Assessing Algorithmic Thinking Skills in Relation to Age in Early Childhood STEM Education

Abstract

In the modern digital era, intensive efforts are made to inject computational thinking (CT) across science, technology, engineering, and mathematics (STEM) fields, aiming at formulating a well-trained citizenry and workforce capable of confronting intricate problems that would not be solvable unless exercising CT skills. Focusing on contributing to the research area of CT assessment in the first two years of primary school, we investigated the correlation of algorithmic thinking skills, as a fundamental CT competency, with students’ age in early childhood settings. This article reports a relevant research study, which we implemented under the umbrella of quantitative methodology, employing an innovative assessment tool we constructed for serving the needs of our study. The research was conducted within the context of the environmental study course, adding to the efforts of infusing CT into STEM fields. The study results shed light on the correlation between algorithmic thinking skills and age in early childhood, revealing that age is a predictor factor for algorithmic thinking and, therefore, for CT.