Assessing the assessment of programming ability
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Many areas of computing are poorly-suited to the proctored exam format.
“Unfortunately, many areas of computing are poorly-suited to this exam format; for example, an understanding of programming is best examined through practical activities on a computer [13].”
From Bob or Bot: Exploring ChatGPT's Answers to University Computer Science Assessment (2024) · cites this paper as [13]
An understanding of programming is best examined through practical activities on a computer.
“Unfortunately, many areas of computing are poorly-suited to this exam format; for example, an understanding of programming is best examined through practical activities on a computer [13].”
From Bob or Bot: Exploring ChatGPT's Answers to University Computer Science Assessment (2024) · cites this paper as [13]
Cites
McCracken, M., Almstrum, V. L., Diaz, D., Guzdial, M., Hagan, D., Kolikant, Y. B., Laxer, C., Thomas, L., Utting, I., & Wilusz, T. (2001) · ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) · doi:10.1145/572133.572137 · Cited by 628 · see citing works
Effectiveness of online assessment
Woit, D. M., & Mason, D. (2003) · ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/611892.611952 · Cited by 58 · see citing works
RoboProf and an introductory computer programming course
Daly, C. (1999) · doi:10.1145/305786.305904 · Cited by 52 · see citing works
Self-citationEvaluating programming ability in an introductory computer science course
Chamillard, A. T., & Braun, K. A. (2000) · doi:10.1145/330908.331857 · Cited by 35 · see citing works
Califf, M. E., & Goodwin, M. (2002) · ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/563340.563425 · Cited by 32 · see citing works
Using lab practica to evaluate programming ability
Chamillard, A. T., & Joiner, J. K. (2001) · doi:10.1145/364447.364572 · Cited by 23 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Synthesis and analysis of automatic assessment methods in CS1: generating intelligent MCQs
Traynor, D., & Gibson, J. P. (2005) · ACM SIGCSE Bulletin · doi:10.1145/1047124.1047502 · Cited by 21 · see citing works
- Authors
- Daly, C., & Waldron, J.
- Affiliations
- Dublin City University (IE)
- Trinity College Dublin (IE)
- Venue
- Proceedings of the 35th SIGCSE technical symposium on Computer science education
- Publisher
- ACM
- Published
- 2004-03
- Pages
- 210-213
- OpenAlex
- W4232897417
- Cited by
- 38
- References
- 6
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 2 · 2022: 3 · 2021: 1 · 2020: 2 · 2019: 2 · 2018: 2 · 2017: 2 · 2016: 1 · 2014: 1 · 2012: 1
- FWCI
- 3.21
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Technical Symposium on Computer Science Education (SIGCSE) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Social Sciences › Education › Educational Assessment and Pedagogy
- Social Sciences › Education › Problem and Project Based Learning
- Keywords
- programming education, computer science education
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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