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<p>In this paper, we are interested in the learning outcomes from undergraduate students’ digital experiences of conducting multiple pure and applied mathematics investigations supported by programming technology. Our case study encompasses a sequence of three project-based mathematics courses implemented for over 20&#xa0;years at Brock University. We conceptualize learning by using elements of theories of community of practice, constructionism, and instrumental genesis. Data was collected through post-course voluntary anonymous questionnaires (N = 31) from the 2nd and 3rd courses. Our results suggest five key dimensions of learning outcomes falling under the three domains (cognitive, intrapersonal and interpersonal) of deeper learning: (1) programming as a useful tool for mathematics and more broadly; (2) computational thinking as a useful competency for mathematics and more broadly; (3) attitudes toward learning to program and programming practices (for mathematics); (4) interest and motivation in expanding one’s understanding of mathematical concepts; and (5) learning about self as a learner. Arising from these results, we argue that opportunities derived from conducting multiple programming-based pure and applied mathematics investigations may empower undergraduate students in their mathematical thinking and activity.</p>

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University Students’ Views of Their Learning Outcomes from Engaging in Programming-Based Mathematical Investigations

  • 期刊论文

  • 发表日期：

    2025年3月1日

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  • Chantal Buteau,
  • Eric Muller,
  • Joyce Mgombelo,
  • Ana Isabel Sacristán,
  • Jessica Sardella,
  • Marisol Santacruz-Rodríguez

摘要

In this paper, we are interested in the learning outcomes from undergraduate students’ digital experiences of conducting multiple pure and applied mathematics investigations supported by programming technology. Our case study encompasses a sequence of three project-based mathematics courses implemented for over 20 years at Brock University. We conceptualize learning by using elements of theories of community of practice, constructionism, and instrumental genesis. Data was collected through post-course voluntary anonymous questionnaires (N = 31) from the 2nd and 3rd courses. Our results suggest five key dimensions of learning outcomes falling under the three domains (cognitive, intrapersonal and interpersonal) of deeper learning: (1) programming as a useful tool for mathematics and more broadly; (2) computational thinking as a useful competency for mathematics and more broadly; (3) attitudes toward learning to program and programming practices (for mathematics); (4) interest and motivation in expanding one’s understanding of mathematical concepts; and (5) learning about self as a learner. Arising from these results, we argue that opportunities derived from conducting multiple programming-based pure and applied mathematics investigations may empower undergraduate students in their mathematical thinking and activity.