DocumentCode :
240467
Title :
Investigating Students´ Interaction Profile in an Online Learning Environment with Clustering
Author :
Akcapynar, Gokhan ; Altun, Arif ; Cosgun, Erdal
Author_Institution :
Comput. Educ. & Instructional Technol., Hacettepe Univ., Ankara, Turkey
fYear :
2014
fDate :
7-10 July 2014
Firstpage :
109
Lastpage :
111
Abstract :
The aim of this study is to identify clusters of students who interact with an online learning environment in similar ways. The study included analyzing three-month interaction data from 74 undergraduates in the online learning environment using the Self Organizing Map (SOM) clustering method. The results of analysis revealed the existence of three distinct groups of students, labeled by their interaction (non-active, active, very active) and course success (low learning, medium learning, high learning). These are the preliminary results of the study and the cluster data which was obtained here is intended to be used in further studies for classifying new students or adaptation and personalization purposes.
Keywords :
computer aided instruction; pattern clustering; self-organising feature maps; SOM clustering method; cluster data; online learning environment; self organizing map clustering method; student interaction profile; Adaptation models; Artificial intelligence; Computational modeling; Computers; Data mining; Graphics; Navigation; clustering; interaction data; student behavior modeling; student profiling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Learning Technologies (ICALT), 2014 IEEE 14th International Conference on
Conference_Location :
Athens
Type :
conf
DOI :
10.1109/ICALT.2014.40
Filename :
6901411
Link To Document :
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