Computational Thinking Self-Efficacy Scale: Development, Validity and Reliability

Abstract

The aim of this study is to develop a self-efficacy measuring tool that can predict the computational thinking skill that is seen as one of the 21st century's skills. According to literature review, an item pool was established and expert opinion was consulted for the created item pool. The study group of this study consists of 319 students educated at the level of secondary school. As a result of the exploratory factor analysis, the scale consisted of 18 items under four factors. The factors are Reasoning, Abstraction, Decomposition and Generalization. As a result of applied reliability analysis, the Cronbach Alpha reliability coefficient can be seen to be calculated as .884 for the whole self-efficacy scale consisting of 18 items. Confirmative factor analysis results and fit indexes were checked, and fit indexes of the scale were seen to have good and acceptable fits. Based on these findings, the Computational Thinking Self-efficacy Scale is a valid and reliable tool that may be used in measuring to predict Computational Thinking.

Keywords

• Computational Thinking
• self-efficacy
• programming and programming languages
• assessment methodologies