Orderliness predicts academic performance: behavioural analysis on campus lifestyle

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...

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Veröffentlicht in:Journal of the Royal Society interface 2018-09, Vol.15 (146), p.20180210
Hauptverfasser: Cao, Yi, Gao, Jian, Lian, Defu, Rong, Zhihai, Shi, Jiatu, Wang, Qing, Wu, Yifan, Yao, Huaxiu, Zhou, Tao
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container_issue 146
container_start_page 20180210
container_title Journal of the Royal Society interface
container_volume 15
creator Cao, Yi
Gao, Jian
Lian, Defu
Rong, Zhihai
Shi, Jiatu
Wang, Qing
Wu, Yifan
Yao, Huaxiu
Zhou, Tao
description 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.
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subjects Academic Performance
Campus Behaviour
Computational Social Science
Data Science
Human Behaviour
Life Sciences–Physics interface
Orderliness
title Orderliness predicts academic performance: behavioural analysis on campus lifestyle
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