izpis_h1_title_alt

Student ability assessment based on two IRT models
ID Cagnone, Silvia (Avtor), ID Ricci, Roberto (Avtor)

URLURL - Predstavitvena datoteka, za dostop obiščite http://mrvar.fdv.uni-lj.si/pub/mz/mz2.1/cagnone.pdf Povezava se odpre v novem oknu

Izvleček
The aim of this work is to analyze a part of the data collected in the Computer Science Department during the Informatics exams in the year 2003. Twodifferent Item Response Theory models for ordered polytomous variables are considered in order to get an evaluation of student ability. Ordered polytomous variables are used for a problem solving process that contains a finite number of steps so that the ability of a student can be evaluated on the basis of the step achieved, namely, higher steps achieved are related to higher ability. The models considered are the Partial Credit Model and the Graded Response Model. The choice of these models has been dictated by the fact that although they are defined into different theoretical frameworks, theformer belongs to the Rasch family (Masters, 1982) and the latter can be viewed as a Generalized Linear Latent Variable Model (Bartholomew and Knott, 1999), and hence they present different properties, both of them allow to treat ordinal observed variables. The analysis of the real data set through the two approaches allows to highlight their advantages and disadvantages.

Jezik:Angleški jezik
Vrsta gradiva:Delo ni kategorizirano
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FDV - Fakulteta za družbene vede
Leto izida:2005
Št. strani:Str. 209-218
Številčenje:Vol. 2, no. 2
PID:20.500.12556/RUL-22452 Povezava se odpre v novem oknu
UDK:303
ISSN pri članku:1854-0023
COBISS.SI-ID:24315229 Povezava se odpre v novem oknu
Datum objave v RUL:11.07.2014
Število ogledov:526
Število prenosov:89
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del revije

Naslov:Metodološki zvezki
Skrajšan naslov:Metodol. zv.
Založnik:Fakulteta za družbene vede
ISSN:1854-0023
COBISS.SI-ID:215795712 Povezava se odpre v novem oknu

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