Title :
A Outliers Analysis of Learner´s Data based on User Interface Behaviors
Author :
Kim, Yong S. ; Yoon, Tae B. ; Cha, Hyun J. ; Jung, Young M. ; Wang, Eric ; Lee, Jee H.
Author_Institution :
Sungkyunkwan Univ., Suwon
Abstract :
A learning diagnosis system collects data from a learner´s learning process, and analyzes it to build a suitable model for the learner, which can then be incorporated into an intelligent tutoring system to provide customized tutoring services. However, if the collected data reflects inconsistent learner behaviors or unpredictable learning tendencies, then the reliability of the learner model is degraded. In this paper, the outliers in the learner´s data are eliminated by a k-NN method. We apply this method to an experimental data set obtained using DOLLS-HI, a learner diagnosis system that uses housing interior learning contents to diagnose learning styles. The resulting diagnosis model shows improved reliability than before eliminating the outliers.
Keywords :
intelligent tutoring systems; pattern classification; user centred design; user interfaces; DOLLS-HI; customized tutoring services; housing interior learning contents; intelligent tutoring system; k-NN method; learner data outliers analysis; learner diagnosis system; learning diagnosis system; user interface behaviors; Aggregates; Data analysis; Data engineering; Deductive databases; Design engineering; Information analysis; Intelligent systems; Nearest neighbor searches; User interfaces; Voting;
Conference_Titel :
Advanced Learning Technologies, 2007. ICALT 2007. Seventh IEEE International Conference on
Conference_Location :
Niigata
Print_ISBN :
0-7695-2916-X
DOI :
10.1109/ICALT.2007.25