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<p>Computational Thinking (CT) is a foundational 21st-century competency, yet its affective architecture remains insufficiently differentiated and undermeasured in educational research. This study developed and validated the Computational Thinking Anxiety Scale (CTAS), a theory-informed instrument designed to assess the multidimensional nature of Computational Thinking Anxiety (CTA) among adolescents. Developed via expert Delphi review and longitudinally validated with 697 Chinese students aged 9–14, the CTAS exhibits a stable eight-factor structure (CFI = 0.974, RMSEA = 0.041). Age-stratified analyses suggested that some CTA facets were represented more consistently across age groups than others, with the 11–12-year group showing greater variability in loading patterns, whereas algorithm-related anxiety remained comparatively stable across cohorts. A 3-month follow-up (<i>N</i> = 387) confirmed high temporal stability (ICC = 0.983; <i>r</i> = .986) with no significant mean-level change. The CTAS demonstrated discriminant validity (trait anxiety <i>r</i> = –.01; gender <i>r</i> = .03) and weak associations with programming experience, but a substantial negative correlation with CT performance (CTP, <i>r</i> = –.43). As a reliable and age-comparable instrument, the CTAS enables affect-aware assessment and intervention design in educational computing environments.</p>

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The affective side of computational thinking: assessment of computational thinking anxiety in Chinese adolescents

  • 期刊论文

  • 发表日期：

    2026年7月11日

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  • Jinhua Wang,
  • Weipeng Yang,
  • Michael K. Yeung

摘要

Computational Thinking (CT) is a foundational 21st-century competency, yet its affective architecture remains insufficiently differentiated and undermeasured in educational research. This study developed and validated the Computational Thinking Anxiety Scale (CTAS), a theory-informed instrument designed to assess the multidimensional nature of Computational Thinking Anxiety (CTA) among adolescents. Developed via expert Delphi review and longitudinally validated with 697 Chinese students aged 9–14, the CTAS exhibits a stable eight-factor structure (CFI = 0.974, RMSEA = 0.041). Age-stratified analyses suggested that some CTA facets were represented more consistently across age groups than others, with the 11–12-year group showing greater variability in loading patterns, whereas algorithm-related anxiety remained comparatively stable across cohorts. A 3-month follow-up (N = 387) confirmed high temporal stability (ICC = 0.983; r = .986) with no significant mean-level change. The CTAS demonstrated discriminant validity (trait anxiety r = –.01; gender r = .03) and weak associations with programming experience, but a substantial negative correlation with CT performance (CTP, r = –.43). As a reliable and age-comparable instrument, the CTAS enables affect-aware assessment and intervention design in educational computing environments.