Behaviors of Higher and Lower Performing Students in CS1
Open accessAbstract
Although recent work in computing has discovered multiple techniques to identify low-performing students in a course, it is unclear what factors contribute to those students' difficulties. If we were able to better understand the characteristics of such students, we may be better able to help those students. This work examines the characteristics of low- and high-performing students through interviews with students from an introductory computing class. We identify a number of relevant areas of student behavior including how they approach their exam studies, how they approach completing programming assignments, whether they sought help after identifying misunderstandings, how and from whom they sought help, and how they reflected on assignments after submitting them. Particular behaviors within each area are coded and differences between groups of students are identified.
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Academic procrastination negatively impacts students' academic performance, well-being, and learning abilities.
“This issue negatively impacts students' academic performance, well-being, and learning abilities [25,26,34,39].”
From ClearMind Workshop: An ACT-based Intervention Tailored for Academic Procrastination among Computing Students (2024) · cites this paper as [26]
Section 5.2 reports that procrastination can amplify poor study practices, cites prior literature linking it to lower programming-assignment grades, and describes a student who could not get help understanding concepts after starting late. Section 4.2.1 also notes that some high-performing students started late and completed their assignments successfully. The paper does not establish an effect on well-being or a general reduction in learning abilities; page numbers are unavailable in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredProcrastination exacerbates lower-performing computing students' learning as they cannot secure enough time to ask for help.
“Some prior research on computing students also mentioned procrastination exacerbates lower-performing students' learning as they cannot secure enough time to ask for help [25,26].”
From ClearMind Workshop: An ACT-based Intervention Tailored for Academic Procrastination among Computing Students (2024) · cites this paper as [26]
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- Authors
- Liao, S. N., Valstar, S., Thai, K., Alvarado, C., Zingaro, D., Griswold, W. G., & Porter, L.
- Affiliations
- University of California San Diego (US)
- University of Toronto (CA)
- Venue
- Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education
- Publisher
- ACM
- Published
- 2019-07-02
- Pages
- 196-202
- OpenAlex
- W2963800060
- Cited by
- 44
- References
- 37
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 7 · 2023: 7 · 2022: 11 · 2021: 8 · 2020: 6
- FWCI
- 7.23
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) (publishedVersion)
- Funders
- National Science Foundation (1712508)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Education › Problem and Project Based Learning
- Keywords
- introductory computing, CS1, student performance, underachieving students, student behavior, programming exercises, help-seeking, student characteristics
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