The way that individuals solve syllogisms is an important topic of deductive reasoning studies. Item response theory permits to select items that maximize information for estimating accurately ability levels. In this work, the two-parameter logistic model was applied to obtain the information functions of categorical syllogisms in order to select the subset that maximized them. A test of 26 syllogisms was administered to 405 students of psychology. BILOG-MG program was run iteratively by applying the two parameter logistic model. The test information function was examined at each iteration, and items with low discrimination were excluded. The process ended when the information function reached the maximum. Six syllogisms were kept that gave their greatest information at the 1.123 difficulty level, which is a medium-high level. The maximum test information was 7.594 and its reliability was 0.744, which may be considered good taking into account the small size of the subset. Every syllogism had valid conclusion. The method allowed finding a core of syllogisms without losing information that might constitute a short test keeping accuracy when estimating ability. It is useful to have a statistical criterion to select items for a briefed test and, thus, avoid the fatigue.
Keywords:
syllogisms, measurement, two parameter logistic model, information function, reliability
Galibert, M. S., Lozzia, G. S., & Aguerri, M. E. (2017). Maximum information of syllogisms by fitting the two-parameter logistic model. Revista De Psicología, 26(1). https://doi.org/10.5354/0719-0581.2017.46461
Twitter