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Article: Orderliness predicts academic performance: Behavioural analysis on campus lifestyle

TitleOrderliness predicts academic performance: Behavioural analysis on campus lifestyle
Authors
Keywordsacademic performance
campus behaviour
computational social science
data science
human behaviour
orderliness
Issue Date2018
Citation
Journal of the Royal Society Interface, 2018, v. 15, n. 146, article no. 0210 How to Cite?
AbstractQuantitative understanding of relationships between students' behavioural patterns and academic performances is a significant step towards personalized education. In contrast to previous studies that were mainly based on questionnaire surveys, recent literature suggests that unobtrusive digital data bring us unprecedented opportunities to study students' lifestyles in the campus. In this paper, we collect behavioural records from undergraduate students' (N = 18 960) smart cards and propose two high-level behavioural characters, orderliness and diligence. The former is a novel entropy-based metric that measures the regularity of campus daily life, which is estimated here based on temporal records of taking showers and having meals. Empirical analyses on such large-scale unobtrusive behavioural data demonstrate that academic performance (GPA) is significantly correlated with orderliness. Furthermore, we show that orderliness is an important feature to predict academic performance, which improves the prediction accuracy even in the presence of students' diligence. Based on these analyses, education administrators could quantitatively understand the major factors leading to excellent or poor performance, detect undesirable abnormal behaviours in time and thus implement effective interventions to better guide students' campus lives at an early stage when necessary.
Persistent Identifierhttp://hdl.handle.net/10722/346683
ISSN
2023 Impact Factor: 3.7
2023 SCImago Journal Rankings: 1.101

 

DC FieldValueLanguage
dc.contributor.authorCao, Yi-
dc.contributor.authorGao, Jian-
dc.contributor.authorLian, Defu-
dc.contributor.authorRong, Zhihai-
dc.contributor.authorShi, Jiatu-
dc.contributor.authorWang, Qing-
dc.contributor.authorWu, Yifan-
dc.contributor.authorYao, Huaxiu-
dc.contributor.authorZhou, Tao-
dc.date.accessioned2024-09-17T04:12:34Z-
dc.date.available2024-09-17T04:12:34Z-
dc.date.issued2018-
dc.identifier.citationJournal of the Royal Society Interface, 2018, v. 15, n. 146, article no. 0210-
dc.identifier.issn1742-5689-
dc.identifier.urihttp://hdl.handle.net/10722/346683-
dc.description.abstractQuantitative understanding of relationships between students' behavioural patterns and academic performances is a significant step towards personalized education. In contrast to previous studies that were mainly based on questionnaire surveys, recent literature suggests that unobtrusive digital data bring us unprecedented opportunities to study students' lifestyles in the campus. In this paper, we collect behavioural records from undergraduate students' (N = 18 960) smart cards and propose two high-level behavioural characters, orderliness and diligence. The former is a novel entropy-based metric that measures the regularity of campus daily life, which is estimated here based on temporal records of taking showers and having meals. Empirical analyses on such large-scale unobtrusive behavioural data demonstrate that academic performance (GPA) is significantly correlated with orderliness. Furthermore, we show that orderliness is an important feature to predict academic performance, which improves the prediction accuracy even in the presence of students' diligence. Based on these analyses, education administrators could quantitatively understand the major factors leading to excellent or poor performance, detect undesirable abnormal behaviours in time and thus implement effective interventions to better guide students' campus lives at an early stage when necessary.-
dc.languageeng-
dc.relation.ispartofJournal of the Royal Society Interface-
dc.subjectacademic performance-
dc.subjectcampus behaviour-
dc.subjectcomputational social science-
dc.subjectdata science-
dc.subjecthuman behaviour-
dc.subjectorderliness-
dc.titleOrderliness predicts academic performance: Behavioural analysis on campus lifestyle-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1098/rsif.2018.0210-
dc.identifier.pmid30232241-
dc.identifier.scopuseid_2-s2.0-85054516833-
dc.identifier.volume15-
dc.identifier.issue146-
dc.identifier.spagearticle no. 0210-
dc.identifier.epagearticle no. 0210-
dc.identifier.eissn1742-5662-

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