Computational Concepts and their Assessment in Preschool Students: An Empirical Study

Abstract

Computational thinking (CT) is a multidimensional term that encompasses a wide variety of problem-solving skills related to the field of computer science. Unfortunately, standardized, valid, and reliable methods to assess CT skills in preschool children are lacking, compromising the reliability of the results reported in CT interventions. To surpass this limitation, we validated in a sample of 700 preschool students (5–6 years old) the Beginners Computational Thinking test Short-Form (BCTt-SF), an unplugged 12-item instrument that measures three of the most common computational concepts assessed in preschool research: sequences, loops, and conditionals. The theoretical model underpinning the BCTt-SF was supported by dimensionality assessment, which suggested that preschool students can be distinguished in terms of four specific abilities (i.e., sequences, simple loops, nested loops, and conditionals) and that all of these abilities were related by a general factor. We modeled this hierarchical structure with a bi-factor model that presented excellent psychometric properties, from good statistical fit indices to adequate reliability of the general ability. To take full advantage of this model, we created an online application in the Shiny platform (https://computationalthinkingtests.shinyapps.io/SF-BCTt/) for the seamless scoring of examinees by any teacher or researcher who uses the BCTt-SF to assess CT skills in preschool children. Finally, we demonstrated how the BCTt-SF can be used to test the impact of educational interventions for improving CT skills in preschoolers.