Unravelling the numerical and spatial underpinnings of computational thinking: a pre-registered replication study

ABSTRACT

Background

Key to optimizing Computational Thinking (CT) instruction is a precise understanding of the underlying cognitive skills. Román-González et al. (2017) reported unique contributions of spatial abilities and reasoning, whereas arithmetic was not significantly related to CT. Disentangling the influence of spatial and numerical skills on CT is important, as neither should be viewed as monolithic traits.

Objective

This study aimed (1) to replicate the results of a previous study by Román-González et al. (Computers in Human Behaviour 72), and (2) to extend this research by investigating other theoretically relevant constructs. Specifying the contribution of reasoning (i.e. numerical, figural), numerical skills (i.e. arithmetic, algebra), and spatial skills (i.e. visualization, mental rotation, short-term memory) helps to better understand the cognitive mechanisms underlying CT.

Method

We investigated a sample of 132 students from Grades 7–8 (age range 12–15 years). Participants completed the Computational Thinking test, as well as a variety of psychometric assessments of reasoning, numerical, and spatial skills. To determine which cognitive skills are relevant for CT, we calculated bivariate correlations and performed a linear regression analysis.

Findings

Results confirmed unique contributions of figural reasoning and visualization. Additional variance was explained by algebraic skills.

Implications

We conclude that CT engages cognitive mechanisms extending beyond reasoning and spatial skills.

KEYWORDS:

• Computational thinking
• cognitive abilities
• computer science education
• numerical processing
• spatial processing
• reasoning

Acknowledgments

The authors acknowledge the financial support by the University of Graz. We would like to thank Marcos Román-González for kindly sharing with us the original Computational Thinking test (CTt), as well as Josef Guggemos and Katerina Tsarava for their German-language adaptations. We would also like to thank Anna Exel very much for helping with administrative issues. Finally, we would like to thank students and teachers from the following schools supporting our research: BG/BRG Knittelfeld, BG/BRG Pestalozzi, BRG Kepler, KLEX Graz and MS Kepler.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data is publicly available on the Open Science Framework and can be accessed at https://osf.io/3c9mw

Notes

1. Although Román-González et al. (2017) did not explicitly report the number of participants considered in the regression analysis, we were able to derive this information from on the degrees of freedom of the regression models.

2. Previously, there were two German-language adaptations of the Computational Thinking Test (CTt) for other age groups: 1) Guggemos et al. (2019) developed a more difficult version for high-school students by replacing the five easiest CTt items with five harder items. 2) Tsarava et al. (2019) designed a version for children from primary school by selecting the 21 easiest CTt items and reducing administration time from 45 to 20 minutes. The novel version developed for this study constitutes a direct translation of all 28 items of the original CTt by Román-González et al. (2017).

Additional information

Funding

This work was supported by internal funding (Route 63) from the University of Graz and the Graz University of Technology.