Morning or Evening? An Examination of Circadian Rhythms of CS1 Students
Open accessAbstract
Circadian rhythms are the cycles of our internal clock that play a key role in governing when we sleep and when we are active. A related concept is chronotype, which is a person's natural tendency toward activity at certain times of day and typically governs when the individual is most alert and productive. In this work we investigate chronotypes in the setting of an Introductory Computer Programming (CS1) course. Using keystroke data collected from students we investigate the existence of chronotypes through unsupervised learning. The chronotypes we find align with those of typical populations reported in the literature and our results support correlations of certain chronotypes to academic achievement. We also find a lack of support for the still-popular stereotype of a computer programmer as a night owl. The analyses are conducted on data from two universities, one in the US and one in Europe, that use different teaching methods. In comparison of the two contexts, we look into programming assignment design and administration that may promote better programming practices among students in terms of procrastination and effort.
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Some work has used fine-grained programming process logs from instrumented IDEs to uncover student work patterns and to visualize student programming processes.
“Some work has looked into using fine-grained programming process logs gathered from instrumented IDEs to uncover student work patterns [21-23, 26, 40] and to visualize student programming processes [10,14,35,38].”
From Instructor Perceptions of AI Code Generation Tools - A Multi-Institutional Interview Study (2024) · cites this paper as [40]
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The ASA Statement on <i>p</i> -Values: Context, Process, and Purpose
Wasserstein, R. L., & Lazar, N. A. (2016) · The American Statistician · doi:10.1080/00031305.2016.1154108 · Cited by 6,306 · cited 1× · see citing works
“We report p-values of our statistical tests as one component among others that together contribute to understanding of our results [43].”
Coordination of circadian timing in mammals
Reppert, S. M., & Weaver, D. R. (2002) · Nature · doi:10.1038/nature00965 · Cited by 4,379 · see citing works
(1991) · Cited by 3,259 · see citing works
Life between Clocks: Daily Temporal Patterns of Human Chronotypes
Roenneberg, T., Wirz-Justice, A., & Merrow, M. (2003) · Journal of Biological Rhythms · doi:10.1177/0748730402239679 · Cited by 2,662 · see citing works
Social Jetlag: Misalignment of Biological and Social Time
Wittmann, M., Dinich, J., Merrow, M., & Roenneberg, T. (2006) · Chronobiology International · doi:10.1080/07420520500545979 · Cited by 2,625 · see citing works
Dibner, C., Schibler, U., & Albrecht, U. (2010) · Annual Review of Physiology · doi:10.1146/annurev-physiol-021909-135821 · Cited by 2,421 · see citing works
Circadian rhythms from multiple oscillators: lessons from diverse organisms
Bell‐Pedersen, D., Cassone, V. M., Earnest, D. J., Golden, S. S., Hardin, P. E., Thomas, T. L., & Zoran, M. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1633 · Cited by 1,481 · see citing works
A time to think: circadian rhythms in human cognition
Schmidt, C., Collette, F., Cajochen, C., & Peigneux, P. (2007) · Cognitive Neuropsychology · doi:10.1080/02643290701754158 · Cited by 778 · see citing works
Inhibitory Mechanisms and the Control of Attention
Hasher, L., Lustig, C., & Zacks, R. T. (2008) · doi:10.1093/acprof:oso/9780195168648.003.0009 · Cited by 553 · see citing works
Cajochen, C., Khalsa, S. B. S., Wyatt, J. K., Czeisler, C. A., & Dijk, D.-J. (1999) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.1999.277.3.r640 · Cited by 349 · see citing works
Vitale, J. A., Roveda, E., Montaruli, A., Galasso, L., Weydahl, A., Caumo, A., & Carandente, F. (2014) · Chronobiology International · doi:10.3109/07420528.2014.986273 · Cited by 326 · see citing works
The Case Against Statistical Significance Testing, Revisited
Carver, R. P. (1993) · The Journal of Experimental Education · doi:10.1080/00220973.1993.10806591 · Cited by 319 · see citing works
Chronotype, cognitive abilities, and academic achievement: A meta-analytic investigation
Preckel, F., Lipnevich, A. A., Schneider, S., & Roberts, R. D. (2011) · Learning and Individual Differences · doi:10.1016/j.lindif.2011.07.003 · Cited by 275 · see citing works
Auvinen, T., Hakulinen, L., & Malmi, L. (2015) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2015.2441718 · Cited by 169 · see citing works
Margulieux, L. E., Guzdial, M., & Catrambone, R. (2012) · Proceedings of the ninth annual international conference on International computing education research · doi:10.1145/2361276.2361291 · Cited by 149 · see citing works
The influence of motivation and comfort-level on learning to program
Bergin, S., & Reilly, R. B. (2005) · Maynooth University ePrints and eTheses Archive (Maynooth University) · Cited by 144 · see citing works
What Do We Think We Think We Are Doing?
Prather, J. E., Becker, B. A., Craig, M., Denny, P. C., Loksa, D., & Margulieux, L. E. (2020) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3372782.3406263 · Cited by 137 · see citing works
Comparing effective and ineffective behaviors of student programmers
Edwards, S. H., Snyder, J., Pérez-Quiñones, M. A., Allevato, A., Kim, D., & Tretola, B. (2009) · doi:10.1145/1584322.1584325 · Cited by 117 · see citing works
Learning Styles: Quiet Revolution in American Secondary Schools
Dunn, R., & Griggs, S. A. (1989) · The Clearing House A Journal of Educational Strategies Issues and Ideas · doi:10.1080/00098655.1989.9955719 · Cited by 103 · see citing works
Automatic Inference of Programming Performance and Experience from Typing Patterns
Leinonen, J., Longi, K., Klami, A., & Vihavainen, A. (2016) · Proceedings of the 47th ACM Technical Symposium on Computing Science Education · doi:10.1145/2839509.2844612 · Cited by 103 · see citing works
Self-citationValdéz, P., Reilly, T. P., & Waterhouse, J. M. (2008) · Mind Brain and Education · doi:10.1111/j.1751-228x.2008.00023.x · Cited by 99 · see citing works
Cognitive efficiency and circadian typologies: a diurnal study
Natale, V., Alzani, A., & Cicogna, P. (2003) · Personality and Individual Differences · doi:10.1016/s0191-8869(02)00320-3 · Cited by 98 · see citing works
Influence of chronotype and social zeitgebers on sleep/wake patterns
Korczak, A., Martynhak, B. J., Pedrazzoli, M., Brito, A. F., & Louzada, F. M. (2008) · Brazilian Journal of Medical and Biological Research · doi:10.1590/s0100-879x2008005000047 · Cited by 87 · see citing works
Analyzing Student Work Patterns Using Programming Exercise Data
Spacco, J. W., Denny, P. C., Richards, B., Babcock, D., Hovemeyer, D., Moscola, J., & Duvall, R. C. (2015) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/2676723.2677297 · Cited by 75 · see citing works
Validation of a Chronotype Questionnaire Including an Amplitude Dimension
Dosseville, F. E. M., Laborde, S., & Lericollais, R. (2013) · Chronobiology International · doi:10.3109/07420528.2012.763042 · Cited by 70 · see citing works
Chronotype and environmental light exposure in a student population
Porcheret, K., Lucien Wald, A., Fritschi, L., Gerkema, M. P., Gordijn, M. C. M., Merrrow, M., Rajaratnam, S. M. W., Rock, D. J., Sletten, T. L., Warman, G. R., et al. (2018) · Chronobiology International · doi:10.1080/07420528.2018.1482556 · Cited by 60 · see citing works
Nowack, K., & van der Meer, E. E. (2018) · Chronobiology International · doi:10.1080/07420528.2018.1500477 · Cited by 56 · see citing works
Effect of chronotype on academic achievement in a sample of Italian University students
Montaruli, A., Castelli, L., Galasso, L., Mulè, A., Bruno, E., Esposito, F., Caumo, A., & Roveda, E. (2019) · Chronobiology International · doi:10.1080/07420528.2019.1652831 · Cited by 54 · see citing works
Influences of morningness-eveningness and time of day on narrative comprehension
Natale, V., & Lorenzetti, R. (1997) · Personality and Individual Differences · doi:10.1016/s0191-8869(97)00059-7 · Cited by 52 · see citing works
Plagiarism in Take-home Exams: Help-seeking, Collaboration, and Systematic Cheating
Hellas, A., Leinonen, J., & Ihantola, P. (2017) · Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education · doi:10.1145/3059009.3059065 · Cited by 50 · see citing works
Self-citationThe Effects of Procrastination Interventions on Programming Project Success
Martin, J., Edwards, S. H., & Shaffer, C. A. (2015) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/2787622.2787730 · Cited by 47 · see citing works
Supporting Self-Regulated Learning with Visualizations in Online Learning Environments
Ilves, K., Leinonen, J., & Hellas, A. (2018) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3159450.3159509 · Cited by 47 · see citing works
Self-citationIdentification of programmers from typing patterns
Longi, K., Leinonen, J., Nygren, H., Salmi, J., Arto Klami, A., & Vihavainen, A. (2015) · Koli Calling International Conference on Computing Education Research · doi:10.1145/2828959.2828960 · Cited by 44 · see citing works
Self-citationKolomeichuk, S. N., Randler, C., Shabalina, I., Fradkova, L., & Borisenkov, M. F. (2016) · Biological Rhythm Research · doi:10.1080/09291016.2016.1207352 · Cited by 44 · see citing works
Comparison of Time Metrics in Programming
Leinonen, J., Leppänen, L., Ihantola, P., & Hellas, A. (2017) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3105726.3106181 · Cited by 41 · see citing works
Self-citationResearch on instructional environments: Implications for student achievement and attitudes.
Dunn, R. (1987) · Professional School Psychology · doi:10.1037/h0090528 · Cited by 36 · see citing works
Do programmers work at night or during the weekend?
Claes, M., Mäntylä, M. V., Kuutila, M., & Adams, B. (2018) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/3180155.3180193 · Cited by 33 · see citing works
Need for Sleep: The Impact of a Night of Sleep Deprivation on Novice Developers’ Performance
Fucci, D., Scanniello, G., Romano, S., & Juristo, N. (2018) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2018.2834900 · Cited by 31 · see citing works
Valladares, M., Ramírez‐Tagle, R., Muñoz, M. A., & Obregón, A. M. (2017) · Chronobiology International · doi:10.1080/07420528.2017.1413385 · Cited by 27 · see citing works
Putilov, A. A., Marcoen, N., Neu, D., Pattyn, N., & Maîresse, O. (2019) · Personality and Individual Differences · doi:10.1016/j.paid.2019.05.017 · Cited by 26 · see citing works
A Study of Keystroke Data in Two Contexts
Edwards, J., Leinonen, J., & Hellas, A. (2020) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3328778.3366863 · Cited by 24 · see citing works
Self-citationImproving complex task performance using a sequence of simple practice tasks
Denny, P. C., Luxton-Reilly, A., Craig, M., & Petersen, A. (2018) · ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) · doi:10.1145/3197091.3197141 · Cited by 21 · see citing works
Typing Patterns and Authentication in Practical Programming Exams
Leinonen, J., Longi, K., Arto Klami, A., Ahadi, A., & Vihavainen, A. (2016) · ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) · doi:10.1145/2899415.2899472 · Cited by 19 · see citing works
Self-citationPauses and spacing in learning to program
Leppänen, L., Leinonen, J., & Hellas, A. (2016) · Koli Calling International Conference on Computing Education Research · doi:10.1145/2999541.2999549 · Cited by 18 · see citing works
Self-citationKeystroke Data in Programming Courses
Leinonen, J. (2019) · Työväentutkimus Vuosikirja · Cited by 8 · see citing works
Self-citation
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Bridson, K., Atkinson, J., & Fleming, S. D. (2022) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3478431.3499385 · Cited by 19 · see citing works
Methodological Considerations for Predicting At-risk Students
Koutcheme, C., Sarsa, S., Hellas, A., Haaranen, L., & Leinonen, J. (2022) · Australasian Computing Education Conference · doi:10.1145/3511861.3511873 · Cited by 14 · see citing works
Self-citationCodeProcess Charts: Visualizing the Process of Writing Code
Shrestha, R., Leinonen, J., Hellas, A., Ihantola, P., & Edwards, J. (2022) · Proceedings of the 24th Australasian Computing Education Conference · doi:10.1145/3511861.3511867 · Cited by 13 · see citing works
Self-citationLatino, F., Tafuri, F., Maisuradze, M., & Tafuri, M. G. (2025) · Children · doi:10.3390/children12101324 · Cited by 11 · see citing works
Experiences With and Lessons Learned on Deadlines and Submission Behavior
Castro, F. E. V., Leinonen, J., & Hellas, A. (2022) · Koli Calling International Conference on Computing Education Research · doi:10.1145/3564721.3564728 · Cited by 10 · see citing works
Self-citationSleep Preferences and Chronotype Traits Impact on Academic Performance Among University Students
Figueiredo, S., & Kulari, G. (2024) · European Journal of Educational Research · doi:10.12973/eu-jer.13.3.895 · Cited by 11 · see citing works
Identifying Different Student Clusters in Functional Programming Assignments
Geng, C., Xu, W., Xu, Y., Pientka, B., & Si, X. (2023) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3545945.3569882 · Cited by 7 · see citing works
TGIF: the evolution of developer commit times
Karyotakis, I., Talos, E., & Spinellis, D. D. (2025) · Empirical Software Engineering · doi:10.1007/s10664-025-10767-2 · Cited by 1 · see citing works
Ebeling, U., de Leeuw, R. A., Georgiadis, J. R., Scheele, F., & Wietasch, G. J. K. G. (2024) · Teaching and Learning in Medicine · doi:10.1080/10401334.2024.2331649 · Cited by 3 · see citing works
Bhattarai, S., & Edwards, J. (2025) · Intermountain Engineering, Technology and Computing (IETC) · doi:10.1109/ietc64455.2025.11039464
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- Authors
- Zavgorodniaia, A., Shrestha, R., Leinonen, J., Hellas, A., & Edwards, J.
- Affiliations
- Aalto University (FI)
- Utah State University (US)
- University of Helsinki (FI)
- Venue
- 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)
- Publisher
- IEEE
- Published
- 2021-05
- Pages
- 261-272
- OpenAlex
- W3133616997
- Cited by
- 13
- References
- 46
- Citations by year
- 2025: 3 · 2024: 5 · 2023: 1 · 2022: 4
- FWCI
- 2.91
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Työväentutkimus Vuosikirja (submittedVersion, other-oa)
- arXiv (Cornell University)
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
- Keywords
- circadian rhythm, chronotype, CS1 course, introductory programming, keystroke data, academic performance, procrastination, student effort, unsupervised learning
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