The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Failure rates in introductory programming
Abstract
It is a common conception that CS1 is a very difficult course and that failure rates are high. However, until now there has only been anecdotal evidence for this claim. This article reports on a survey among institutions around the world regarding failure rates in introductory programming courses. The article describes the design of the survey and the results. The number of institutions answering the call for data was unfortunately rather low, so it is difficult to make firm conclusions. It is our hope that this article can be the starting point for a systematic collection of data in order to find solid proof of the actual failure and pass rates of CS1.
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Citations
Cites
Learning and Teaching Programming: A Review and Discussion
Robins, A., Rountree, J., & Rountree, N. (2003) · Computer Science Education · doi:10.1076/csed.13.2.137.14200 · Cited by 1,736
Cited by
Failure rates in introductory programming revisited
Watson, C., & Li, F. W. B. (2014) · Proceedings of the 2014 conference on Innovation & technology in computer science education - ITiCSE '14 · doi:10.1145/2591708.2591749 · Cited by 639
A systematic literature review of automated feedback generation for programming exercises
Keuning, H., Jeuring, J., & Heeren, B. (2019) · ACM Transactions on Computing Education · doi:10.1145/3231711 · Cited by 370
Increased Course Structure Improves Performance in Introductory Biology
Freeman, S., Haak, D., & Wenderoth, M. P. (2011) · CBE—Life Sciences Education · doi:10.1187/cbe.10-08-0105 · Cited by 306
Programming, Problem Solving, and Self-Awareness: Effects of Explicit Guidance
Loksa, D., Ko, A. J., Jernigan, W., Oleson, A., Mendez, C. J., & Burnett, M. M. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858252 · Cited by 223
Solving parsons problems versus fixing and writing code
Ericson, B. J., Margulieux, L. E., & Rick, J. (2017) · Proceedings of the 17th Koli Calling International Conference on Computing Education Research · doi:10.1145/3141880.3141895 · Cited by 121
Metadata
- Authors
- Bennedsen, J., & Caspersen, M. E.
- Venue
- ACM SIGCSE Bulletin
- Published
- 2007-06
- Volume
- 39
- Issue
- 2
- Pages
- 32-36
- ISSN
- 0097-8418 (ISSN-L)
- OpenAlex
- W2067963826
- Cited by
- 627
- References
- 1
- FWCI
- 18.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bennedsen, J., & Caspersen, M. E. (2007). Failure rates in introductory programming. ACM SIGCSE Bulletin. https://doi.org/10.1145/1272848.1272879
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
