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<p>As STEM education increasingly emphasizes the development of both cognitive and non-cognitive competencies, there remains a critical gap in understanding how pedagogical approaches such as design thinking can simultaneously foster computational thinking (CT) and learning motivation in primary school contexts. This study investigates the effectiveness of a design thinking–guided STEM intervention in fostering primary students’ CT skills and learning motivation. It further examines the moderating roles of gender and educational stage, while addressing three specific gaps: the lack of empirical evidence on design thinking as a framework for CT development, the need for a nuanced understanding of differential growth across CT dimensions, and the unresolved relationship between general STEM motivation and domain-specific CT performance. A one-month quasi-experimental study was conducted with 34 fourth- to sixth-grade students (22 male, 12 female) from a public school in Shenzhen, China. Participants engaged in a micro: bit–based project to design an automated plant monitoring system, structured around the five phases of design thinking: empathize, define, ideate, prototype, and test. CT was assessed using pre- and post-test Bebras challenges across five dimensions (abstraction, algorithmic thinking, decomposition, evaluation, and generalization). Learning motivation was measured using adapted STEM self-efficacy and ability belief scales. Data were analyzed using paired t-tests, ANOVA, and content analysis. Results revealed a statistically significant overall improvement in CT following the intervention. Among the five dimensions, evaluation skills showed the most substantial growth, while algorithmic thinking remained the strongest component throughout. However, decomposition and generalization exhibited relative declines in normalized scores, suggesting these areas require additional instructional support. No significant gender or grade-level differences were found in overall CT gains, although greater performance variability was observed among female students, and Grade 5 demonstrated the highest mean post-test score. Notably, no significant correlation emerged between CT performance and STEM motivation, challenging conventional assumptions about the motivation–cognition relationship in project-based learning environments. This study provides novel empirical evidence for design thinking as an effective pedagogical framework for cultivating multi-dimensional CT in primary STEM education. It advances the field by revealing differential developmental trajectories across CT components and identifying a dissociation between general STEM motivation and CT performance, findings that underscore the need for domain-specific motivational frameworks.</p>

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From empathy to algorithms: how design thinking pedagogy influences primary school students’ computational thinking skills and learning motivation in STEM education

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月16日

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  • Zhizi Zheng,
  • Siu Cheung Kong,
  • Yuqin Yang,
  • Yingfeng Liao,
  • Daner Sun

摘要

As STEM education increasingly emphasizes the development of both cognitive and non-cognitive competencies, there remains a critical gap in understanding how pedagogical approaches such as design thinking can simultaneously foster computational thinking (CT) and learning motivation in primary school contexts. This study investigates the effectiveness of a design thinking–guided STEM intervention in fostering primary students’ CT skills and learning motivation. It further examines the moderating roles of gender and educational stage, while addressing three specific gaps: the lack of empirical evidence on design thinking as a framework for CT development, the need for a nuanced understanding of differential growth across CT dimensions, and the unresolved relationship between general STEM motivation and domain-specific CT performance. A one-month quasi-experimental study was conducted with 34 fourth- to sixth-grade students (22 male, 12 female) from a public school in Shenzhen, China. Participants engaged in a micro: bit–based project to design an automated plant monitoring system, structured around the five phases of design thinking: empathize, define, ideate, prototype, and test. CT was assessed using pre- and post-test Bebras challenges across five dimensions (abstraction, algorithmic thinking, decomposition, evaluation, and generalization). Learning motivation was measured using adapted STEM self-efficacy and ability belief scales. Data were analyzed using paired t-tests, ANOVA, and content analysis. Results revealed a statistically significant overall improvement in CT following the intervention. Among the five dimensions, evaluation skills showed the most substantial growth, while algorithmic thinking remained the strongest component throughout. However, decomposition and generalization exhibited relative declines in normalized scores, suggesting these areas require additional instructional support. No significant gender or grade-level differences were found in overall CT gains, although greater performance variability was observed among female students, and Grade 5 demonstrated the highest mean post-test score. Notably, no significant correlation emerged between CT performance and STEM motivation, challenging conventional assumptions about the motivation–cognition relationship in project-based learning environments. This study provides novel empirical evidence for design thinking as an effective pedagogical framework for cultivating multi-dimensional CT in primary STEM education. It advances the field by revealing differential developmental trajectories across CT components and identifying a dissociation between general STEM motivation and CT performance, findings that underscore the need for domain-specific motivational frameworks.