Team formation instruments to enhance learner interactions in open learning environments. (April 2015)

• Record Type: Journal Article
• Authors: Spoelstra, Howard; van Rosmalen, Peter; Houtmans, Tilly; Sloep, Peter
• Is Part Of: Computers in human behavior. Volume 45(2015)
• Page Start: 11
• Page End: 20
• Publication Date: 2015-04
• Subjects: Open learning environments -- MOOCs -- Social learning networks -- Team formation model -- Project-based learning -- Project team formation; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2014.11.038
• Languages: English
• ISSNs: 0747-5632

Abstract

Highlights: Facilitating team formation for project-based learning in MOOCs. Team formation model describing the project definition and team formation process. Validated principles and algorithms for automated formation of teams. Abstract: Open learning environments, such as Massive Open Online Courses (MOOCs), often lack adequate learner collaboration opportunities; they are also plagued by high levels of drop-out. Introducing project-based learning (PBL) can enhance learner collaboration and motivation, but PBL does not easily scale up into MOOCS. To support definition and staffing of projects, team formation principles and algorithms are introduced to form productive, creative, or learning teams. These use data on the project and on learner knowledge, personality and preferences. A study was carried out to validate the principles and the algorithms. Students ( n = 168) and educational practitioners ( n = 56) provided the data. The principles for learning teams and productive teams were accepted, while the principle for creative teams could not. The algorithms were validated using team classifying tasks and team ranking tasks. The practitioners classify and rank small productive, creative and learning teams in accordance with the algorithms, thereby validating the algorithms outcomes. When team size grows, for practitioners, forming teams quickly becomes complex, as demonstrated by the increased divergence in ranking and classifying accuracy. Discussion of the results, conclusions, and directions for future research are provided.