Collaborative learning activities are an essential part of education and are part of many teaching approaches including problem-based learning and project-based learning. However, in open-ended collaborative small group work, evidence on the effectiveness of using these learning activities are hard to find. The PELARS project explores how multimodal learning analytics can generate information about what happens when students are engaged in collaborative, project-based learning activities.
This article was originally published in the IOTAP 2016 brochure.
The PELARS project investigates how small groups of learners interact. This by using various sensors that include computer vision, data from the learning objects – in this case physical-computing components – and the student’s generated content. The system then processes and extracts different aspects of the students’ interactions to investigate what features of student group work that are good predictors of team success.
Daniel Spikol, one of the researchers in the project, says: ”The need to provide support for collaborative and complex learning activities across all types of education that empower learners and teachers is one way to keep education innovative and meaningful to society. New technologies provide vast educational resources, but to leverage these technologies, the forms of education need to evolve and projects like PELARS offer solutions for helping.”
The PELARS project has received funding from the European Union’s 7th Framework Programme for research, technological development and demonstrations (GA No. 619738). The project is a collaboration with several European universities, SMEs, and non-profit organizations.