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Autor/inn/enMorris, Darrell; Trathen, Woodrow; Lomax, Richard G.; Perney, Jan; Kucan, Linda; Frye, Elizabeth M.; Bloodgood, Janet W.; Ward, Devery; Schlagal, Robert
TitelModeling Aspects of Print-Processing Skill: Implications for Reading Assessment
QuelleIn: Reading and Writing: An Interdisciplinary Journal, 25 (2012) 1, S.189-215 (27 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0922-4777
DOI10.1007/s11145-010-9253-z
SchlagwörterSpelling; Silent Reading; Oral Reading; Structural Equation Models; Word Recognition; Reading Rate; Regression (Statistics); Reading Tests; Reading Achievement
AbstractThis study examined how well elementary students' performance on a set of commonly-used reading assessments conformed to a model of automatic print processing. The assessments included measures of word recognition-untimed, word recognition-timed, oral reading accuracy, oral reading rate, silent reading rate, and spelling. The proposed print-processing model, based on the work of Perfetti (1992) and Share (1995), held that contextual reading accuracy is directly related to automatized word knowledge which is directly related to reading rate. Structural equation modeling showed that the performance data had an acceptable fit to the proposed model and to a second, post hoc model in which automatic word recognition is directly related to contextual reading accuracy. However, additional regression analyses tended to favor the initial model. Because the six print-processing components in this study proved to be reliable and related, and because two of the components (word recognition-timed and spelling) are seldom used in conventional reading assessments, the results have important implications for practice. (As Provided).
AnmerkungenSpringer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2017/4/10
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