The Callysto Computational Thinking Test for undergraduate students: A psychometric study

• In Event: AERA Roundtable Session Saturday 11:45 am - Gold 4
  In Roundtable Session: Evaluating and Validating Measures of Student Learning and Performance

Abstract

Computational thinking (CT) is essential for acquiring 21st-century literacy. Accurate assessments of CT literacy are needed to provide individualized support, requiring reliable and valid instruments. To address this need, this study evaluated the Callysto Computational Thinking Test (CCTt) using data from 254 undergraduate students. Results confirmed that the CCTt reliably and validly assessed learners’ CT attitudes, skills, and problem-solving abilities, and it detected performance improvements. The CCTt also revealed a wide range of item difficulties and differentiated among learners' CT literacy. These findings support the use of the CCTt to monitor student CT literacy development and inform CT instruction in higher education. Several items were identified for further refinement to enhance the quality of this instrument.

Authors

• Yajie Song, McGill University

• Yimei Zhang, McGill University

• Hao-Yue Jin, University of Alberta

• Chang Lu, Shanghai Jiao Tong University

• Connie Levina Yuen, Athabasca University

• Florence Glanfield, University of Alberta

• Catherine Adams, University of Alberta

• Maria Cutumisu, McGill University