Specialized Rasch measures applied at the forefront of education.

Sonst. Personen	Waugh, Russell F. (Hrsg.)
Titel	Specialized Rasch measures applied at the forefront of education.
Quelle	New York, NY: Nova Science Publ. (2010), XIV, 226 S.Verfügbarkeit
Reihe	Education in a competitive and globalizing world series
Beigaben	grafische Darstellungen
Zusatzinformation	Inhaltsverzeichnis
Sprache	englisch
Dokumenttyp	gedruckt; Monographie
ISBN	1-61668-032-6; 978-1-61668-032-9
Schlagwörter	Rasch-Modell; Bildungsforschung; Fragebogenerhebung; Skalierung; Selbsteinschätzung; Itemanalyse; Schuljahr 10; Primarbereich; Sekundarbereich; Schüler; Leistungsbeurteilung; Schülerleistung; Gruppenarbeit; Computerprogramm; Datenanalyse; Datenbank; Lesen; Mathematikunterricht; Mathematisches Denken; Rechnen; Variable; Messverfahren; Statistik; Prüfverfahren; Student; Australien; Singapur
Abstract	In making a measure of a variable intended for Rasch analysis, items are designed to be conceptually ordered by difficulty along an increasing continuum from easy to harder for that variable. For the purpose of explanation here, [the author uses] three items ordered from easy to medium to hard. In designing the items, one keeps in mind that the respondent measures of the variable are conceptualised as being ordered along the continuum from low to high according to certain conditions. The conditions in the three-item example are that respondents with low measures will have a high probability of answering the easy items positively, and a low probability of answering the medium and hard items positively. Respondents with medium measures will have a high probability of answering the easy and medium items positively, and a low probability of answering the hard items positively. Respondents with high measures will have a high probability of answering the easy, medium and hard items positively. These conditions are tested through a Rasch analysis which provides a test of the structure of the variable. Data are collected from respondents on the items and scored dichotomously (0/1), as in, for example, but not limited to, wrong/right, no/yes, none/a lot, disagree/agree, some/often, bad/good, slow/fast, or the items can be scored with three or more responses as, for example, with none (0), some (1), most (2) and always (3). It is better to have an ordered response set and the RUMM computer program will test whether the response categories are being answered consistently and logically for each item. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2011/3