Track every move of your students: log files for Learning Analytics from mobile screen recordings
Zusammenfassung
One of the main data sources for Learning Analytics are Learning Management Systems (LMS). These log files are limited though to interactions within the LMS and cannot take into account interactions of students in other applications and software in a digital learning environment. In this paper, we present an approach for generating log files based on mobile screen recordings as a data source for Learning Analytics. Logging mobile application usage is limited to rather general system events unless you have access to the source code of the operating system or applications. To address this we generate log files from mobile screen recordings by applying computer vision and machine learning methods to detect individually defined events. In closing, we discuss how these log files can be used as a data source for Learning Analytics and relevant ethical concerns.
- Vollständige Referenz
- BibTeX
Krieter, P. & Breiter, A.,
(2018).
Track every move of your students: log files for Learning Analytics from mobile screen recordings.
In:
Krömker, D. & Schroeder, U.
(Hrsg.),
DeLFI 2018 - Die 16. E-Learning Fachtagung Informatik.
Bonn:
Gesellschaft für Informatik e.V..
(S. 231-242).
@inproceedings{mci/Krieter2018,
author = {Krieter, Philipp AND Breiter, Andreas},
title = {Track every move of your students: log files for Learning Analytics from mobile screen recordings},
booktitle = {DeLFI 2018 - Die 16. E-Learning Fachtagung Informatik},
year = {2018},
editor = {Krömker, Detlef AND Schroeder, Ulrik} ,
pages = { 231-242 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
author = {Krieter, Philipp AND Breiter, Andreas},
title = {Track every move of your students: log files for Learning Analytics from mobile screen recordings},
booktitle = {DeLFI 2018 - Die 16. E-Learning Fachtagung Informatik},
year = {2018},
editor = {Krömker, Detlef AND Schroeder, Ulrik} ,
pages = { 231-242 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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| proceedings_23.pdf | 348.3Kb | Öffnen |
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Mehr Information
ISBN: 978-3-88579-678-7
ISSN: 1617-5468
Datum: 2018
Sprache:
(en)
(en)
Typ: Text/Conference Paper

