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Surf or sleep?: Understanding the influence of bedtime patterns on campus

Published: 03 January 2022 Publication History

Abstract

Poor sleep habits may cause serious problems of mind and body, and it is a commonly observed issue for college students due to study workload as well as peer and social influence. Understanding its impact and identifying students with poor sleep habits matters a lot in educational management. Most of the current researches is either based on self-reports and questionnaires, suffering from small sample size and social desirability bias, or the methods used are not suitable for the education system. In this paper, we develop a general data-driven method for identifying students' sleep patterns according to their Internet access pattern stored in the education management system and explore its influence from various aspects. First, we design a Possion-based probabilistic mixture model to cluster students according to the distribution of bedtime and identify students who are used to stay up late. Second, we profile students from five aspects (including eight dimensions) based on campusbehavior data and build Bayesian networks to explore the relationship between behavioral characteristics and sleeping habits. Finally, we test the predictability of sleeping habits. This paper not only contributes to the understanding of student sleep from a cognitive and behavioral perspective but also presents a new approach that provides an effective framework for various educational institutions to detect the sleeping patterns of students.

References

[1]
R. Agrahari, A. Foroushani, T. R. Docking, L. Chang, G. Duns, M. Hudoba, A. Karsan, and H. Zare. Applications of bayesian network models in predicting types of hematological malignancies. Scientific reports, 8(1):6951, 2018.
[2]
W. Al-Salman, Y. Li, and P. Wen. Detecting sleep spindles in eegs using wavelet fourier analysis and statistical features. Biomedical Signal Processing and Control, 48:80--92, 2019.
[3]
Z. Alimoradi, C.-Y. Lin, A. Brostr´om, P. H. B´ulow, Z. Bajalan, M. D. Griffiths, M. M. Ohayon, and A. H. Pakpour. Internet addiction and sleep problems: A systematic review and meta-analysis. Sleep Medicine Reviews, 47:51--61, 2019.
[4]
T. Althoff, E. Horvitz, R. W. White, and J. Zeitzer. Harnessing the web for population-scale physiological sensing: A case study of sleep and performance. In WWW '17 Proceedings of the 26th International Conference on World Wide Web, pages 113--122, 2017.
[5]
K. Bartel, R. Scheeren, and M. Gradisar. Altering adolescents' pre-bedtime phone use to achieve better sleep health. Health Communication, 34(4):456--462, 2019.
[6]
M. B. Becerra, B. S. Bol, R. Granados, and C. Hassija. Sleepless in school: The role of social determinants of sleep health among college students. Journal of American College Health, (1):1--7, 2018.
[7]
H. D. Bedru, S. Yu, X. Xiao, D. Zhang, L.Wan, H. Guo, and F. Xia. Big networks: A survey. Computer Science Review, 37:100247, 2020.
[8]
B. Bjorvatn, J. Mrdalj, I. W. Saxvig, T. Aasnæs, S. Pallesen, and S. Waage. Age and sex differences in bedroom habits and bedroom preferences. Sleep medicine, 32:157--161, 2017.
[9]
F. C. Brown, W. C. Buboltz Jr, and B. Soper. Relationship of sleep hygiene awareness, sleep hygiene practices, and sleep quality in university students. Behavioral medicine, 28(1):33--38, 2002.
[10]
W. C. Buboltz Jr, F. Brown, and B. Soper. Sleep habits and patterns of college students: a preliminary study. Journal of American college health, 50(3):131-- 135, 2001.
[11]
C. Burr, J. Morley, M. Taddeo, and L. Floridi. Digital psychiatry: Risks and opportunities for public health and wellbeing. IEEE Transactions on Technology and Society, 1(1):21--33, 2020.
[12]
C.-F. Chien, S.-L. Chen, and Y.-S. Lin. Using bayesian network for fault location on distribution feeder. IEEE Transactions on Power Delivery, 17(3):785--793, 2002.
[13]
D. Combs, J. L. Goodwin, S. F. Quan, W. J. Morgan, S. Shetty, and S. Parthasarathy. Insomnia, healthrelated quality of life and health outcomes in children: a seven year longitudinal cohort. Scientific reports, 6:27921, 2016.
[14]
J. N. Cousins, K. Sasmita, and M. W. L. Chee. Memory encoding is impaired after multiple nights of partial sleep restriction. Journal of Sleep Research, 27(1):138-- 145, 2018.
[15]
J. N. Cousins, E. van Rijn, J. L. Ong, K. F. Wong, and M. W. L. Chee. Does splitting sleep improve long-term memory in chronically sleep deprived adolescents? npj Science of Learning, 4(1):8, 2019.
[16]
F. de Arriba P´erez, J. M. S. Gago, and M. C. Rodr ´?guez. Calculation of sleep indicators in students using smartphones and wearables. In New Advances in Information Systems and Technologies, pages 169--178. Springer, 2016.
[17]
A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39(1):1--22, 1977.
[18]
N. Ducheneaut, N. Yee, E. Nickell, and R. J. Moore. Alone together? exploring the social dynamics of massively multiplayer online games. In Proceedings of the SIGCHI conference on Human Factors in computing systems, pages 407--416, 2006. SIGKDD Explorations Volume 23, Issue 2 11
[19]
I. N. Fossum, L. T. Nordnes, S. S. Storemark, B. Bjorvatn, and S. Pallesen. The association between use of electronic media in bed before going to sleep and insomnia symptoms, daytime sleepiness, morningness, and chronotype. Behavioral sleep medicine, 12(5):343-- 357, 2014.
[20]
N. Friedman, D. Geiger, and M. Goldszmidt. Bayesian network classifiers. Machine learning, 29(2--3):131--163, 1997.
[21]
J. Grønli, I. K. Byrkjedal, B. Bjorvatn, Ø. Nødtvedt, B. Hamre, and S. Pallesen. Reading from an ipad or from a book in bed: the impact on human sleep. a randomized controlled crossover trial. Sleep medicine, 21:86--92, 2016.
[22]
D. Grossman and P. Domingos. Learning bayesian network classifiers by maximizing conditional likelihood. Twenty-first international conference on Machine learning - ICML '04, page 46, 01 2004.
[23]
T. Guo, F. Xia, S. Zhen, X. Bai, D. Zhang, Z. Liu, and J. Tang. Graduate employment prediction with bias. In Thirty-Second AAAI Conference on Artificial Intelligence. AAAI Press, 2020.
[24]
D. Heckerman, D. Geiger, and D. M. Chickering. Learning bayesian networks: The combination of knowledge and statistical data. Machine learning, 20(3):197--243, 1995.
[25]
F. V. Jensen et al. An introduction to Bayesian networks, volume 210. UCL press London, 1996.
[26]
M. D. Kaos, R. E. Rhodes, P. H¨am¨al¨ainen, and T. N. Graham. Social play in an exergame: how the need to belong predicts adherence. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pages 1--13, 2019.
[27]
P. Kelley, S. W. Lockley, R. G. Foster, and J. Kelley. Synchronizing education to adolescent biology:'let teens sleep, start school later'. Learning, Media and Technology, 40(2):210--226, 2015.
[28]
Y.-M. Liu, L. Wang, H.-C. Chu, and C. Yang. Development of a mobile sleep-management system for improving students' lifestyles based on a self-regulated learning strategy. In 2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), pages 623-- 628. IEEE, 2017.
[29]
J. C. Lo, J. L. Ong, R. L. Leong, J. J. Gooley, and M. W. Chee. Cognitive performance, sleepiness, and mood in partially sleep deprived adolescents: The need for sleep study. Sleep, 39(3):687--698, 2016.
[30]
M. J. McGeachie, H.-H. Chang, and S. T. Weiss. Cgbayesnets: Conditional gaussian bayesian network learning and inference with mixed discrete and continuous data. PLOS Computational Biology, 10(6):e1003676, 2014.
[31]
G. McLachlan and T. Krishnan. The EM algorithm and extensions, volume 382. John Wiley & Sons, 2007.
[32]
K. Okano, J. R. Kaczmarzyk, N. Dave, J. D. Gabrieli, and J. C. Grossman. Sleep quality, duration, and consistency are associated with better academic performance in college students. NPJ science of learning, 4(1):1--5, 2019.
[33]
K. M. Orzech, M. A. Grandner, B. M. Roane, and M. A. Carskadon. Digital media use in the 2 h before bedtime is associated with sleep variables in university students. Computers in human behavior, 55:43--50, 2016.
[34]
J. Park, R. Yu, F. Rodriguez, R. Baker, P. Smyth, and M. Warschauer. Understanding student procrastination via mixture models. International Educational Data Mining Society, 2018.
[35]
M. E. Patrick, J. Griffin, E. D. Huntley, and J. L. Maggs. Energy drinks and binge drinking predict college students sleep quantity, quality, and tiredness. Behavioral sleep medicine, 16(1):92--105, 2018.
[36]
D. Peters, K. Vold, D. Robinson, and R. A. Calvo. Responsible ai-two frameworks for ethical design practice. IEEE Transactions on Technology and Society, 1(1):34-- 47, 2020.
[37]
A. C. Schneider, D. Zhang, and Q. Xiao. Adolescent sleep characteristics and body-mass index in the family life, activity, sun, health, and eating (flashe) study. Scientific Reports, 10(1):1--10, 2020.
[38]
E. B. Simon and M. P. Walker. Sleep loss causes social withdrawal and loneliness. Nature communications, 9(1):1--9, 2018.
[39]
P. Spirtes, C. Glymour, and R. Scheines. Causation, prediction, and search. 1993.
[40]
R. Tavernier and T. Willoughby. Sleep problems: predictor or outcome of media use among emerging adults at university? Journal of Sleep Research, 23(4):389-- 396, 2014.
[41]
R. Tavernier and T. Willoughby. A longitudinal examination of the bidirectional association between sleep problems and social ties at university: The mediating role of emotion regulation. Journal of youth and adolescence, 44(2):317--330, 2015.
[42]
L.-L. Tsai and S.-P. Li. Sleep patterns in college students: Gender and grade differences. Journal of psychosomatic research, 56(2):231--237, 2004.
[43]
J. Vroon, C. Zaga, D. Davison, J. Kolkmeier, and J. Linssen. Snoozle--a robotic pillow that helps you go to sleep: Hri 2017 student design competition. In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, pages 399--400. ACM, 2017.
[44]
H. Zhao, W. Gui, H. Huang, Y. Liu, H. Ding, W. Fan, S. Huang,W. Yang, X.Wang, and G. Chen. Association of long-term sleep habits and hypertension: a crosssectional study in chinese adults. Journal of Human Hypertension, pages 1--10, 2019.
[45]
X. Zhao, J. Li, W. Liu, J. Zhang, and Y. Li. Design of the sleeping aid system based on face recognition. Ad Hoc Networks, 99:102070, 2020.

Cited By

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  • (2023)Knowledge Discovery in Ubiquitous and Personal Sleep Tracking: Scoping ReviewJMIR mHealth and uHealth10.2196/4275011(e42750)Online publication date: 28-Jun-2023

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Published In

cover image ACM SIGKDD Explorations Newsletter
ACM SIGKDD Explorations Newsletter  Volume 23, Issue 2
December 2021
22 pages
ISSN:1931-0145
EISSN:1931-0153
DOI:10.1145/3510374
Issue’s Table of Contents
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Publication History

Published: 03 January 2022
Published in SIGKDD Volume 23, Issue 2

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  • (2023)Knowledge Discovery in Ubiquitous and Personal Sleep Tracking: Scoping ReviewJMIR mHealth and uHealth10.2196/4275011(e42750)Online publication date: 28-Jun-2023

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