Using similarity measures for collaborating groups formation: A model for distance learning environments

Adaptability to each separate user's needs and preferences is a common concern in modern e-learning systems. Among various adaptation techniques described in recent research, collaboration support seeks to create groups that efficiently work together in order to advance user's learning. This paper defines two similarity coefficients between users and learning objects and focuses on automatic creation of properly matching collaborating groups based on an algorithmic approach. By adopting methods derived from Group Technology, the method simultaneously selects appropriate learning objects to form a corresponding educational package for each group, thus assuring optimal value of user's learning.