DDAAV - detector do desempenho do aluno em AVAs

Abstract

The virtual learning environments (VLEs) are benefited with advances in the use of technologies in education, enabling a more dynamic and meaningful learning. In the face of increased interaction in these environments, greatly increases the amount of data stored. The process of knowledge discovery in database (KDDKnowledge Discovery in Databases) has been used successfully in several areas and in the academic area some results have been used to assist the teachers. This dissertation describes a survey conducted with the steps of KDD, which utilizes the WEKA tool (free data mining software), specifically the J48 algorithm, to apply data mining techniques on the information stored in the database, in order to detect the student performance while running the course. The research scenario was constructed with data from assessments of introduction to media in education, Integration of the specialization course in Media in education, composed of 134 (one hundred and thirty-four) students, distributed in 5 (five) different poles. In this way, with the results obtained in the research, noted that the application of rules of the algorithm, can be a valuable instrument to professor during the execution of the course, and not only a posteriori, because it allows a positive immediate intervention of even in several variables that impact on the success of the apprentice, as type of material, discussions, activities, methodologies and strategies.