On the Transfer of Problem Solving Skills with Educational Robotics and Turtle Graphics Programming
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Date
2025
Publication Type
Doctoral Thesis
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yes
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Abstract
In a rapidly evolving and increasingly complex world, problem-solving skills are regarded as critical competencies for both professional and personal development. Cultivating these abilities equips students to respond effectively and creatively to ever-changing demands. However, transferring acquired competencies to unfamiliar or novel problem contexts remains a significant challenge. The effectiveness of different teaching and learning approaches in fostering such transfer has yet to be thoroughly examined in the context of high school computer science education.
This study investigates and compares the effectiveness of two widely used instructional approaches for introducing programming at the high school level: a purely virtual, software-based method using turtle graphics, and a physical approach involving educational robotics. The central research question examines how these methods support the transfer of spatial thinking, algorithmic thinking (often referred to as “computational thinking”), and complex problem-solving—the ability to address problems characterized by multiple unknowns and interdependencies. The study also considers verbal, figural, and numerical reasoning abilities, students’ prior knowledge as potential moderators, and demographic characteristics as covariates.
To address these questions, a two-month quasi-experimental pre-post classroom intervention study was conducted across 39 German-speaking Swiss high school classes (N = 751, M(Age) = 15.26, N(female) = 402, N(male) = 349). Classes were randomly assigned to either an experimental group (receiving instruction in robotics or turtle graphics) or a control group (which did not participate in programming or robotics activities). Standardized teaching materials were developed and piloted to ensure instructional consistency across the experimental groups.
A new assessment tool was developed to measure computational thinking, incorporating cognitive dimensions such as abstraction, decomposition, evaluation, algorithm design, and generalization, and enabling the analysis of both proximal and distal transfer. The results indicated significant gains in both computational and spatial abilities among the experimental groups, surpassing the control group's performance. Robotics instruction produced substantial learning gains across nearly all domains, with particularly notable outcomes for female students. Learners with above-average cognitive abilities improved significantly in computational thinking across both instructional formats, whereas those with below-average cognitive abilities benefited more from the robotics-based approach.
Students’ motivation to program remained stable in both experimental groups and did not change significantly throughout the intervention.
Future research should investigate additional influencing factors such as socio-economic status, motivation, and learners’ academic self-concept to advance our understanding of transfer performance further.
In conclusion, this study demonstrates that both instructional approaches effectively teach problem-solving skills when accounting for key moderating factors. The findings provide meaningful guidance for educational practice, suggesting that incorporating robotics into the regular curriculum offers clear added value in fostering students’ problem-solving competencies.
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published
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Contributors
Examiner : Stern, Elsbeth
Examiner : Komm, Dennis
Examiner : Romeike, Ralf
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Pages / Article No.
Publisher
ETH Zurich
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Methods
Software
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Subject
Computational Thinking; Transfer of cognitive skills; Spatial abilities; Educational robotics; Programming; Turtle graphics; Classroom Intervention study
Organisational unit
03753 - Stern, Elsbeth (ehemalig) / Stern, Elsbeth (former)