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Varying the Valuating Function and the Presentable Bank in Computerized Adaptive Testing

Published online by Cambridge University Press:  10 January 2013

Juan Ramón Barrada,
Francisco José Abad and
Julio Olea
Juan Ramón Barrada*
Affiliation:
Universidad Autónoma de Barcelona (Spain)
Francisco José Abad
Affiliation:
Universidad Autónoma de Madrid (Spain)
Julio Olea
Affiliation:
Universidad Autónoma de Barcelona (Spain)
*
Correspondence concerning this article should be addressed to Juan Ramón Barrada. Facultad de Psicología. Universidad Autónoma de Barcelona. 08193 Bellaterra. Barcelona. (Spain). Phone: +34-935813263. E-mail: juanramon.barrada@uab.es
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Abstract

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In computerized adaptive testing, the most commonly used valuating function is the Fisher information function. When the goal is to keep item bank security at a maximum, the valuating function that seems most convenient is the matching criterion, valuating the distance between the estimated trait level and the point where the maximum of the information function is located. Recently, it has been proposed not to keep the same valuating function constant for all the items in the test. In this study we expand the idea of combining the matching criterion with the Fisher information function. We also manipulate the number of strata into which the bank is divided. We find that the manipulation of the number of items administered with each function makes it possible to move from the pole of high accuracy and low security to the opposite pole. It is possible to greatly improve item bank security with much fewer losses in accuracy by selecting several items with the matching criterion. In general, it seems more appropriate not to stratify the bank.

En los tests adaptativos informatizados, la función de valoración más comúnmente empleada es la función de información de Fisher. Cuando el objetivo es mantener al máximo la seguridad del banco de ítems, la función de valoración que parece más adecuada es el criterio de proximidad, con el que se valora la distancia entre el nivel de rasgo estimado y el punto donde es máxima la información proporcionada por un ítem. Recientemente, se ha propuesto no mantener la misma regla de valoración constante a lo largo de todo el test. En este estudio, expandimos la idea de combinar el criterio de proximidad con la función de información de Fisher. También manipulamos el número de estratos en los que se divide el banco. Encontramos que la manipulación del número de ítems administrados con cada función hace posible moverse desde el extremo de alta precisión y baja seguridad hasta el extremo opuesto. La selección de varios ítems con el criterio de proximidad hace posible mejorar en gran medida la seguridad del banco con pérdidas escasas en precisión. En general, parece más adecuado no estratificar el banco.

Keywords

computerized adaptive testingitem selection ruleitem bank securityoverlap ratetests adaptativos informatizadosregla de selección de ítemsseguridad del banco de ítemstasa de solapamiento

Information

Type
Research Article
Information
The Spanish Journal of Psychology , Volume 14 , Issue 1 , May 2011, pp. 500 - 508
Copyright
Copyright © Cambridge University Press 2011

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