Metodologia analítica inov-ativa: o uso da mineração de dados na avaliação do interesse do aluno e seus efeitos em um curso MOOC

Abstract

This study aims understanding how data mining, being an innovative analytical methodology, can be used to promote pedagogical strategies in order to minimize evasion and provide permanency on students enrolled in a MOOC (Massive Online Open Course), based on their initial interests. An observational case study is applied by adopting a qualitative methodological approach of an exploratory and descriptive nature to collect data and analyze the event under study of a MOOC course offered by UNA-SUS/UFMA, entitled: Health care for women with disabilities. A total of 289 applicants were analyzed during the course's 6- month offer. The results indicated that the engagement and behavior pattern of the course participants may be associated with their interests and introductory motives, as well as discussing the personalized strategic interventions that were carried out to promote performance in the formative trajectory. It is believed that the research will contribute to the re-signification of pedagogical strategies as well as offering new reflections regarding to evasion and statistical data that influence the success of a MOOC, as well as, in a socioeducational context.