Assignment of Groups for the Execution of a Collaborative Work Using Emerging Algorithms

Abstract

In educational institutions collaborative work is used as a strategy to enhance active learning. One of the organizational tasks that is in charge of the teacher is the assignment of groups. Hence the purpose of this article, which is to show how emerging algorithms with their self-organization characteristics, can be used in group formation to carry out a collaborative task. Showing that performance and small groups do not necessarily go hand in hand. The methodology used is a case study and the sample corresponds to 62 students of the subject of Artificial Intelligence of Distance Modality of the Universidad Técnica Particular de Loja, in the academic period April-August/2018, to whom a dichotomous 16-item survey was applied based on the three phases of the Zimmerman selfregulated learning cycle. Among the remarkable results, we can mention that the synergy of individual regulation known as socially shared regulation influenced the execution of the collaborative task. Likewise, the cohesion of a group is not a determining variable to achieve meaningful learning since the less cohesion the greater regulation of socially shared learning. The contribution of the present study is given in the field of Computer Supported Cooperative Learning (CSCL) to alleviate one of the administrative tasks of teachers “Group Assignment”, which can be replicated in classroom learning environments or in any of the variations of e-learning.