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Student Performance in Computing Courses in the face of Growing Enrollments

Published: 22 February 2019 Publication History

Abstract

As computing enrollments have grown in the last decade there have been anecdotal claims from faculty that the discipline has attracted weaker students. To the best of our knowledge the only paper that has studied, and debunked, this claim has been based on data from an exclusive North American university. In this paper we examine data from six courses drawn taught over a 3 year period at a public university in a developing country. We find that in the case of the CS1 course, the distribution of student grades has fluctuated over this period. In addition, courses in object-oriented programming, networking, algorithms and discrete mathematics have also shown variation in student grades. We provide discussion as to why the grades in the courses show variation. We also explain why our findings differ from previous claims of stability in student grades.

References

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Computing Research Association. 2017. Generation CS: Computer Science Undergraduate Enrollments Surge Since 2006. Technical Report. http://cra.org/data/Generation-CS/
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B. S. Everitt. 2006. Mixture Distributions-I . Encyclopedia of Statistical Sciences . John Wiley & Sons, Inc., Hoboken, NJ, USA.
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D. Koller, A. Ng, C. Do, and Z. Chen. 2013. Retention and Intention in Massive Open Online Courses . EDUCAUSE Review, Vol. 48, 3 (2013), 62--63.
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E. Patitsas, J. Berlin, M. Craig, and S. Easterbrook. 2016. Evidence That Computer Science Grades Are Not Bimodal. In Proceedings of the 2016 ACM Conference on International Computing Education Research - ICER '16 . ACM Press, New York, New York, USA, 113--121.
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R Core Team. 2014. R: A Language and Environment for Statistical Computing . (2014). http://www.R-project.org
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M. Sahami and C. Piech. 2016. As CS Enrollments Grow, Are We Attracting Weaker Students?. In Proc. 47th ACM Technical Symposium on Computing Science Education (SIGCSE '16). ACM, New York, NY, USA, 54--59.

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  • (2024)Quickly Producing "Isomorphic" Exercises: Quantifying the Impact of Programming Question PermutationsProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653617(178-184)Online publication date: 3-Jul-2024

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cover image ACM Conferences
SIGCSE '19: Proceedings of the 50th ACM Technical Symposium on Computer Science Education
February 2019
1364 pages
ISBN:9781450358903
DOI:10.1145/3287324
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 February 2019

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Author Tags

  1. algorithms
  2. enrollment growth
  3. introductory programming
  4. mixture modeling
  5. student performance

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SIGCSE '19 Paper Acceptance Rate 169 of 526 submissions, 32%;
Overall Acceptance Rate 1,595 of 4,542 submissions, 35%

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The 56th ACM Technical Symposium on Computer Science Education
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  • (2024)Quickly Producing "Isomorphic" Exercises: Quantifying the Impact of Programming Question PermutationsProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653617(178-184)Online publication date: 3-Jul-2024

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