Critical behavior in a cross-situational lexicon learning scenario

The associationist account for early word learning is based on the co-occurrence between referents and words. Here we introduce a noisy cross-situational learning scenario in which the referent of the uttered word is eliminated from the context with probability gamma, thus modeling the noise produced by out-of-context words. We examine the performance of a simple associative learning algorithm and find a critical value of the noise parameter gamma(c) above which learning is impossible. We use finite-size scaling to show that the sharpness of the transition persists across a region of order tau(-1/2) about gamma(c), where tau is the number of learning trials, as well as to obtain the learning error (scaling function) in the critical region. In addition, we show that the distribution of durations of periods when the learning error is zero is a power law with exponent -3/2 at the critical point. Copyright (C) EPLA, 2012

SCIENTIFIC LANGUAGE RHETORIC: FROM THE THEORETICAL BASIS TO THE PRODUCTION OF DIDACTIC MATERIAL FOR UNDERGRADUATE CHEMISTRY TEACHING

This work is part of a study that focused on analyzing the contributions of didactic activities related to scientific language rhetoric characteristics aimed at developing students' abilities to identify such characteristics in chemistry scientific texts and critical reading of those texts. In this study, we present the theoretical basis adopted to determine the scientific discourse characteristics and for the production of the didactic material used in those activities. Latour, Coracini and Campanario studies on persuasive rhetorical strategies present in scientific articles aided the production of such material.