Modeling Programming Competency: A Qualitative Analysis
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An examination of course syllabi showed that reading and tracing code is often an afterthought in computing courses.
“Although the ability to both read and trace code has always been important [19,128], an examination of course syllabi showed that this is often an afterthought [37,112,114].”
From The Robots Are Here: Navigating the Generative AI Revolution in Computing Education (2023) · cites this paper as [114]
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The Robots Are Here: Navigating the Generative AI Revolution in Computing Education
Prather, J., Denny, P., Leinonen, J., Becker, B. A., Albluwi, I., Craig, M., Keuning, H., Kiesler, N., Kohn, T., Luxton-Reilly, A., et al. (2023) · Proceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education · doi:10.1145/3623762.3633499 · Cited by 396 · see citing works
Self-citationLohr, D., Keuning, H., & Kiesler, N. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.13107 · Cited by 33 · see citing works
Self-citationScholl, A., & Kiesler, N. (2024) · 2024 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10893442 · Cited by 35 · see citing works
“Even though it is challenging to predict which programming competencies [4] students will require in the future and how to adapt curricula respectively [5], [6], computing educators need to gain an understanding of how students currently apply GenAI tools.”
Self-citationGao, Z., Yan, H., Huang, Y., Zhang, X., Saqr, M., Sun, X., & Feng, J. H. (2026) · Smart Learning Environments · doi:10.1186/s40561-026-00431-7 · Cited by 5 · see citing works
“Dispositions, in turn, capture the manner in which students approach tasks, including when and how they choose to participate (Kiesler, 2024).”
Software Engineering Competency Challenges
de Souza, A. D., de Oliveira, J. D., Paiva, S. L. D. C., & de Vasconcelos, A. M. L. (2024) · Anais do IX Workshop sobre Aspectos Sociais, Humanos e Econômicos de Software (WASHES 2024) · doi:10.5753/washes.2024.3043 · Cited by 3 · see citing works
“For instance, the American competency approach focuses on individual capabilities, while the European approach includes social and methodological issues and emphasizes the application of competencies in various contexts [Kiesler 2024].”
BackgroundStudent Engagement with GenAI's Tutoring Feedback: A Mixed Methods Study
Jacobs, S., Haas, J., & Kiesler, N. (2025) · Koli Calling International Conference on Computing Education Research · doi:10.1145/3769994.3770034 · Cited by 6 · see citing works
“This is particularly relevant in computing education in Germany, where students are increasingly heterogeneous in terms of their prior education, competencies, programming experience, and feedback needs [23].”
Self-citationMODELING OF INFORMATION TECHNOLOGY FOR THE FORMATION OF COMPETENCIES OF STUDENTS
Kryvoruchko, O., & Zakharov, R. (2024) · Cybersecurity Education Science Technique · doi:10.28925/2663-4023.2024.24.196204
- Authors
- Kiesler, N.
- Affiliations
- DIPF | Leibniz Institute for Research and Information in Education (DE)
- Corresponding author
- Kiesler, Natalie
- ORCID
- Kiesler, Natalie
- Venue
- Springer eBooks
- Publisher
- Springer International Publishing
- Published
- 2024
- OpenAlex
- W4390292222
- Cited by
- 7
- References
- 0
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 1
- FWCI
- 6.12
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer eBooks (publishedVersion)
- OHMdok (Technische Hochschule Nürnberg) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Engineering › Media Technology › Engineering Education and Curriculum Development
- Social Sciences › Education › Higher Education Teaching and Evaluation
- Keywords
- programming skills, programming education, competency modeling, software engineering 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.
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