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- Publisher Website: 10.1098/rsif.2018.0210
- Scopus: eid_2-s2.0-85054516833
- PMID: 30232241
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Article: Orderliness predicts academic performance: Behavioural analysis on campus lifestyle
Title | Orderliness predicts academic performance: Behavioural analysis on campus lifestyle |
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Authors | |
Keywords | academic performance campus behaviour computational social science data science human behaviour orderliness |
Issue Date | 2018 |
Citation | Journal of the Royal Society Interface, 2018, v. 15, n. 146, article no. 0210 How to Cite? |
Abstract | Quantitative 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 Identifier | http://hdl.handle.net/10722/346683 |
ISSN | 2023 Impact Factor: 3.7 2023 SCImago Journal Rankings: 1.101 |
DC Field | Value | Language |
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dc.contributor.author | Cao, Yi | - |
dc.contributor.author | Gao, Jian | - |
dc.contributor.author | Lian, Defu | - |
dc.contributor.author | Rong, Zhihai | - |
dc.contributor.author | Shi, Jiatu | - |
dc.contributor.author | Wang, Qing | - |
dc.contributor.author | Wu, Yifan | - |
dc.contributor.author | Yao, Huaxiu | - |
dc.contributor.author | Zhou, Tao | - |
dc.date.accessioned | 2024-09-17T04:12:34Z | - |
dc.date.available | 2024-09-17T04:12:34Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Journal of the Royal Society Interface, 2018, v. 15, n. 146, article no. 0210 | - |
dc.identifier.issn | 1742-5689 | - |
dc.identifier.uri | http://hdl.handle.net/10722/346683 | - |
dc.description.abstract | Quantitative 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.language | eng | - |
dc.relation.ispartof | Journal of the Royal Society Interface | - |
dc.subject | academic performance | - |
dc.subject | campus behaviour | - |
dc.subject | computational social science | - |
dc.subject | data science | - |
dc.subject | human behaviour | - |
dc.subject | orderliness | - |
dc.title | Orderliness predicts academic performance: Behavioural analysis on campus lifestyle | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1098/rsif.2018.0210 | - |
dc.identifier.pmid | 30232241 | - |
dc.identifier.scopus | eid_2-s2.0-85054516833 | - |
dc.identifier.volume | 15 | - |
dc.identifier.issue | 146 | - |
dc.identifier.spage | article no. 0210 | - |
dc.identifier.epage | article no. 0210 | - |
dc.identifier.eissn | 1742-5662 | - |