Authors:
Mohammad Jaber
1
;
Panagiotis Papapetrou
2
;
Ana González-Marcos
3
and
Peter T. Wood
1
Affiliations:
1
Birkbeck and University of London, United Kingdom
;
2
Stockholm University, Sweden
;
3
Universidad de la Rioja, Spain
Keyword(s):
Project Management, Asynchronous Communication, Educational Data Mining, Social Network Analysis.
Related
Ontology
Subjects/Areas/Topics:
Collaborative Learning
;
Computer-Supported Education
;
Learning/Teaching Methodologies and Assessment
;
Project Based Learning and Engineering Education
;
Social Context and Learning Environments
;
Web 2.0 and Social Computing for Learning and Knowledge Sharing
Abstract:
This paper studies the application of Educational Data Mining to examine the online communication behaviour
of students working together on the same project in order to identify the different roles played by the students.
Analysis was carried out using real data from students’ participation in project communication tools. Several
sets of features including individual attributes and information about the interactions between the project
members were used to train different classification algorithms. The results show that considering the individual
attributes of students provided regular classification performance. The inclusion of information about the
reply relationships among the project members generally improved mapping students to their roles. However,
“time-based” features were necessary to achieve the best classification results, which showed both precision
and recall of over 95% for a number of algorithms. Most of these “time-based” features coincided with the
first weeks of t
he experience, which indicates the importance of initial interactions between project members.
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