Modeling Reading Growth in Grades 3 to 5 with an Alternate Assessment

Autor/inn/en	Farley, Dan; Anderson, Daniel; Irvin, P. Shawn; Tindal, Gerald
Titel	Modeling Reading Growth in Grades 3 to 5 with an Alternate Assessment
Quelle	In: Remedial and Special Education, 38 (2017) 4, S.195-206 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext (1); PDF als Volltext kostenfreie Datei (2) Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0741-9325
DOI	10.1177/0741932516678661
Schlagwörter	Grade 3; Grade 4; Grade 5; Elementary School Students; Reading Tests; Reading Achievement; Achievement Gains; Student Characteristics; Alternative Assessment; Intellectual Disability; High Stakes Tests; Research Methodology; Goodness of Fit; Effect Size; Symptoms (Individual Disorders); Statistical Analysis; Scores + Suchen Sie Ihr Suchwort? School year 03; 3. Schuljahr; Schuljahr 03; School year 04; 4. Schuljahr; Schuljahr 04; School year 05; 5. Schuljahr; Schuljahr 05; Lesetest; Leseleistung; Achievement gain; Leistungssteigerung; Intellect; Disability; Disabilities; Verstand; Behinderung; Research method; Forschungsmethode; Psychiatrische Symptomatik; Statistische Analyse
Abstract	Modeling growth for students with significant cognitive disabilities (SWSCD) is difficult due to a variety of factors, including, but not limited to, missing data, test scaling, group heterogeneity, and small sample sizes. These challenges may account for the paucity of previous research exploring the academic growth of SWSCD. Our study represents a unique context in which a reading assessment, calibrated to a common scale, was administered statewide to students in consecutive years across Grades 3 to 5. We used a nonlinear latent growth curve pattern-mixture model to estimate students' achievement and growth while accounting for patterns of missing data. While we observed significant intercept differences across disability subgroups, there were no significant slope differences. Incorporating missing data patterns into our models improved model fit. Limitations and directions for future research are discussed. (As Provided).
Anmerkungen	SAGE Publications and Hammill Institute on Disabilities. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01