Using Structural Equation Modeling to Examine the Relationship Between Computational Thinking Attitudes and Skills

• In Event: Measurement and Assessment in Higher Education Roundtable

Abstract

The increasing interest of educational researchers in computational thinking (CT) led to a growing body of literature on CT frameworks, pedagogy, and assessment. However, few studies have been conducted to determine whether attitudes towards CT predict CT skills. Thus, the present study examines the relationship between pre-service teachers’ attitudes towards CT and their CT skills. The Callysto Computational Thinking Test (CCTt) for Teachers was administered to n=105 pre-service teachers to collect their CT attitudes and skills. Structural Equation Modeling was used to examine the relationships between participants’ CT skill levels and attitudes toward CT, technology, coding, data, and problem solving. Results revealed that only CT attitudes predicted CT skills. Importantly, findings provided validity evidence for the CCTt instrument.

Authors

• Chang Lu, Shanghai Jiao Tong University

• Connie Yuen, University of Alberta

• Florence A. Glanfield, University of Alberta

• Maria Cutumisu, University of Alberta

• Catherine Adams, University of Alberta