that form the basis of the estimated models are automatically extracted by natural language processing techniques. Model performance is evaluated by comparing the proportion of acceptable documents located with the screening capability turned on to the proportion of acceptable documents located with the screening capability turned off. The evaluation suggests that the estimated models have succeeded in capturing useful information about the characteristics of texts that affect test developers' ratings of source acceptability and that they can help test developers find a greater number of high-quality sources in less time. (As Provided).
Anmerkungen	Educational Testing Service. Rosedale Road, MS19-R Princeton, NJ 08541. Tel: 609-921-9000; Fax: 609-734-5410; e-mail: RDweb@ets.org; Web site: https://www.ets.org/research/policy_research_reports/ets
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01