Detecting Bimodality in the Analogical Reasoning Performance of Elementary Schoolchildren

Abstract

This paper reports on modelling six frequency distributions representing the analogical reasoning performance of four different samples of elementary schoolchildren. A two-component model outperformed a one-component model in all investigated data sets, discriminating accurate performers with high success probabilities and inaccurate performers with low success probabilities, whereas for two data sets a three-component model provided the best fit. In a treatment-control group data set, the treatment group comprised a larger proportion of accurate performers than the control group, whereas the success probabilities of the two latent classes were nearly identical in both groups. In a repeated-measures data set, both the success probabilities of the two latent classes and the proportion of accurate performers increased from the first to the second test session. The results provided a first indication of a transition in the development of analogical reasoning in elementary schoolchildren.