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

**Authors:** Valentin Kassarnig, Andreas Bjerre-Nielsen, Enys Mones, Sune Lehmann,, David Dreyer Lassen

arXiv: 1702.01262 · 2018-04-10

## TL;DR

This large field study uses smartphone sensor data to accurately measure class attendance and finds it strongly predicts academic success and correlates among social peers, overcoming survey biases.

## Contribution

Introduces a novel smartphone-based method for measuring class attendance, enabling more accurate analysis of its impact on academic performance.

## Key findings

- Early and consistent attendance predicts better grades.
- Attendance among social peers is substantially correlated.
- Smartphone data overcomes survey biases in attendance measurement.

## Abstract

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.

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/1702.01262/full.md

## References

40 references — full list in the complete paper: https://tomesphere.com/paper/1702.01262/full.md

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Source: https://tomesphere.com/paper/1702.01262