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Exploring Networks of Problem-solving Interactions by Michael Eagle; Drew Hicks; Barry Peddycord; Tiffany Barnes is a scholarly article available to read on EtoBox.

What is Exploring Networks of Problem-solving Interactions about?

Intelligent tutoring systems and other computer-aided learning environments produce large amounts of transactional data on student problem-solving behavior, in previous work we modeled the student-tutor interaction data as a complex network, and successfully generated automated nextstep hints as well as visualizations for educators. In this work we discuss the types of tutoring environments that are best modeled by interaction networks, and how the empirical observations of problem-solving result in common network features. We find that interaction networks exhibit the properties of scale-free networks such as vertex degree distributions that follow power law. We compare data from two versions of a propositional logic tutor, as well as two different representations of data from an educational game on programming. We find that statistics such as degree assortativity and the scale-free metric allow comparison of the network structures across domains, and provide insight into student problem solving behavior.

Author

Michael Eagle; Drew Hicks; Barry Peddycord; Tiffany Barnes

Publisher

ACM

Published

2015

Language

EN