Estimating the Impact of Automation on Vocational Education: The Case of Technical Courses

Abstract

The present article proposes a methodology that uses Artificial Intelligence to analyze how automation affects technical courses and presents a case study that evaluates the technical courses offered by Senac from the perspective of the impact of state-of-the-art automation in seven categories of technologies. The research reveals that 39.1% of the Course Competence Indicators of the institution are at a Medium automation level, this being the most representative level. Digital Platforms and Applications emerge as the most relevant technology category, while 3D/4D Modeling/Printing is the least significant. The research presented here suggests the recurrent and lasting adaptation of the National Curricular Plans of the institution in accordance with the emergence of new technologies as well as the development of courses focused on emerging technologies, preparing students for a job market in constant and rapid change.