Employing online social networks to monitor and evaluate training of digital inclusion agents

This work presents challenges in evaluating and monitoring digital inclusion training programs, considering the aspects inherent in large-scale training, and report the main challenges in an approach based on network learning. For this, our goals are as follows: develop an architecture to provide all interface features with communication tools, data collection, automatic notification (alerts) of interest to those involved in training and proposal, and survey analyses; employ algorithms to measure the centrality, prestige, and density of interactions in a real case and consolidated training based on learning network; employ algorithms to correlate and measure, in probabilistic terms, the effects of participation in the interaction tools and the use of the resources and activities proposed; and improve a large-scale training program from the implementation of monitoring and tracking services offered in the architecture.