Authors:
Italo Zoppis
1
;
Riccardo Dondi
2
;
Sara Manzoni
1
;
Giancarlo Mauri
1
;
Luca Marconi
3
and
Francesco Epifania
3
Affiliations:
1
Department of Computer Science, University of Milano Bicocca, Milano and Italy
;
2
Department of Letters, Philosophy, Communication, University of Bergamo, Bergamo and Italy
;
3
Social Things srl, Milano and Italy
Keyword(s):
Social Networks, Optimized Social Explanation, Communities Identification, Genetic Algorithms, WhoTeach.
Related
Ontology
Subjects/Areas/Topics:
Computer-Supported Education
;
Domain Applications and Case Studies
;
Intelligent Learning and Teaching Systems
Abstract:
Recommender Systems have became extremely appealing for all technology enhanced learning researches aimed to design, develop and test technical innovations which support and enhance learning and teaching practices of both individuals and organizations. In this scenario a new emerging paradigm of explainable Recommander Systems leverages social friend information to provide (social) explanations in order to supply users with his/her friends’ public interests as explained recommendation. In this paper we introduce our educational platform called “WhoTeach”, an innovative and original system to integrate knowledge discovery, social networks analysis, and educational services. In particular, we report here our work in progress for providing “WhoTeach” environment with optimized Social Explainable Recommandations oriented to design new teachers’ programmes and courses.