Authors:
Elias de Oliveira
;
Márcia Gonçalves Oliveira
and
Patrick Marques Ciarelli
Affiliation:
Universidade Federal do Espírito Santo, Brazil
Keyword(s):
Activities Recommendation, Computers Programming, e-Learning, kNN Algorithm.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaborative Filtering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Symbolic Systems
;
User Profiling and Recommender Systems
Abstract:
Personalization is more than ever the must feature’s requirement a system needs to comply this days. One can find in many areas online systems which have as a goal to provide each individual user with their potential
needs, or desire. To achieve this goal they need to rely on a good recommendation system. Hence, recommendation systems must work under the assumption that one’s need, could also be applied to someone else who has similar desire, tastes, or necessities. So, we present in this paper a system for recommending students extra activities accordingly to their individual needs. The additional assumption is that a promptly reply and tailored guidance in each step of the way of their learning process improve their chances of success. We propose the use of the kNN algorithm to assign activities to students as much similar as possible an expert would as well assign. The results are promising as we are able to mimic human decisions 90.0% of the time.