How Structural Assessment of Knowledge Can Be Used for the Identification of Specific Alternative Conceptions and for Assessing Domain Competence in Physics

Abstract

The purpose of this study is to investigate the viability of Structural Assessment of Knowledge (SAK) as a tool for identifying alternative conceptions and for predicting domain performance in Physics. The process begins by eliciting and then representing students‘ knowledge. One of these types of knowledge is conceptual knowledge, which is important for performing procedural tasks. This thesis employs a cognitively based theoretical framework to uncover students‘ knowledge, and then represents that knowledge for analytical purposes using SAK. SAK uses the Pathfinder algorithm to empirically derive the semantic networks of the students‘ and experts‘ cognitive structures, by asking them both to rate the relatedness of pairs of physics terms. Comparing students‘ and experts‘ knowledge structures provided some support for the structural assessment theory. In particular, supporting evidence that Pathfinder networks help in predicting student‘s problem solving capabilities was attained.