An Exploration of the Gap between Highest and Lowest Ability Readers across 20 Countries

Autor/in	Alivernini, Fabio
Titel	An Exploration of the Gap between Highest and Lowest Ability Readers across 20 Countries
Quelle	In: Educational Studies, 39 (2013) 4, S.399-417 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0305-5698
DOI	10.1080/03055698.2013.767187
Schlagwörter	Foreign Countries; Predictor Variables; Questionnaires; Regression (Statistics); Context Effect; Educational Resources; Literacy; Reading Ability; Reading Achievement; Achievement Gap; Educational Environment; Educational Finance; Educational Indicators; Teacher Salaries; Curriculum Design; School Surveys; Teacher Surveys; Family Environment; Parent Surveys; Elementary School Students; Low Achievement; Progress in International Reading Literacy Study + Suchen Sie Ihr Suchwort? Ausland; Prädiktor; Fragebogen; Regression; Regressionsanalyse; Bildungsmittel; Alphabetisierung; Schreib- und Lesefähigkeit; Reading competence; Lesekompetenz; Leseleistung; Lernumgebung; Pädagogische Umwelt; Schulumwelt; Bildungsfonds; Educational indicato; Bildungsindikator; Lehrerbesoldung; Lehrervergütung; Lehrplangestaltung; Familienmilieu; Unterdurchschnittliche Leistung
Abstract	The aim of the present study, based on data from 20 countries, is to identify the pattern of variables (at country, school and student levels), which are typical of students performing below the low international benchmark compared to students performing at the advanced performance benchmark, in the Progress in International Reading Literacy Study (PIRLS) 2006. The dependent variable of the analysis is a dichotomous variable, the values of which represent the two different performance groups of students. The independent variables are two sets of Organisation for Economic Co-operation and Development educational indicators, variables from PIRLS 2006 Reading Curriculum Questionnaire data, variables and indices based on data obtained from questionnaires for teachers, schools, parents and students. The analysis is based on classification and regression trees, which is a full hierarchical non-parametric method suited to detecting and interpreting complex reciprocal influences between a large number of independent variables. The results show that pupils' performance can be predicted by the relationships between country-level variables (the changes in teachers' salaries at the top of the salary scale), school context variables (e.g. percentages of students from economically affluent home) and home educational resources and variables at student level (e.g. students' reading self-concept). (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10