Abstract:

Indicators from the PISA (Programme for International Student Assessment) show that collaborative problem-solving is one of the areas requiring attention in the upcoming years. It seems there is an imbalance between society needs and the perceptions students have about their skills to solve problems collaboratively. Thus, whereas students think they are good to collaborate to solve problems, the work market stakeholders identify weaknesses in this field. This work provides some hints about what could be done to help university students to develop their collaborative problem-solving skills. We focus in the statistics subject in the degree of psychology. Statistics is one of these areas of knowledge in which collaborative work is common. Take, for example, the case of the evolution of the R Project for Statistical Computing (https://www.r-project.org). The R project has quickly evolved as a collaborative-based project in the last decades and many scientists consider it as the lingua franca for statistical data analysis. Our proposal vertebrates into four main points. Firstly, we think strategical organization and discussion is in the core of collaborative problem-solving. As a result, university students should be encouraged to think about the problem-task in these terms. Communication skills, planning and shared understanding of the problem should be stressed when student teams try to solve the problem. Secondly, we think the better way to make a team work is finding consensus. This consensus is transversal to all team activity and it is related with the multi-agent and dynamic leadership. On the other hand, we also think that teams working collaboratively need certain rules to keep working efficiently. As long as team members are aware of their roles and committed to them as well as they play the agreed rules fairly, the best the team output. Finally, from an instructional point of view, monitoring and providing continuous feedback is crucial to help students to solve the problems they face. In this paper, we provide some insights to make the collaborative problem-solving philosophy work in the class context at university.

Keywords:

Problem-based learning, collaborative problem, statistics, psychology, instruction.