Analyzing a Computational Infrastructure for Supporting the Design of Group Learning Scenarios

Collaborative learning (CL) processes are not always effective and inadequate design of CL scenarios is one of the main causes of its failure. Designing CL scenarios is a complex task, since it involves countless requirements and constraints that affect the learning process. A previous study showed that educators, in general, perform an inappropriate design of CL scenarios—failing to specify essential parameters and processes, mainly regarding the guidance of the learners’ actions and the evaluation of their learning. This indicates the need to provide educators with proper support and guidance. This study is particularly interested in providing a computational infrastructure to support and guide educators throughout the design process. The proposed infrastructure was evaluated through a case study with a sample of professors at a university in real situations of group work design in their face-to-face undergraduate courses. The results showed that, for this sample of educators, the infrastructure was able to expose them to relevant design parameters, supporting them in their specification and helping them to understand these parameters. Therefore, the infrastructure shows potential to prevent CL scenarios from being inappropriately and inefficiently structured.