Eliciting Motivation Knowledge from Log Files Towards Motivation Diagnosis for Adaptive Systems

Cocea, Mihaela and Weibelzahl, Stephan (2007) Eliciting Motivation Knowledge from Log Files Towards Motivation Diagnosis for Adaptive Systems. In: User Modeling 2007. UM 2007. Lecture Notes in Computer Science, 4511 . Springer Verlag, pp. 197-206. ISBN 978-354073077-4

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Abstract

Motivation is well-known for its importance in learning and its influence on cognitive processes. Adaptive systems would greatly benefit from having a user model of the learner's motivation, especially if integrated with information about knowledge. In this paper a log file analysis for eliciting motivation knowledge is presented, as a first step towards a user model for motivation. Several data mining techniques are used in order to find the best method and the best indicators for disengagement prediction. Results show a very good level of prediction: around 87% correctly predicted instances of all three levels of engagement and 93% correctly predicted instances of disengagement. Data sets with reduced attribute sets show similar results, indicating that engagement level can be predicted from information like reading pages and taking tests, which are common to most e-Learning systems.

Item Type:	Book Section
Uncontrolled Keywords:	Log files analysis; User modeling
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Electronic computers. Computer science > Computer Systems T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science > Computer Systems L Education > LC Special aspects / Types of education > E-Learning
Divisions:	School of Computing > Staff Research and Publications
Depositing User:	Tamara Malone
Date Deposited:	11 Sep 2025 13:55
Last Modified:	11 Sep 2025 13:55
URI:	https://norma.ncirl.ie/id/eprint/8851

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