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Computational Thinking in Life Science Education

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  • Amir Rubinstein
  • Benny Chor

Abstract

We join the increasing call to take computational education of life science students a step further, beyond teaching mere programming and employing existing software tools. We describe a new course, focusing on enriching the curriculum of life science students with abstract, algorithmic, and logical thinking, and exposing them to the computational “culture.” The design, structure, and content of our course are influenced by recent efforts in this area, collaborations with life scientists, and our own instructional experience. Specifically, we suggest that an effective course of this nature should: (1) devote time to explicitly reflect upon computational thinking processes, resisting the temptation to drift to purely practical instruction, (2) focus on discrete notions, rather than on continuous ones, and (3) have basic programming as a prerequisite, so students need not be preoccupied with elementary programming issues. We strongly recommend that the mere use of existing bioinformatics tools and packages should not replace hands-on programming. Yet, we suggest that programming will mostly serve as a means to practice computational thinking processes. This paper deals with the challenges and considerations of such computational education for life science students. It also describes a concrete implementation of the course and encourages its use by others.

Suggested Citation

  • Amir Rubinstein & Benny Chor, 2014. "Computational Thinking in Life Science Education," PLOS Computational Biology, Public Library of Science, vol. 10(11), pages 1-5, November.
  • Handle: RePEc:plo:pcbi00:1003897
    DOI: 10.1371/journal.pcbi.1003897
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    Cited by:

    1. Berk Ekmekci & Charles E McAnany & Cameron Mura, 2016. "An Introduction to Programming for Bioscientists: A Python-Based Primer," PLOS Computational Biology, Public Library of Science, vol. 12(6), pages 1-43, June.
    2. Ching-Hsiang Lai & Yan-Kwang Chen & Ya-huei Wang & Hung-Chang Liao, 2022. "The Study of Learning Computer Programming for Students with Medical Fields of Specification—An Analysis via Structural Equation Modeling," IJERPH, MDPI, vol. 19(10), pages 1-17, May.

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