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Using WiFi technology to identify student activity within a bounded environment

Scanlon, Philip and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2017) Using WiFi technology to identify student activity within a bounded environment. In: EC-TEL 2017, 11-15 Sep 2017, Tallinn, Estonia.

We use the unique digital footprints created by student interactions with online systems within a University environment to measure student behaviour and correlate it with exam performance. The specific digital footprint we use is student use of the Eduroam WiFi platform within our campus from smartphones, tablets and laptops. The advantage of this data-set is that it captures the personal interactions each student has with the IT systems. Data-sets of this type are usually structured, complete and traceable. We will present findings that illustrate that the behaviour of students can be contextualised within the academic environment by mining this data-set. We achieve this through identifying student location and those who share that location with them and cross-referencing this with the scheduled University timetable.
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Social Network Analysis
Subjects:Computer Science > Computer networks
Computer Science > Machine learning
DCU Faculties and Centres:Research Institutes and Centres > INSIGHT Centre for Data Analytics
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Data Driven Approaches in Digital Education. Lecture Notes in Computer Science (LNCS) . Springer International Publishing.
Publisher:Springer International Publishing
Official URL:https://www.springerprofessional.de/en/using-wifi-...
Copyright Information:© 2017 Springer. The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289
ID Code:21857
Deposited On:13 Sep 2017 08:19 by Philip Scanlon . Last Modified 05 Jan 2022 14:19

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