  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.
