Application of Ontologies for Assessing Collaborative Problem Solving Skills

Abstract

Abstract Collaborative problem solving (CPS) has been deemed a critical twenty-first century competency for a variety of contexts. However, less attention has been given to work aimed at the assessment and acquisition of such capabilities. Recently large scale efforts have been devoted toward assessing CPS skills, but there are no agreed upon guiding principles for assessment of this complex construct, particularly for assessment in digital performance situations. There are notable challenges in conceptualizing the complex construct and extracting evidence of CPS skills from large streams of data in digital contexts such as games and simulations. In the current paper, we discuss how the in-task assessment framework (I-TAF), a framework informed by evidence-centered design, can provide guiding principles for the assessment of CPS in these contexts. We give specific attention to one aspect of I-TAF, ontologies, and describe how they can be used to instantiate the student model in evidence-centered design which lays out what we wish to measure in a principled way. We further discuss how ontologies can serve as an anchor representation for other components of assessment such as scoring rubrics, evidence identification, and task design.