research-article

A computational thinking course accessible to non-stem majors

Authors:

Dennis Kafura,

Austin Cory Bart,

Bushra ChowdhuryAuthors Info & Claims

Journal of Computing Sciences in Colleges, Volume 34, Issue 2

Pages 157 - 163

Published: 01 December 2018 Publication History

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Abstract

We describe the content, pedagogy and technology of a computational thinking course. While open to students in all majors, in practice the course serves students in predominantly non-STEM majors. We have seen the positive impact on student motivation of the data science context used in the course and the pedagogical value of the "cohort" model of collaborative peer learning. The technology includes a scaffolded programming environment for accessing curated real-world data sets.

References

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Bart, A.C., Whitcomb, R., Kafura, D., Shaffer, C.A., Tilevich, E., 2017. Computing with CORGIS: Diverse, Real-world Datasets for Introductory Computing, Proceedings of SIGCSE '17, pp. 57--62, 2017.

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Chowdhury, B., Bart, A.C., Kafura, D., Analysis of Collaborative Learning in a Computational Thinking Class. Proceedings SIGCSE '18, pp. 143--148, 2018.

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Computational Thinking Course Site, https://think.cs.vt.e.du

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Eddy, S.L., Converse, M., Wenderoth, M.P., PORTAAL: A Classroom Observation Tool Assessing Evidence-Based Teaching Practices for Active Learning in Large Science, Technology, Engineering, and Mathematics Classes, CBE, Vol. 14, Summer 2015, p. 1--16.

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Guzdial, M., Tew, A.E. Imagineering inauthentic legitimate peripheral participation: an instructional design approach for motivating computing education. In Proceedings of ICER'06, 2006.

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Kafura, D., Bart, A.C., Chowdhury, B., Design and Preliminary Results from a Computational Thinking Course, Proceedings of ITiCSE '15, pp. 63--68, 2015.

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Lockwood, J., A. Mooney, A., Computational Thinking in Education: Where does it Fit? A systematic literary review, CoRR, 2017, vol. abs/1703.07659

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Cited By

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Barboza LMello RModell MTeixeira EHilliger IKhosravi HRienties BDawson S(2023)Blockly-DS: Blocks Programming for Data Science with Visual, Statistical, Descriptive and Predictive AnalysisLAK23: 13th International Learning Analytics and Knowledge Conference10.1145/3576050.3576097(644-649)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3576050.3576097
Gusukuma LBart AKafura DZhang JSherriff MHeckman SCutter PMonge A(2020)PedalProceedings of the 51st ACM Technical Symposium on Computer Science Education10.1145/3328778.3366913(1061-1067)Online publication date: 26-Feb-2020
https://dl.acm.org/doi/10.1145/3328778.3366913

A computational thinking course accessible to non-stem majors
1. Applied computing
2. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs

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cover image Journal of Computing Sciences in Colleges

Journal of Computing Sciences in Colleges Volume 34, Issue 2

December 2018

208 pages

ISSN:1937-4771

EISSN:1937-4763

Editor:
John Meinke
UMUC Europe, Retired

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Consortium for Computing Sciences in Colleges

Evansville, IN, United States

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Published: 01 December 2018

Published in JCSC Volume 34, Issue 2

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Barboza LMello RModell MTeixeira EHilliger IKhosravi HRienties BDawson S(2023)Blockly-DS: Blocks Programming for Data Science with Visual, Statistical, Descriptive and Predictive AnalysisLAK23: 13th International Learning Analytics and Knowledge Conference10.1145/3576050.3576097(644-649)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3576050.3576097
Gusukuma LBart AKafura DZhang JSherriff MHeckman SCutter PMonge A(2020)PedalProceedings of the 51st ACM Technical Symposium on Computer Science Education10.1145/3328778.3366913(1061-1067)Online publication date: 26-Feb-2020
https://dl.acm.org/doi/10.1145/3328778.3366913

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Computing for STEM majors: enhancing non CS majors' computing skills

Thinking about Computational Thinking: Lessons from Education Research

Teaching how to teach computational thinking

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