Article In: cienciavitae, dblp, scopus, orcid
Predicting teamwork results from social network analysis
Expert Systems
— 2015 — Expert Syst. J. Knowl. Eng.
Key information
Authors:
Published in
April 1, 2015
Abstract
Modelling students' behaviours has reached a status that can only be overcome by improving the ability of predicting the results on teamwork. Indeed, teamwork is an important piece on the learning process, but understanding their mechanisms and predicting the results achieved is far from being solved by traditional classifiers. In this paper, we address the problem of predicting teamwork results, and propose a recommender system that suggests new teams, in the context of a given curricular unit. Any student, who is looking for a team, may use the system; in particular, he may ask for the best team to join, either considering all available colleagues or just the set of his previous teammates. Our system makes use of social network analysis and classification methods as the algorithmic core of the decision-making process. System evaluation is presented through a set of experimental results, which report the performance of social network analysis and classification algorithms over real datasets.
Publication details
Authors in the community:
Pedro Miguel Terras Crespo
ist156986
Claudia Martins Antunes
ist14046
Publication version
P - Proof
Publisher
Expert Syst. J. Knowl. Eng.
Link to the publisher's version
https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.12038?deniedAccesAsCustomisedMessage=&userIsAuthenticated=false
Title of the publication container
Expert Systems
First page or article number
312
Last page
325
Volume
32
Issue
2
Fields of Science and Technology (FOS)
computer-and-information-sciences - Computer and information sciences
Publication language (ISO code)
eng - English
Alternative identifier (URI)
http://www.scopus.com/inward/record.url?eid=2-s2.0-84926529596&partnerID=MN8TOARS
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