Work

Computational Thinking in Grade 1: An Educational Robotics Study Using the intelino Smart Train

Year: 2026

Type: article

Abstract: Computational thinking is increasingly regarded as an important component of digital education in primary school. Educational robotics is often discussed as a promising way to introduce computational thinking and promote problem-solving skills, which are key for the future, in early learning settings. However, empirical evidence on the extent to which computational thinking can be systematically fostered in Grade 1 students through short robotics-based instructional units remains limited. This study therefore investigates whether the computational thinking of first graders can be supported through an educational robotics intervention using the intelino Smart Train. A quasi-experimental pre-test/post-test design with an intervention group and a control group was employed. Students completed TechCheck-1 at two measurement points (before and after the intervention) to assess their basic computational thinking skills. The intervention group participated in a six-unit instructional intervention in which they controlled the intelino Smart Train through colour-coded commands. The findings indicate that the participating children already showed comparatively high computational thinking skills at the beginning of the intervention. No significant gender differences were found, and the intervention group did not demonstrate a significant advantage over the control group, which may also be related to ceiling effects. However, both groups showed learning gains across the measurement period. The results suggest that computational thinking can already be meaningfully addressed in Grade 1, but its systematic promotion may require longer-term curricular integration rather than a single short, isolated intervention.

Source: Education Sciences

DOI: 10.3390/educsci16050686

Author: Raphael Fehrmann

Institution: University of Münster

Language: English

Topic: Teaching and Learning Programming

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,172