Exploring Bimodality in Introductory Computer Science Performance Distributions

Ram B Basnet; Lori K Payne; Tenzin Doleck; David John Lemay; Paul Bazelais

doi:10.29333/ejmste/93190

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Ram B Basnet ¹, Lori K Payne ¹, Tenzin Doleck ² ^* , David John Lemay ², Paul Bazelais ²

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¹ Colorado Mesa University, Grand Junction, Colorado, USA
² McGill University, Montreal, Quebec, CANADA
^* Corresponding Author

Abstract

This study examines student performance distributions evidence bimodality, or whether there are two distinct populations in three introductory computer science courses grades at a four-year southwestern university in the United States for the period 2014-2017. Results suggest that computer science course grades are not bimodal. These findings counter the double hump assertion and suggest that proper course sequencing can address the needs of students with varying levels of prior knowledge and obviate the double-hump phenomenon. Studying performance helps to improve delivery of introductory computer science courses by ensuring that courses are aligned with student needs and address preconceptions and prior knowledge and experience.

Keywords

computer science performance
coding
programming
double hump
grade distribution
bimodal distribution
unimodal distribution

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

https://doi.org/10.29333/ejmste/93190

EURASIA J Math Sci Tech Ed, 2018 - Volume 14 Issue 10, Article No: em1591

Publication date: 11 Jul 2018

Article Views: 1243

Article Downloads: 434

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How to cite this article

APA

Basnet, R. B., Payne, L. K., Doleck, T., Lemay, D. J., & Bazelais, P. (2018). Exploring Bimodality in Introductory Computer Science Performance Distributions. Eurasia Journal of Mathematics, Science and Technology Education, 14(10), em1591. https://doi.org/10.29333/ejmste/93190

Vancouver

Basnet RB, Payne LK, Doleck T, Lemay DJ, Bazelais P. Exploring Bimodality in Introductory Computer Science Performance Distributions. EURASIA J Math Sci Tech Ed. 2018;14(10):em1591. https://doi.org/10.29333/ejmste/93190

AMA

Basnet RB, Payne LK, Doleck T, Lemay DJ, Bazelais P. Exploring Bimodality in Introductory Computer Science Performance Distributions. EURASIA J Math Sci Tech Ed. 2018;14(10), em1591. https://doi.org/10.29333/ejmste/93190

Chicago

Basnet, Ram B, Lori K Payne, Tenzin Doleck, David John Lemay, and Paul Bazelais. "Exploring Bimodality in Introductory Computer Science Performance Distributions". Eurasia Journal of Mathematics, Science and Technology Education 2018 14 no. 10 (2018): em1591. https://doi.org/10.29333/ejmste/93190

Harvard

Basnet, R. B., Payne, L. K., Doleck, T., Lemay, D. J., and Bazelais, P. (2018). Exploring Bimodality in Introductory Computer Science Performance Distributions. Eurasia Journal of Mathematics, Science and Technology Education, 14(10), em1591. https://doi.org/10.29333/ejmste/93190

MLA

Basnet, Ram B et al. "Exploring Bimodality in Introductory Computer Science Performance Distributions". Eurasia Journal of Mathematics, Science and Technology Education, vol. 14, no. 10, 2018, em1591. https://doi.org/10.29333/ejmste/93190