Análisis de la formación de grupos en Aprendizaje Colaborativo Soportado por Computadoras

ARIEL MONTESERIN; SILVIA SCHIAFFINO; PATRICIO GARCIA; ANALÍA AMANDI,

Joao Pessoa

Simposio; SBIE 2010, XXI Simposio Brasilero de Informática en Educación; 2010

Group formation and performance is a research area that has gained great interest in the e-learning community in the last years. The motivation underlying this area is that putting a group of students to work together does not guarantee learning. In this work we analyze whether some students’ individual features influence group performance. Particularly we have analyzed by applying Machine Learning techniques to students’ log files in a CSCL environment, how their learning styles and their negotiation skills influence on the result of group work. The results we have obtained indicate that these aspects actually have an effect on the group performance. In addition, we propose some ideas that teachers or an automatic tool in a CSCL environment can take into account to form groups that will, supposedly, work and learn better.