Literaturnachweis - Detailanzeige
Autor/in | Burstein, Leigh |
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Institution | Center for Research on Evaluation, Standards, and Student Testing, Los Angeles, CA. |
Titel | Conceptual Considerations in Instructionally Sensitive Assessment. |
Quelle | (1989), (14 Seiten)
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Monographie |
Schlagwörter | Academic Ability; Academic Achievement; Achievement Tests; Data Analysis; Educational Assessment; Factor Analysis; Grade 8; International Studies; Junior High School Students; Junior High Schools; Mathematics Tests; Psychometrics; Research Design; Testing Programs Schulleistung; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen; Auswertung; Education; assessment; Bewertungssystem; Faktorenanalyse; School year 08; 8. Schuljahr; Schuljahr 08; Internationaler Studiengang; Junior High Schools; Student; Students; Sekundarstufe I; Schüler; Schülerin; Psychometry; Psychometrie; Forschungsdesign |
Abstract | The conceptual framework for the instructionally sensitive assessment that guided the analyses of data from the Second International Mathematics Study (SIMS) are described. The intellectual rationale for the project effort and the current draft version of the guiding conception of "instructionally sensitive psychometrics" are discussed, and practical realities of large-scale assessment derived from the analysis of SIMS data so far are considered. Some clear issues in instructionally sensitive assessment are identified. Predominant are the use of multiple means of assessment and sensitivity to specific aspects of student achievement and ability. It is evident that refining and clarifying the current conception of instructional sensitivity is necessary, as is thinking carefully about the adequacy of achievement trait modeling. The psychometric aim of the analysis of SIMS data is to try to isolate specific factors corresponding to more narrowly defined sets of items in a factor analysis modeling when a dominant factor is present. (SLD) |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |