A satisfação dos alunos de educação a distância da Universidade Federal de Santa Maria

Abstract

The institutions of Superior Education in Brazil, from a public policy of incentives for Distance Education (DE), along with the facilities provided by the Information Communication Technologies (ICT), has made significant investments in this type of education. Even if the interests of each university may be different, the individual benefits of the teaching-learning and the returns to society justify the infrastructure improvements for the demands attendance of the process. In this sense, the study relates specific issues to analyze which are the variables that influence the satisfaction of students linked to DE courses at graduation and post-graduation levels. Based on the literature, it has been adapted a model that defines dimensions, constructs and variables for analysis. The dimensions considered are: Perceived Satisfaction of Distance Education (dependent variables), and Student dimensions (independent variables), Teacher / Tutor, Course, Technology, Environment Course and Teaching Model. The participants were all students of graduation and post-graduation distance system of the Open University of Brazil, at the Federal University of Santa Maria, located in the state of Rio Grande do Sul, Brazil. For the analysis of data and in order to reduce uncorrelated variables, it was initially used the method of factor analysis and Pearson correlation. Seeking for the prediction of a variable on the other to explain the relationship between dependent and independent variables of the model - as well as validation of the model used, we used multiple regression. In relation to confirmation of the model, the results of multiple regression revealed four variables as predictors of DE student satisfaction: Flexibility and Quality of the Course belonged to the Course dimension and the Perceived Usefulness and Perceived Ease variables belonging to Teaching Model dimension. The constructs, Course Quality, Flexibility Course, Perceived Usefulness and Perceived Ease of Use (predictors / independent model), explaining 40.6% of the variance. With this result, we conclude about the efficiency of the model and the satisfaction of students in distance education. In addition, it established a relationship with the infrastructure Virtual Teaching- Learning Environment regarding the flexibility and ease of studying on graduation or postgraduation degrees and this mode of teaching, as well as with regard to the quality and usefulness of the courses.