Academic Performance and Behavioral Patterns

Kassarnig, Valentin; Mones, Enys; Bjerre-Nielsen, Andreas; Sapieżyński, Piotr; Lassen, David Dreyer; Lehmann, Sune

doi:10.48550/arxiv.1706.09245

Cited by 2 publications

(3 citation statements)

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“…In a similar study, Bogomolov et al (2014) tried to predict the reported levels of stress perceived by the participants in terms of their call related features, Bluetooth data, weather conditions and personality traits. There have been studies along similar lines focussing on day-to-day mood (Asselbergs et al, 2016), depression (Saeb et al, 2015), specific mental disorders (Torous et al, 2016), academic performance (Kassarnig et al, 2017), and positioning in the social network (Aledavood et al, 2017b). This is a rapidly developing field 10 in its inception phase with the current focus on infrastructure development (Huguet et al, 2016;Aledavood et al, 2017a).…”

Section: Daily and Seasonal Rhythmsmentioning

confidence: 99%

Social physics: uncovering human behaviour from communication

Bhattacharya

Kaski

2018

Advances in Physics: X

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In the post year 2000 era the technologies that facilitate human communication have rapidly multiplied. While the adoption of these technologies has hugely impacted the behaviour and sociality of people, specifically in urban but also in rural environments, their "digital footprints" on different data bases have become an active area of research. The existence and accessibility of such large population-level datasets, has allowed scientists to study and model innate human tendencies and social patterns in an unprecedented way that complements traditional research approaches like questionnaire studies. In this review we focus on data analytics and modelling research -we call Social Physics -as it has been carried out using the mobile phone data sets to get insight into the various aspects of human sociality, burstiness in communication, mobility patterns, and daily rhythms.

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Section: Daily and Seasonal Rhythmsmentioning

confidence: 99%

Social physics: uncovering human behaviour from communication

Bhattacharya

Kaski

2018

Advances in Physics: X

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“…Also note that there is no observable difference between the grade distribution of the last two attendance groups. The lack of difference suggests that attendance is better at discriminating between whether or not a student is likely to fail rather than predicting the actual grade achieved provided that the student passes the exam; this observation is supported by separate work on the CNS dataset [38], where the predictive power of not only class attendance, but of many other behavioral factors, is considered. To statistically evaluate the variation in the distribution over the groups, we performed a Kruskal-Wallis H-test.…”

Section: Resultsmentioning

confidence: 92%

“…Note that it is beyond the scope of this study to control for personal characteristics. However, in [38], attendance is shown to be an important predictor of subsequent performance when controlling for performance of friends and personality. Also, our estimates are not causal estimates of attendance, cf.…”

Section: Discussionmentioning

confidence: 94%

Class attendance, peer similarity, and academic performance in a large field study

et al. 2017

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Identifying the factors that determine academic performance is an essential part of educational research. Existing research indicates that class attendance is a useful predictor of subsequent course achievements. The majority of the literature is, however, based on surveys and self-reports, methods which have well-known systematic biases that lead to limitations on conclusions and generalizability as well as being costly to implement. Here we propose a novel method for measuring class attendance that overcomes these limitations by using location and bluetooth data collected from smartphone sensors. Based on measured attendance data of nearly 1,000 undergraduate students, we demonstrate that early and consistent class attendance strongly correlates with academic performance. In addition, our novel dataset allows us to determine that attendance among social peers was substantially correlated (>0.5), suggesting either an important peer effect or homophily with respect to attendance.

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Academic Performance and Behavioral Patterns

Cited by 2 publications

References 0 publications

Social physics: uncovering human behaviour from communication

Social physics: uncovering human behaviour from communication

Class attendance, peer similarity, and academic performance in a large field study

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