Computational thinking in K-12 education. An insight through meta-analysis

Abstract

The interest in computational thinking development at pre-university education stage is increasing. In this study, a meta-analysis was conducted to address two main objectives: (a) to analyze the effectiveness of empirical interventions in K-12 education for the development of Computational Thinking (CT); and (b) to identify and evaluate the variables that influences the effectiveness of the interventions. The analysis was especially focused on the intra-group effect sizes. Interventions show large effect size in the development of CT in the comparison between pre- and post-tests (g = 1.044). Among the different types of interventions, programming is the most efficient learning tool.

Keywords:

• Computational thinking
• effectiveness
• meta-analysis
• K-12
• educational research

Notes

1 Includes preprint papers which publication date could be 2020, but there are available before.

Additional information

Notes on contributors

José Miguel Merino-Armero

José Miguel Merino-Armero is a primary school teacher. His main areas of work are computational thinking and educational robotics.

José Antonio González-Calero

José Antonio González-Calero is a lecturer at the Department of Mathematics of the University of Castilla-La Mancha (Spain), with research interests in mathematics education, technology-based learning and problem solving.

Ramón Cózar-Gutiérrez

Ramón Cózar-Gutiérrez works as a lecturer at the Department of History (University of Castilla-La Mancha, Spain). His research interest is centered on social science education, teacher training and educational innovation and technology.