Improving e-learning communities through optimal composition of multidisciplinary learning groups

  • Authors:

  • Maria-Iuliana Dascalu;Constanta-Nicoleta Bodea;Miltiadis Lytras;Patricia Ordoñez De Pablos;Alexandru Burlacu

  • Affiliations:

  • Politehnica University of Bucharest, Department of Engineering in Foreign Languages, Splaiul Independentei 313, Bucharest 060042, Romania;The Bucharest Academy of Economic Studies, Department of Economic Informatics and Cybernetics, Calea Dorobani, 15-17, Sector 1, Bucharest 010552, Romania;ELTRUN, The Research Center, Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece;University of Oviedo, Department of Business Administration, Oviedo, Spain;Politehnica University of Bucharest, Department of Engineering in Foreign Languages, Splaiul Independentei 313, Bucharest 060042, Romania

  • Venue:
  • Computers in Human Behavior
  • Year:
  • 2014

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Abstract

The current study proposes an intelligent approach to compose optimal learning groups in which the members have different domain backgrounds. The approach is based on a well-known evolutionary algorithm - Particle Swarm Optimization. The authors claim that quantifying various indicators, such as background diversity and similarity between the type of interest of the participants, within a group and between groups can positively impact on building learning groups. The algorithm is integrated in an ontology-based e-learning system, designed to create self-built educating communities, in which a trainees goes through the education process, gains points through achievements and ultimately becomes a trainer. When creating a new account, the newly created trainee is asked to self asses himself by filling out a form. The resulting profile is used to assign the user to the most suitable learning group. We propose to assign him by the following rule: maximizing the diversity within a group (due to the fact that multidisciplinary teams are more challenging) and minimizing the diversity between groups (all the groups should have similar composition), meaning a group will have members with similar interests. The study is presented in the context of group building strategies in adults' education.