Building teaching clusters by research interest: A method to assist the decision making in higher education courses

Abstract

This article reports the results of a multivariate analysis application and teaching clusters on the decision-making in the Production Engineering course at a Higher Education Institution. For this purpose, firstly, a conceptual review was carried out on the importance of teacher selection and their allocation in different teaching activities, such as examining boards, orientations and lectures. Subsequently, the objective of the present study was to apply clustering tools, which are widely used in manufacturing environments, in an educational context, presenting a method of clustering for teachers by research topics, as well as the practical results of the application of this method in a course of Production Engineering. Finally, some evaluations and considerations are presented in order to contribute to the management of higher education courses, as well as to stimulate and broaden the conceptual basis for applying this approach in educational institutions.

Keywords:
Multivariate Analysis; Clustering; Similarity Coefficient; Teacher Selection