δείτε την πρωτότυπη σελίδα τεκμηρίου στον ιστότοπο του αποθετηρίου του φορέα για περισσότερες πληροφορίες και για να δείτε όλα τα ψηφιακά αρχεία του τεκμηρίου*
Social network analysis techniques and text mining to assess the learning process of students' participation in the online discussion
On a daily basis, a large amount of data is gathered through the participation of students in elearning
environments. This wealth of data is an invaluable asset to researchers as they can utilize
it in order to generate conclusions and identify hidden patterns and trends by using big data
analytics techniques. The purpose of this study is a threefold analysis of the data that are related to
the participation of students in the online forums of their University. In one hand the content of
the messages posted in these fora can be efficiently analyzed by text mining techniques. On the
other hand, the network of students interacting through a forum can be adequately processed
through social network analysis techniques. Still, the combined knowledge attained from both of
the aforementioned techniques, can provide educators with practical and valuable information for
the evaluation of the learning process, especially in a distance learning environment. In addition,
we propose a classification via decision tree approach in order to forecast students' learning
performance based on forum data. The study was conducted by using real data originating from
the online forums of the Hellenic Open University (HOU). The analysis of the data has been
accomplished by using the R tools, in order to analyze the structure and the content of the
exchanged messages in these fora as well as to model the interaction of the students in the
discussion threads.
*Η εύρυθμη και αδιάλειπτη λειτουργία των διαδικτυακών διευθύνσεων των συλλογών (ψηφιακό αρχείο, καρτέλα τεκμηρίου στο αποθετήριο) είναι αποκλειστική ευθύνη των αντίστοιχων Φορέων περιεχομένου.
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