Validating Educational Assessments: The Callysto Computational Thinking Test

• In Event: Rasch Modeling Applications

Abstract

Computational thinking (CT) is a 21st-century competency that encompasses complex skills and attitudes relating to technology literacy, problem-solving, coding literacy, and data literacy. We present the Callysto Computational Thinking test (CCTt) for K-12 teachers that surveys CT perspectives and attitudes, CT concepts and practices, and problem-solving. After administering the CCTt to a group of pre-service teachers, we investigated the validity and reliability evidence of the instrument using Rasch-model item analyses, confirmatory factor analyses, and internal consistency analyses. Results demonstrate the CCTt is a reliable and valid instrument for assessing pre-service teachers’ CT competency and self-conception, and that participants with higher CCTt scores performed better in an Educational Technology course, thereby indicating that CT is related to other competencies.

Authors

• Connie Yuen, University of Alberta

• Chang Lu, Shanghai Jiao Tong University

• Florence A. Glanfield, University of Alberta

• Maria Cutumisu, University of Alberta

• Catherine Adams, University of Alberta