Computational Typologies of Multidimensional End-of-Primary-School Performance Profiles from an Educational Perspective of Large-Scale TIMSS and PIRLS Surveys

Autor/inn/en	Unlu, Ali; Schurig, Michael
Titel	Computational Typologies of Multidimensional End-of-Primary-School Performance Profiles from an Educational Perspective of Large-Scale TIMSS and PIRLS Surveys
Quelle	In: Current Issues in Comparative Education, 18 (2015) 1, S.6-25 (20 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1523-1615
Schlagwörter	Achievement Tests; Elementary Secondary Education; Mathematics Tests; Foreign Countries; International Assessment; Mathematics Achievement; Science Achievement; Science Tests; Grade 4; Reading Achievement; Reading Tests; Profiles; Multivariate Analysis; Classification; Elementary School Students; Item Response Theory; Comparative Analysis; Usability; Benchmarking; Goodness of Fit; Germany; Progress in International Reading Literacy Study; Trends in International Mathematics and Science Study + Suchen Sie Ihr Suchwort? Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen; Ausland; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; School year 04; 4. Schuljahr; Schuljahr 04; Leseleistung; Lesetest; Charakterisierung; Profilanalyse; Multivariate Analyse; Classification system; Klassifikation; Klassifikationssystem; Item-Response-Theorie; Deutschland
Abstract	Recently, performance profiles in reading, mathematics and science were created using the data collectively available in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS) 2011. In addition, a classification of children to the end of their primary school years was conducted in accordance with these performance types. To create performance profiles and classifications, multidimensional item response theory and latent profile analysis were used. The focus in this study is on the comparison and usability of clustering methods in their application in large-scale assessments. In a first step, the cluster solutions of classic approaches such as k-means, fuzzy c-means and hierarchical procedures are compared to one another and assessed in terms of their proximity to the reference typology of latent profile analysis. In the second step, the results of the model-supported latent profile analysis are compared directly with the findings of the classic model-free cluster analyses by means of appropriate measured values. The result is a high consistency in the classification of invariant ranked profiles. In the last step, the calculated "quantitative" cluster solutions are compared to the "qualitative" typology of the pupils derived from the content-based benchmarking of the competency levels in mathematics using the TIMSS guidelines. It is evident that, as a cluster solution, the benchmarking breakdown of the sample in the five competency levels does not show a high goodness of fit with the available data. (As Provided).
Anmerkungen	Teachers College, Columbia University. International and Transcultural Studies, P.O. Box 211, 525 West 120th Street, New York, NY 10027. e-mail: info@cicejournal.org; Web site: http://www.tc.columbia.edu/cice
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01