Participation in a computational thinking and educational robotics elective and change in reasoning and complex problem-solving: a matched longitudinal study of a population-based regional cohort

Introduction This study examines whether participation in a computational thinking and educational robotics (CT&ER) elective is associated with differential change in reasoning and complex problem-solving among lower secondary students in Burgenland, Austria. Methods From a regional cohort of 1,676 seventh-grade students at all 38 public middle schools, 1,383 participated. In this longitudinal quasi-experimental design, students who chose the elective Coding & Robotik (C&R; n = 404) were compared with students who chose other electives (n = 979). Principal analyses were conducted on a propensity-score-matched sample of 401 pairs (N = 802). Reasoning was assessed at t1 and t3 (KFT 4-12+R: figural and numeric) and dynamic problem-solving at three occasions (DYNAMIS-based tasks assessing system knowledge, exploration systematicity, and system control). Results The C&R group showed greater change than the control group on all outcomes. Standardized change-score differences were d = 0.48 for system knowledge, 0.30 for systematicity, and −0.23 for system control (negative values indicate improvement; task-count-invariant metric), and d = 0.32 for numeric and 0.33 for figural reasoning. All five effects held in multilevel models with random intercepts for schools and students and in baseline-adjusted analyses. Exploratory within-group analyses showed largely comparable change across sociodemographic subgroups, with one exception that survived correction for multiple testing in all three specifications estimated on the matched sample: students from more prosperous families showed larger gains in system control. Discussion Because computational thinking itself was not measured and assignment was not randomized, these findings establish association rather than causation and warrant replication in randomized designs with direct measurement of computational thinking.

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Publication Details

Journal
Frontiers in Education
Published
2026-11-04
DOI
https://doi.org/10.3389/feduc.2026.1959156
Primary Topic
Teaching and Learning Programming
Type
article
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article

Participation in a computational thinking and educational robotics elective and change in reasoning and complex problem-solving: a matched longitudinal study of a population-based regional cohort

Katja Scharenberg, Wolfram Rollett, Thomas Leitgeb
2 links
Frontiers in Education
Teaching and Learning Programming
article

Participation in a computational thinking and educational robotics elective and change in reasoning and complex problem-solving: a matched longitudinal study of a population-based regional cohort

Katja Scharenberg, Wolfram Rollett, Thomas Leitgeb
article en

Abstract

Introduction This study examines whether participation in a computational thinking and educational robotics (CT&ER) elective is associated with differential change in reasoning and complex problem-solving among lower secondary students in Burgenland, Austria. Methods From a regional cohort of 1,676 seventh-grade students at all 38 public middle schools, 1,383 participated. In this longitudinal quasi-experimental design, students who chose the elective Coding & Robotik (C&R; n = 404) were compared with students who chose other electives (n = 979). Principal analyses were conducted on a propensity-score-matched sample of 401 pairs (N = 802). Reasoning was assessed at t1 and t3 (KFT 4-12+R: figural and numeric) and dynamic problem-solving at three occasions (DYNAMIS-based tasks assessing system knowledge, exploration systematicity, and system control). Results The C&R group showed greater change than the control group on all outcomes. Standardized change-score differences were d = 0.48 for system knowledge, 0.30 for systematicity, and −0.23 for system control (negative values indicate improvement; task-count-invariant metric), and d = 0.32 for numeric and 0.33 for figural reasoning. All five effects held in multilevel models with random intercepts for schools and students and in baseline-adjusted analyses. Exploratory within-group analyses showed largely comparable change across sociodemographic subgroups, with one exception that survived correction for multiple testing in all three specifications estimated on the matched sample: students from more prosperous families showed larger gains in system control. Discussion Because computational thinking itself was not measured and assignment was not randomized, these findings establish association rather than causation and warrant replication in randomized designs with direct measurement of computational thinking.

Frontiers in EducationVol. 11
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Teaching and Learning Programming
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