Brazilian Higher Education Analysis Through Knowledge Discovery: Annual and Temporal Approaches

This project presents the Ph.D. thesis proposal in the Information Management area and aims to contextualize the scenario of Higher Education Institutions (HEIs) in Brazil, generate new knowledge and provide subsidies to justify the relevance of the problem investigated and its contributions. It explores the Brazilian Higher Education Census, from 2010 to 2015, and other official and public databases in order to generate new knowledge, based on the fact that knowledge is the main factor of social development in the Age of the Knowledge Society and Economy. It proposes to answer the following research question: "How does the annual and temporal analysis of the Brazilian Higher Education Census and other public and official databases generate new knowledge and provide strategic information to ensure the Higher Education Institutions mission’s accomplishment?" To achieve its objective, it adopts an inductive research process as a research strategy, divided into two phases: an exploratory study, followed by the knowledge generation phase. It is an interpretative, constructionist, and quantitative study. As a methodological resource, it uses the Self-Organizing Maps (SOM), a type of neural network that explores hidden patterns in a large volume of data. In this case, specifically, it is used to discover new knowledge in the area of higher education, considering the higher education institutions, their undergraduate courses, teachers, and students. Besides, and therefore, it assesses the internal dynamics of the higher education institutions and, according to the Resource-Based View (RBV) theory, presents a new approach to identify their internal resources - a gap in the current literature. The proposed approach contributes to fostering new forms of relationship, based on the combination of similar or complementary resources between and among the institutions, which will enable them to become more entrepreneurial and to behave more collaboratively. The research also contributes to 1) the adoption of an innovative methodology - SOM - for the area of Education, specifically Higher Education and a new typology for grouping the educational institutions, courses, teachers and students; 2) the advancement of the theory of RBV; 3) the area of Education, lacking quantitative studies; and 4) the extension of the concept of the entrepreneurial university – the enhanced triple helices, based on their complementary and similar resources. This new knowledge plays a significant role in the implementation of competitive responses or decisions to take in a fiercely competitive environment and contributes to the advancement of the theory under study. Keywords: knowledge discovery, higher education, Self-Organizing Maps - SOM, entrepreneurial university.