Algorithmic thinking in early childhood

Abstract

The rising interest of educators, researchers, and policymakers around the world as far as the development of computational thinking skills in compulsory education is concerned is echoed in the plethora of research studies discussed in the pertinent literature. However, the successful injection of computation thinking in formal educational settings demands the construction of developmentally appropriate assessment tools. In this paper, we discuss a novel framework for assessing computational thinking skills in early childhood settings. The proposed framework was employed in a relevant quantitative research study conducted in the city of Heraklion, Crete, from February to June 2019, with a sample of 435 first and second graders and within the context of the Environmental Study course. This paper also provides evidence regarding the examination of age, gender, and learning achievements in the Environmental Study course as predictive factors of one of the core computational thinking competencies, namely algorithmic thinking. The research findings revealed that age and learning achievements in the Environmental Study course constitute predictive factors for algorithmic thinking skills in the first and second grade level of primary school. On the contrary, algorithmic thinking skills are not related to first and second graders’ gender. The results of this study provide a solid background for designing and implementing developmentally appropriate tools for cultivating and assessing computational thinking skills in the early years of schooling.