Computational Statistics & Data Analysis
A framework for process-solution analysis in collaborative learning environments
International Journal of Human-Computer Studies
Theory-Driven Group Formation through Ontologies
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
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
Assigning Students to Groups Using General and Context-Specific Criteria
IEEE Transactions on Learning Technologies
Guiding knowledge communication in CSCL via group knowledge awareness
Computers in Human Behavior
Improving Group Selection and Assessment in an Asynchronous Collaborative Writing Application
International Journal of Artificial Intelligence in Education
An Ambient Awareness Tool for Supporting Supervised Collaborative Problem Solving
IEEE Transactions on Learning Technologies
A groupware system to support collaborative programming: Design and experiences
Journal of Systems and Software
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Nowadays, most students take part in collaborative learning activities, which consist of carrying out academic tasks in groups. Computer-Supported Collaborative Learning (CSCL) systems offer tools to support these collective activities. The method used to form the learners groups can be a key element in achieving a successful collaboration. This paper proposes a method of group formation using indicators that analyze previous collaborative activities of the learners. This method is based on data depth, a statistical tool that allows the ordering of multivariate data. In the process, the data depth of the analysis indicators of each learner is calculated, providing a measure that compares the values of the indicators of each learner with those of other learners. Thus, the method allows us to group learners whose analysis indicators register similar or different values. In this way, a flexible approach for forming homogeneous or heterogeneous groups is offered. We develop a software tool for this method, which we use in a case study to form groups of learners who work on programming tasks using a CSCL system.