Analysis of Knowledge Structure Network Representations: an Example for Tenth-grade Fundamental Mechanics

Author: Pai-hsiang Huang(Department of Early Childhood Care & Education, Tajen University), Shing-Ho Chiang, Jeng-Fung Hung(Institute of Science Education, National Kaohsiung Normal University)

Vol.&No.：Vol. 52, No.1&2
Date：October 2007
Pages：79-104
DOI：10.6300/JNTNU.2007.52.04

Abstract：

The purpose of this study is to apply the Pathfinder Method to analyze the mechanics knowledge structure of tenth-grade students. This study investigates the predictive efficacy of learning achievements by knowledge structure indices. It also analyzes both the patterns difference in knowledge structure network representations and the node activation in problem solving. The subjects included 148 tenth-grade students from Kaohsiung district schools. The tools employed in this study included a mechanics knowledge structure assessment, a foundational mechanics achievement test, and an assessment of the analysis of problem solving with thinking aloud. The main findings were: (1) The knowledge structure indices can effectively predict learning achievement; among the three indices the one most able to predict students’ learning achievement was found to be the PFC index (R=.635，R2 ＝.404). (2) The knowledge structures of the high-achiever group were found to be organized with a super-ordinate concept in the center, and compared with the low-achiever group were more hierarchical, displaying tree structures that connected related concepts by concept definition. These variations influenced students’ ability to extract concepts and their node activation path, and thus influenced their performance in physics problem-solving. These results are thought to have relevance for curriculum design and pedagogy.

Keywords：knowledge structure, Pathfinder Method, network representations, fundamental mechanics

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