%0 Journal Article
%T Aplicaci¨®n del modelo LLTM de Fischer al an¨¢lisis de las fuentes de dificultad de ¨ªtemes de razonamiento deductivo
%A Attorresi
%A Horacio F¨¦lix
%A Pic¨®n Janeiro
%A Jimena
%A Abal
%A Facundo
%A Aguerri
%A Mar¨ªa Ester
%A Galibert
%A Mar¨ªa Silvia
%J Interdisciplinaria
%D 2009
%I Scientific Electronic Library Online
%X the processes involved in deductive reasoning have been studied by cognitive psychology since the seventies. many hypotheses have been put forward to explain the difficulties in solving simple reasoning problems when considering their logical connectives, content and context of the tasks in which they are presented. these hypotheses have led to the development of different theories of reasoning like those based on the formal inference rules approach (braine, 1978; braine & o'brien, 1991; braine & rumain, 1983; rips, 1994), the pragmatic schemas theory (cheng & holyoak, 1985) and the theory of semantic mental models (johnson-laird, 1983, johnson-laird & byrne, 1991). the componential models of the item response theory have allowed psychometry to explain said these processes (embretson, 1994). thus, for instance, the linear logistic latent trait model (lltm) (fischer, 1973, 1997), an extension of the rasch model, expresses item difficulty as the sum of the effects due to the sources of difficulty predicted by the mentioned cognitive theories, which enables us to decide whether these effects are significant and estimate them. in other words, the rasch item parameters ¦Â1 are linearly decomposed in the form where p is the number of components considered, ¦Ál -the basic parameters of the model, expresses the difficulty of each component l, wil is the weight of ¦Ál with respect to the difficulty of the item i and c is an arbitrary normalization constant. formula (1) implies that the application of the lltm model makes sense only when the rasch model fits the data. on the other hand, if the proposed components were sufficiently exhaustive to explain the differences between the items, formula (1) would allow us, once the basic parameters ¦Ál have been estimated, to recover estimates similar to those obtained directly by the application of the rasch model, which would imply a high correlation between the parameters estimated under both models. the identification of the difficult
%K fischer lltm model
%K rasch model
%K sources of difficulty
%K deductive reasoning
%K cognitive theories
%K educational practice.
%U http://www.scielo.org.ar/scielo.php?script=sci_abstract&pid=S1668-70272009000100004&lng=en&nrm=iso&tlng=en