Grade of Membership Response Time Model for Detecting Guessing Behaviors

Autor/in	Pokropek, Artur
Titel	Grade of Membership Response Time Model for Detecting Guessing Behaviors
Quelle	In: Journal of Educational and Behavioral Statistics, 41 (2016) 3, S.300-325 (26 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998616636618
Schlagwörter	Reaction Time; Models; Guessing (Tests); Computation; Group Membership; Classification; Motivation; Ability; Monte Carlo Methods; Comparative Analysis; Bias; International Assessment; Foreign Countries; Maximum Likelihood Statistics; Australia; Austria; Belgium; Canada; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Ireland; Italy; Japan; Netherlands; Poland; Slovakia; South Korea; Spain; Sweden; United Kingdom (England); United Kingdom (Northern Ireland); United States + Suchen Sie Ihr Suchwort? Reaktionsvermögen; Analogiemodell; Erraten; Gruppenzugehörigkeit; Classification system; Klassifikation; Klassifikationssystem; psychologische; Motivation (psychologisch); Fähigkeit; Fertigkeit; Monte-Carlo-Methode; Ausland; Australien; Österreich; Belgien; Kanada; Zypern; Tschechische Republik; Dänemark; Estland; Finnland; Frankreich; Deutschland; Irland; Italien; Niederlande; Polen; Slowakei; Korea; Republik; Spanien; Schweden; USA
Abstract	A response model that is able to detect guessing behaviors and produce unbiased estimates in low-stake conditions using timing information is proposed. The model is a special case of the grade of membership model in which responses are modeled as partial members of a class that is affected by motivation and a class that responds only according to the level of ability. Monte Carlo simulations were conducted to compare the proposed model with an approach that ignored guessing and an approach based on item filtering. In each simulated condition, the proposed model outperformed the other approaches by showing the lowest level of bias and the highest precision of item and persons estimates. Finally, the model was estimated using real life data from Programme for the International Assessment of Adult Competencies research (PIAAC). The results showed slight but expected corrections for the levels of proficiency in all countries. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01