Level of computational thinking skills among first-year university students: Variation across gender, geographical background, academic discipline, and programming learning experience

Abstract

This study explores the current status of computational thinking (CT) skills among first-year university students and examines whether any differences exist across genders, geographic backgrounds and academic disciplines with programming learning experience given the growing interest in computational thinking (CT) in recent years. It also investigates the correlations among the five sub-dimensions of CT. 375 Chinese undergraduates were selected through random sampling and completed a computational thinking skills questionnaire. Data were analyzed using quantitative methods, including descriptive statistics, independent samples t-tests, and Pearson correlation analysis. The following results were found: (1) The overall CT skills of the first-year students reached a moderate level.  (2) Programming learning experience and academic discipline significantly influenced CT skills of undergraduates but no statistical difference was found across gender and geographic background. (3) There were significant and positive correlations among the five sub-dimensions of CT. The study reveals that differences in CT skills among first-year students are primarily associated with academic discipline and programming learning experience, emphasizing the need for targeted instructional strategies to support diverse learning backgrounds. The present study offers valuable insights into integrating CT into the university curriculum to benefit undergraduates across different academic disciplines.