Abstract

Purpose – The internship is an activity that must be carried out in a real work environment by Industrial Engineering students as a requirement for obtaining the degree. The internship programs, in turn, are entities that mediate the processes related to intern student’s admission, achievement and evaluation. The aim of this article is to propose a model to evaluate internship programs in Industrial Engineering courses. Design/methodology/approach – Scientific mapping methods and multicriteria decision-making methods were used. Fuzzy DEMATEL was applied to a group of experts to determine criteria weights, by cause-and-effect evaluation. Subsequently, based on a survey with Industrial Engineering students from Brazilian universities, Fuzzy VIKOR was used to classify and evaluate internship programs. Findings – Using bibliographic techniques and analysis of social networks, it was possible to identify the main criteria related to internship quality: the student's technical learning; student employability; development of student interpersonal skills; dealings with social issues; the themes developed during the internship; and the internship model and student experience. The model proved to be useful both for comparing different programs, from different universities, as for comparing the evolution of a single program over time. Research, practical & social implications – The proposed model promises to enhance the quality of internship programs, enabling objective comparisons between institutions and inspiring innovations. The success of multicriteria methods advances knowledge in internship management, highlighting the social relevance of the research in addressing issues such as gender inequality, contributing to equity in a practical and replicable manner. Originality/value – Besides the unprecedented proposal of using multicriteria decision making to evaluate internship programs, the bibliographic survey brings original issues on the theme as genre equality and discrimination. Keywords - Internship; Engineering Education; Industrial Engineering; Higher Education; Multi-Criteria Decision-Making Methods.

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