Resumen

CARVALHO, José Luís; RAMOS, José Luís; CASAS GARCIA, Luis  y  LUENGO GONZALEZ, Ricardo. Estrutura cognitiva dos alunos e aprendizagem conceptual da matemática: contributos para o seu conhecimento através da técnica de Redes Associativas Pathfinder. Educ. Form. Tecnol. [online]. 2010, vol.03, n.01, pp.15-30. ISSN 1646-933X.

This paper describes a learning experience, which took place in a 4th grade Portuguese classroom and involved an educational intervention using a mathematical learning platform, named PmatE. The study aims at contributing for a better understanding of the student’s conceptual networks while learning two mathematical operations: division and multiplication. Before and after the use of the PmatE platform, participating students were subject to an evaluation of their mathematical concepts using a technique proposed by Schvaneveldt (1990) “PathFinder Associative Networks”, which generates arrays of data corresponding to the students’ conceptual network. These data matrices were then analyzed at different levels using the SPSS software. The CN_MeBa and the PATHFINDER software were used as tools for capturing students’ knowledge representation while solving mathematical problems by using the PmatE environment systematically. Results suggest differences in student’s mental representations of mathematical concepts related with division and multiplication operations in the beginning and at the end of the educational intervention. Regarding the similarity of students’ networks compared with the teacher’s networks, the analysis indicates that the differences between the results obtained before and after the intervention with PmatE were not significant. Conclusions and limitations of the study are discussed. The results suggests that this approach can be an useful method to understand students’ mathematical conceptual knowledge during the learning processes and help teachers’ to better analyze and observe students’ progress.

Palabras clave : Artificial Intelligence; Knowledge Representation; Cognitive Structure; Semantic Networks; Pathfinder Associative Network.

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