Abstract:

This article aims to analyze a set of pedagogical practices that were introduced in 13 higher education institutions in Portugal and which constitute co-creation with the business environment and the training of students to create companies, promoting entrepreneurship, in an environment of Problem-based Learning. The implementation of these teaching-learning methodologies, with the aim of bringing academia and business closer together and increasing students' entrepreneurial skills, resulted from a project financed by European funds. The project, in the period between 2021 and 2023, was developed around 7 activities and the measurement of the project's success was done through 3 result indicators and 4 achievement indicators, both supported by KPIs with the respective metrics. For some indicators, the measurement values exceeded those set for the project and for others, the values achieved were below the objective established for the project. The aim is to carry out an efficiency analysis of the execution of the project, mainly based on the results that were expected to be achieved with this project. For this, a non-parametric method is used, Data Envelopment Analysis, which is a mathematical programming method. This analysis methodology is aimed at analyzing efficiency and in this specific case what is intended to be compared is the revealed efficiency with that supported by the initial metric for the result and achievement indicators. The aim is to know to what extent the project went well or, from an efficiency point of view, fell short of what would be expected depending on the resources applied. The conclusion reached is that for certain indicators, the results revealed the inability to obtain total technical efficiency. The fact that part of the project was carried out during the covid19 and post-pandemic period may be the reason for not being able to achieve the learning benefits that would have been expected for students.

Keywords:

Co-creation of innovation, entrepreneurship, Problem-based Learning Data Envelopment Analysis, Efficiency.