Examining the Relationship between Computational Thinking, Lifelong Learning Competencies and Personality Traits Using Path Analysis

Abstract

The purpose of this study is to determine the relationship between computational thinking, lifelong learning competencies and personality traits of university students. It was aimed to create a model that explains and predicts the relationship among the variables determined in the study. Convenience sampling method was used in determining the study group. Data were collected from 228 university students through social media. Descriptive statistics, correlation and path analysis were used to analyze the data. The results indicated that extroversion, agreeableness, and openness are statistically significant predictors of computational thinking. Among the personality traits, agreeableness yielded the greatest effect, while extroversion and openness resulted in medium effect on computational thinking. In addition, computational thinking significantly predicts lifelong learning competencies.