Further evidence of a relationship between explaining, tracing and writing skills in introductory programming
Open accessAbstract
This paper reports on a replication of earlier studies into a possible hierarchy of programming skills. In this study, the students from whom data was collected were at a university that had not provided data for earlier studies. Also, the students were taught the programming language Python, which had not been used in earlier studies. Thus this study serves as a test of whether the findings in the earlier studies were specific to certain institutions, student cohorts, and programming languages. Also, we used a non–parametric approach to the analysis, rather than the linear approach of earlier studies. Our results are consistent with the earlier studies. We found that students who cannot trace code usually cannot explain code, and also that students who tend to perform reasonably well at code writing tasks have also usually acquired the ability to both trace code and explain code.
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Prior work in introductory programming has shown that code-reading and tracing skills are essential to problem-solving activities including code-writing.
“Prior work in introductory programming has shown that code-reading and tracing skills are essential to problem-solving activities including code-writing [49,55,57].”
From Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming (2023) · cites this paper as [55]
Cites
Relationships between reading, tracing and writing skills in introductory programming
Lopez, M., Whalley, J., Robbins, P., & Lister, R. (2008) · Proceedings of the Fourth international Workshop on Computing Education Research · doi:10.1145/1404520.1404531 · Cited by 363 · see citing works
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Students’ Misconceptions and Other Difficulties in Introductory Programming: A Literature Review
Qian, Y., & Lehman, J. (2018) · ACM Transactions on Computing Education · doi:10.1145/3077618 · Cited by 529 · see citing works
Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming
Kazemitabaar, M., Chow, J., Ma, C. K. T., Ericson, B. J., Weintrop, D., & Grossman, T. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580919 · Cited by 366 · see citing works
“Prior work in introductory programming has shown that code-reading and tracing skills are essential to problem-solving activities including code-writing [48, 54, 55].”
BackgroundPrather, J., Reeves, B. N., Denny, P., Leinonen, J., MacNeil, S., Luxton-Reilly, A., Orvalho, J., Alipour, A., Alfageeh, A., Amarouche, T., et al. (2024) · arXiv · doi:10.48550/arxiv.2412.12800 · Cited by 20 · see citing works
The Role of Working Memory in Program Tracing
Crichton, W., Agrawala, M., & Hanrahan, P. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445257 · Cited by 13 · see citing works
- Authors
- Lister, R., Fidge, C., & Teague, D.
- Affiliations
- University of Technology Sydney (AU)
- Queensland University of Technology (AU)
- Venue
- Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education
- Publisher
- ACM
- Published
- 2009-07-06
- Pages
- 161-165
- OpenAlex
- W2071792242
- Cited by
- 118
- References
- 1
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 4 · 2023: 9 · 2022: 4 · 2021: 9 · 2020: 11 · 2019: 12 · 2018: 13 · 2017: 7 · 2016: 4 · 2015: 5 · 2014: 7 · 2013: 5 · 2012: 6
- FWCI
- 5.87
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, programming, and type systems
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Keywords
- programming skills, code tracing, code explanation, writing software, skill hierarchy, introductory programming, Python, replication study, non-parametric analysis
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