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

Maria Cutumisu, Catherine Adams, Florence Glanfield, Connie Yuen, Chang Lu

2021IEEE Transactions on Education16 citationsDOI

Abstract

The growing interest of educational researchers in computational thinking (CT) has led to an expanding literature on assessments of CT skills and attitudes. However, few studies have examined whether CT attitudes influence CT skills. The present study examines the relationship between CT attitudes and CT skills for preservice teachers (PSTs). The Callysto CT test (CCTt) for Teachers was administered to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n\,\,=$ </tex-math></inline-formula> 105 PSTs to measure their CT attitudes and skills. Structural equation modeling was used to examine the relationship of participants’ CT and problem-solving skills with their attitudes toward CT, technology, coding, and data. Findings revealed that CT attitudes predicted CT skills and provided the first step in exploring the validity and reliability of the CCTt instrument.

Topics & Concepts

Structural equation modelingNotationMathematics educationTest (biology)Coding (social sciences)PsychologyComputational thinkingReliability (semiconductor)MathematicsStatisticsArithmeticPhysicsQuantum mechanicsPaleontologyPower (physics)BiologyTeaching and Learning ProgrammingOnline Learning and AnalyticsGender and Technology in Education