Specificity of Structural Assessment of Knowledge

Abstract

This study examines the specificity of information provided by structural assessment of knowledge (SAK). SAK is a technique which uses the Pathfinder scaling algorithm to transform ratings of concept relatedness into network representations (PFnets) of individuals’ knowledge. Inferences about individuals’ overall domain knowledge based on the similarity between their PFnets and a referent PFnet have been shown to be valid. We investigate a more fine grained evaluation of specific links in individuals’ PFnets for identifying particular strengths and weaknesses. Thirty-five undergraduates learned about a computer programming language and were then tested on their knowledge of the language with SAK and a problem solving task. The presence of two subsets of links in participants’ PFnets differentially predicted performance on two types of problems, thereby providing evidence of the specificity of SAK. Implications for the formative use of SAK in the classroom and in computer-based environments are discussed.