Developing Young Learners’ Logical/Deductive Thinking Skills and Second Language Skills through a CLIL approach

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teaching English as a Second / Foreign Language.

Conditional and syllogistic deductive tasks dissociate functionally during premise integration.

Deduction allows us to draw consequences from previous knowledge. Deductive reasoning can be applied to several types of problem, for example, conditional, syllogistic, and relational. It has been assumed that the same cognitive operations underlie solutions to them all; however, this hypothesis remains to be tested empirically. We used event-related fMRI, in the same group of subjects, to compare reasoning-related activity associated with conditional and syllogistic deductive problems. Furthermore, we assessed reasoning-related activity for the two main stages of deduction, namely encoding of premises and their integration. Encoding syllogistic premises for reasoning was associated with activation of BA 44/45 more than encoding them for literal recall. During integration, left fronto-lateral cortex (BA 44/45, 6) and basal ganglia activated with both conditional and syllogistic reasoning. Besides that, integration of syllogistic problems additionally was associated with activation of left parietal (BA 7) and left ventro-lateral frontal cortex (BA 47). This difference suggests a dissociation between conditional and syllogistic reasoning at the integration stage. Our finding indicates that the integration of conditional and syllogistic reasoning is carried out by means of different, but partly overlapping, sets of anatomical regions and by inference, cognitive processes. The involvement of BA 44/45 during both encoding (syllogisms) and premise integration (syllogisms and conditionals) suggests a central role in deductive reasoning for syntactic manipulations and formal/linguistic representations.

Formalizing defeasible argumentation using a labeled deductive system

In the last years there has been an increasing demand of a variety of logical systems, prompted mostly by applications of logic in AI, logic programming and other related areas. Labeled Deductive Systems (LDS) were developed as a flexible methodology to formalize such a kind of complex logical systems. In the last decade, defeasible argumentation has proven to be a confluence point for many approaches to formalizing commonsense reasoning. Different formalisms have been developed, many of them sharing common features. This paper presents a formalization of an LDS for defensible argumentation, in which the main issues concerning defeasible argumentation are captured within a unified logical framework. The proposed framework is defined in two stages. First, defeasible inference will be formalized by characterizing an argumentative LDS. That system will be then extended in order to capture conflict among arguments using a dialectical approach. We also present some logical properties emerging from the proposed framework, discussing also its semantical characterization.

Logique deductive et inductive

UANL

System for Automated Deduction (SAD): Linguistic and Deductive Peculiarities

In this paper a state of the art of a system of automated deduction called SAD is described . An architecture of SAD corresponds well to a modern vision of the Evidence Algorithm programme, initiated by Academician V.Glushkov.

A method of anatomy, descriptive and deductive.

Mode of access: Internet.

A method of anatomy, descriptive and deductive,

Mode of access: Internet.