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The book presents a model for mapping signs of mediation in virtual teaching-learning environments - VLEA. The model aims to support the pedagogical mediation process for teachers who carry out activities linked to Distance Education, with the aim of reducing their workload in identifying and monitoring the evolution of the mediations carried out in the environment. To this end, text mining techniques using Bayesian inference mechanisms were used to identify mediation categories based on interactions between participants in a distance learning course. The system was validated and the results…mehr

Produktbeschreibung
The book presents a model for mapping signs of mediation in virtual teaching-learning environments - VLEA. The model aims to support the pedagogical mediation process for teachers who carry out activities linked to Distance Education, with the aim of reducing their workload in identifying and monitoring the evolution of the mediations carried out in the environment. To this end, text mining techniques using Bayesian inference mechanisms were used to identify mediation categories based on interactions between participants in a distance learning course. The system was validated and the results evaluated using a case study. After mapping the interactions and identifying the students' mediation categories, graphs and reports were generated with information on the mediation process. The categories helped to identify the levels of mediation. The results show that the use of technology made it possible to identify the levels of mediation needed by the students in the online course.
Autorenporträt
Doktor in Informatik im Bildungswesen an der UFRGS, Master in Informatik an der UFRGS, Diplom in Informatik an der UERGS und Bachelor in Informatik an der URCAMP. Dozentin an der IFSul, tätig in den technologischen Grundkursen in Informatik, in der Spezialisierung auf Bildung und im Masterstudiengang für berufliche und technologische Bildung.