Evaluating automatic group formation mechanisms to promote collaborative learning - a case study

Authors:
Carine G. Webber;Maria de Fátima Webber do Prado Lima
Affiliations:
Information Technology Centre, University of Caxias do Sul, Rua Francisco Getúlio Vargas, 1130, 95070-560 Caxias do Sul, RS, Brazil.;Information Technology Centre, University of Caxias do Sul, Rua Francisco Getúlio Vargas, 1130, 95070-560 Caxias do Sul, RS, Brazil
Venue:
International Journal of Learning Technology
Year:
2012

Citing 19
Cited 0

From data mining to knowledge discovery: an overview

Advances in knowledge discovery and data mining
Data clustering: a review

ACM Computing Surveys (CSUR)
Group formation in computer-supported collaborative learning

GROUP '01 Proceedings of the 2001 International ACM SIGGROUP Conference on Supporting Group Work
Machine Learning

Machine Learning
The effects of pair-programming on performance in an introductory programming course

SIGCSE '02 Proceedings of the 33rd SIGCSE technical symposium on Computer science education
Failure rates in introductory programming

ACM SIGCSE Bulletin
A Group Formation Tool in an E-Learning Context

ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
A design to promote group learning in e-learning: Experiences from the field

Computers & Education
A Framework for Semantic Group Formation

ICALT '08 Proceedings of the 2008 Eighth IEEE International Conference on Advanced Learning Technologies
Generating Teacher Adapted Suggestions for Improving Distance Educational Systems with SIgMa

ICALT '08 Proceedings of the 2008 Eighth IEEE International Conference on Advanced Learning Technologies
Web Usage Mining to Evaluate the Transfer of Learning in a Web-Based Learning Environment

WKDD '08 Proceedings of the First International Workshop on Knowledge Discovery and Data Mining
Clustering and Sequential Pattern Mining of Online Collaborative Learning Data

IEEE Transactions on Knowledge and Data Engineering
Formation of Learning Groups by using Learner Profiles and Context Information

Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Clustering learners according to their collaboration

CSCWD '09 Proceedings of the 2009 13th International Conference on Computer Supported Cooperative Work in Design
How Pair Programming Really Works

IEEE Software
Effects of Personality on Pair Programming

IEEE Transactions on Software Engineering
Data Mining: Practical Machine Learning Tools and Techniques

Data Mining: Practical Machine Learning Tools and Techniques
Empirical Studies of Pair Programming for CS/SE Teaching in Higher Education: A Systematic Literature Review

IEEE Transactions on Software Engineering
Forming heterogeneous groups for intelligent collaborative learning systems with ant colony optimization

ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Group work is an important resource that educators have in order to promote collaborative learning situations. In several domains it has been exploited as a valuable teaching strategy. In technical domains, such as logic programming, results on the effect of collaborative activities on learning remains still uncertain. In this sense, this paper intends to contribute with one main research questions: can an automatic group formation mechanism be able to form consistent and successful groups for learning activities? In order to answer this question, we have prepared an experiment with students from computer programming undergraduate course. Students were asked to work individually and in automatically formed pairs. Our conclusion is that group work can help and bring benefits to most learners. We demonstrate in this paper that automatic techniques can produce coherent results regarding group formation.