%0 Journal Article
%4 sid.inpe.br/plutao/2014/11.28.00.59
%2 sid.inpe.br/plutao/2014/11.28.00.59.28
%@doi 10.4018/ijdet.2014040101
%@issn 1539-3100
%@issn 1539-3119
%F lattes: 9922863822347014 4 SilvaBrMaViRoCoFr:2014:SoNeAn
%T Social Network Analysis and Participation in Learning Environments to Digital Inclusion Based on Large-Scale Distance Education
%D 2014
%8 Apr.-June
%9 journal article
%A Silva, Aleksandra do Socorro da,
%A Brito, Silvana Rossy de,
%A Martins, Dalton Lopes,
%A Vijaykumar, Nandamudi Lankalapalli,
%A Rocha, Claudio Alex Jorge da,
%A Costa, João Crisóstomo Weyl Albuquerque,
%A Francês, Carlos Renato Lisboa,
%@affiliation
%@affiliation
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%B International Journal of Distance Education Technologies
%V 12
%N 2
%P 1-25
%K bayesian networks, digital inclusion, distance learning.
%X Evaluating and monitoring large-scale distance learning programs require different techniques, systems, and analysis methods. This work presents challenges in evaluating and monitoring digital inclusion training programs, considering the aspects inherent in large-scale distance training, and reports an approach based on network and distance learning. The paper has the following objectives: (i) apply algorithms to extract indicators from interaction networks, in a real scenario and consolidated training based on distance learning; (ii) apply algorithms to correlate interaction indicators with other indicators related to the use and participation in learning environments; and (iii) discuss the relevance of the obtained indicators to promote feedback with information critical to the success of a large-scale distance training program.
%@language en
%3 AleksandraSilvaEtAl_IJDET_Proof_Reading.pdf