Cross-System Validation of Engagement Prediction from Log Files View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2007

AUTHORS

Mihaela Cocea , Stephan Weibelzahl

ABSTRACT

Engagement is an important aspect of effective learning. Time spent using an e-Learning system is not quality time if the learner is not engaged. Tracking the student disengagement would give the possibility to intervene for motivating the learner at appropriate time. In previous research we showed the possibility to predict engagement from log files using a web-based e-Learning system. In this paper we present the results obtained from another web-based system and compare them to the previous ones. The similarity of results across systems demonstrates that our approach is system-independent and that engagement can be elicited from basic information logged by most e-Learning systems: number of pages read, time spent reading pages, number of tests/ quizzes and time spent on test/ quizzes. More... »

PAGES

14-25

Book

TITLE

Creating New Learning Experiences on a Global Scale

ISBN

978-3-540-75194-6
978-3-540-75195-3

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-75195-3_2

DOI

http://dx.doi.org/10.1007/978-3-540-75195-3_2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1048203376


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