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This research investigates how effectively automated source-code analysis can assess computational thinking skills in programming education.

July 26, 2026Applied SciencesOpen Access

Towards a Code-Based Assessment of Computational Thinking Skills

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This research investigates how effectively automated source-code analysis can assess computational thinking skills in programming education.
Controlled study with 44 students in a Data Structures course completing four programming exercises.
Assessment involved automated code metrics, expert rubric evaluation, and CT self-efficacy scale.
Data analyzed using Spearman correlations, quartile analyses, and qualitative case inspections.
Automated metrics and expert evaluations did not converge at the per-student level for either computational thinking skill.
One exercise showed convergence with expert evaluation, while another revealed complementary skill facets.
Qualitative analysis highlighted the value of distinct insights from each assessment method.

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Controlled study examines code-based assessment of computational thinking skills, suggesting multi-source evaluation for improved validity.

Alpizar-Chacón et al. (2026) studied this question.

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Controlled study examines code-based assessment of computational thinking skills, suggesting multi-source evaluation for improved validity.