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Author Bousbia, Nabila
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract Abstract. It is argued that the analysis of the learner’s generated log files during interactions with a learning environment is necessary to produce interpretative views of their activities. The analysis of these log files, or traces, provides "knowledge " about the activity we call indicators. Our work is related to this research field. We are particularly interested in automatically identifying learners ’ learning styles from learning indicators. This concept, used in several Educational Hypermedia Systems (EHS) as a criterion for adaptation and tracking, belongs to a set of behaviors and strategies in how to manage and organize information. In this paper, we validate our approach of auto-detection of student's learning styles based on their navigation behavior using machinelearning classifiers. 1
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article