Mobile Social Media Usage and Academic Performance

Social media have penetrated in the everyday life of Internet users, and the increasing pervasiveness of smartphones is only strengthening this phenomenon. Nowadays, these two technologies are intertwined, since smartphones are becoming more and more pervasive, especially in the student population.

In the literature, there is overwhelming evidence of the negative impact of social media, especially Facebook, and smartphone usage on academic performance. These technologies combined lead to a series of behaviours that cause students to dedicate more time to them than actually studying.

We propose to bridge this gap via a systematic approach consisting in defining new metrics for representing social media usage and using smartphones to both track app usage and administer time diaries, a well known sociological tool for understanding people's time use. This innovative coupling allows us to isolate the time of specific activities related to academic performance and provide new insights on behavioural correlations.

We validate our proposed solution on the data from the SmartUnitn project, which belongs to a family of projects called i-Log that leverages on smartphones to extract behavioural patterns from people and develop systems that assist users in their everyday life.

In this project, 72 students were selected from the ones enrolled at the University of Trento in the academic year 2015-2016. The project lasted two weeks. In the first one, students used i-Log to answer to time diaries while also having their data collected.

The SmartUnitn dataset amounts to 110 Gb, containing behavioural data from smartphones merged with socio-demographic characteristics of students obtained both through surveys and academic performance data provided by the University of Trento.

We quantify two dimensions of the parameters for understanding the usage behaviour of students with respect to social media: temporal distribution of the usage, which allows us to identify temporal patterns, and its average mean.

Within SM apps for both studying and attending lessons, Instant Messaging (IM) apps are the most checked but with the longest window of time in between sessions, while Social Network Sites (SNS) apps are the ones with the highest duration of usage.

In this paper, we proposed to overcome the current limitations of the state of the art in linking students' usage of social media on smartphones by coupling smartphones and time diaries, to then be able to match reports of time use with actual logs of SM apps.

Our results seems to confirm our hypothesis that controlling the use of social media during studying or lesson attending is more informative with respect to their association with students' academic performance than considering their general use without activity distinction.