Using HLM and NAEP Data To Explore School Correlates of 1990 Mathematics and Geometry Achievement in Grades 4, 8, and 12: Methodology and Results. Research and Development Report.

Autor/in	Arnold, Carolyn L.
Institution	MPR Associates, Berkeley, CA.
Titel	Using HLM and NAEP Data To Explore School Correlates of 1990 Mathematics and Geometry Achievement in Grades 4, 8, and 12: Methodology and Results. Research and Development Report.
Quelle	(1995), (213 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
ISBN	0-16-045449-2
Schlagwörter	Quantitative Daten; Academic Achievement; Correlation; Elementary Secondary Education; Ethnicity; Geometry; Grade 12; Grade 4; Grade 8; Institutional Characteristics; Mathematics Achievement; Outcomes of Education; Prediction; Racial Differences; Research Methodology; Sex Differences; Tables (Data); National Assessment of Educational Progress + Suchen Sie Ihr Suchwort? Schulleistung; Korrelation; Ethnizität; Geometrie; School year 12; 12. Schuljahr; Schuljahr 12; School year 04; 4. Schuljahr; Schuljahr 04; School year 08; 8. Schuljahr; Schuljahr 08; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Lernleistung; Schulerfolg; Vorhersage; Rassenunterschied; Research method; Forschungsmethode; Sex difference; Geschlechtsunterschied; Tabelle
Abstract	This report illustrates the use of hierarchical linear models (HLM) with National Assessment of Educational Progress (NAEP) data to identify school and other correlates of student achievement. Based on an analysis of the 1990 NAEP mathematics achievement data for 4th, 8th, and 12th graders in public schools, this study is part of an ongoing exploratory effort to demonstrate the potential usefulness of HLM with NAEP data. The focus of the report is on the methodology of using HLM with NAEP data, and results of the study are presented as an illustration of the methodology. HLM accurately models the multilevel nature of the data and enables student-level outcomes such as gender and race/ethnicity to be predicted as a function of school-level factors. Several types of HLM analysis were conducted on 1990 NAEP data to predict achievement outcomes in mathematics and geometry, predicting average achievement between schools, the gender gap, and the race/ethnicity gap. The HLM methods worked well to explain variations in achievement but less well for the gender gap and race/ethnicity gaps. Results are discussed in the context of improving the usefulness of NAEP data. Data are presented in 66 tables, with 42 tables of supporting data in an appendix. (SLD)
Anmerkungen	U.S. Government Printing Office, Superintendent of Documents, Mail Stop: SSOP, Washington, DC 20402-9328.
Erfasst von	ERIC (Education Resources Information Center), Washington, DC