TY - CHAP A1 - Krieter, Philipp A1 - Breiter, Andreas ED - Krömker, Detlef ED - Schroeder, Ulrik T1 - Track every move of your students: log files for Learning Analytics from mobile screen recordings T2 - DeLFI 2018: die 16. E-Learning Fachtagung Informatik der Gesellschaft für Informatik e.V., 10.-12. September 2018, Frankfurt am Main, Deutschland N2 - 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. KW - Learning Analytics KW - mobile screen recordings KW - Computer Vison KW - data sources KW - Human Computer Interaction KW - log files Y1 - 2018 SN - 9783885796787 U6 - https://doi.org/10.18154/RWTH-2018-229913 VL - Lecture Notes in Informatics(LNI)-Proceedings, Vol. P-284 SP - 231 EP - 242 PB - Köllen Druck+Verlag CY - Bonn ER - TY - CHAP A1 - Krieter, Philipp A1 - Breiter, Andreas ED - Hofhues, Sandra ED - Schiefner-Rohs, Mandy ED - Aßmann, Sandra ED - Brahm, Taiga T1 - Digitale Spuren von Studierenden in virtuellen Lernumgebungen T2 - Studierende – Medien – Universität: Einblicke in studentische Medienwelt N2 - In diesem Beitrag werden die Ergebnisse und der Prozess der LogfileAnalyse im Projekt You(r) Study beschrieben, die zum Ziel hat, die qualitativen Daten des Projekts mit den quantitativen Logdaten eines Learning Management Systems zu verbinden. Mittels deskriptiver Methoden und Clusterbildung werden die Logdaten in Hinblick auf die Fragestellungen des Projekts betrachtet. Außerdem wird kritisch diskutiert, welche Grenzen eine Logfile-Analyse in Bezug zur Zielsetzung hat KW - moodle KW - Logfile-Analyse KW - Learning Analytics KW - Learning Management System Y1 - 2020 SN - 9783830940494 U6 - https://doi.org/10.31244/9783830990499 SP - 131 EP - 152 PB - Waxmann CY - Münster ER - TY - RPRT A1 - Duckardt, Alina T1 - Anwendung von Learning Analytics in Schule und Hochschule KW - Hg_TCR KW - Ethik KW - Datenschutz KW - Höhere Bildung KW - Learning Analytics Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-36521 VL - Arbeitspapier des Lehrgebiets Datenbanken und E-Business, Nr. 1/2022 CY - Düsseldorf ER -