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Leveraging Computational Science Students' Coding Strengths for Mathematics Learning

Published:03 March 2023Publication History

ABSTRACT

The nebulous relationship between mathematics and computation in education has led to questions surrounding computational science students' experiences in mathematics courses. However, many of these conversations are framed in terms of students' misconceptions or their 'poor mathematical skills'. In contrast, I propose leveraging student's computational strengths as a pedagogical approach for creating relevant and engaging mathematics experiences. In order to build an understanding of the ways in which computation affects student's experience and understanding of mathematics, a framework designed to link student's computational experiences and attitudes by adding explicit linkage to these mathematical experiences was implemented. A series of Jupyter notebooks were developed which focused on introducing linear algebra through computing. This study followed computational science students as they worked through the modules in small groups across six weeks. They completed weekly reflections, and pre/post-study interviews. The theoretical framework was operationalized as an analytical framework to link student experience and attitudes. Results highlighted the shift in students' views of the nature of mathematics, their abilities, and the interplay between disciplines. The computational environment enabled students to naturally consider multiple solution paths, develop resilience, and enhanced their ability to explore mathematical concepts in a novel way. This was in contrast with students' initial views that framed mathematics as a set series of steps and formulas to follow. This study both provides a novel perspective in the discourse surrounding research on computational students' experiences in mathematics and highlights the pedagogical power of computing as a novel environment for learning mathematics.

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          cover image ACM Conferences
          SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1
          March 2023
          1481 pages
          ISBN:9781450394314
          DOI:10.1145/3545945

          Copyright © 2023 ACM

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          • Published: 3 March 2023

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