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Identifying student groups through their wifi digital footprint.

Scanlon, Philip (2016) Identifying student groups through their wifi digital footprint. In: National Forum - Exploring LA in the Irish HE Landscape, 8th December 2016, Dublin.

Abstract
Research in the field of peer influence is often based on the data collected through direct observation, interviews and surveys. These methods can be prone to bias and errors induced through human errors caused by question or answer interpretation or interviewee recall of historical events. My research utilises a unique form of data collection in the learning analytics domain. The data source is the anonymised digital footprint generated through the interaction of students wifi enabled devices and the universities wifi platforms. This datasets are collected without the intervention of researchers. It is hypothesized that the analysis of wifi logs can identify: student location patterns, duration of visits to each location and more importantly those who colocation regularly at these location. This research will carry out a longitudinal study to identify friendships and the correlation between friends academic results.
Metadata
Item Type:Conference or Workshop Item (Invited Talk)
Event Type:Conference
Refereed:No
Subjects:Computer Science > Information technology
Social Sciences > Educational technology
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland Grant Number SFI/12/RC/2289
ID Code:21545
Deposited On:11 Jan 2017 09:23 by Philip Scanlon . Last Modified 19 Jul 2018 15:09
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