Implementation of Group Formation Algorithms in the ELARS Recommender System ARTICLE
Tina Knez, Martina Holenko Dlab, Natasa Hoic-Bozic, University of Rijeka, Department of Informatics
iJET Volume 12, Number 11, ISSN 1863-0383 Publisher: International Association of Online Engineering, Kassel, Germany
Collaborative learning is recognized as an effective way of gaining knowledge in an online environment. Therefore, e-courses frequently include collaborative e-learning activities (e-tivities) that are performed in pairs or small groups of students. One of the challenges for teachers who organize e-tivities is the effective group forming. This paper presents algorithms that can be used to divide a set of students participating in an e-tivity to homogeneous or heterogeneous groups. The criterion for automatic group formation includes the following characteristics: the program of study, gender, learning styles preferences, Web 2.0 tools preferences, knowledge level and activity level. Designed algorithms were implemented in the educational recommender system ELARS and tested in the context of e tivities.
Knez, T., Holenko Dlab, M. & Hoic-Bozic, N. (2017). Implementation of Group Formation Algorithms in the ELARS Recommender System. International Journal of Emerging Technologies in Learning (iJET), 12(11), 198-207. Kassel, Germany: International Association of Online Engineering. Retrieved December 14, 2017 from https://www.learntechlib.org/p/181442/.
© 2017 IAOE