STRATEGY AND IMPLEMENTATION PLAN
The AIM@VET project has the main goal of developing teaching units about AI for VET, in a similar way as in the AI+ project. The current proposal faces two main issues of AI training found during the AI+ development.
First, it is necessary to provide support to teachers to train students in AI properly. Considering that AI education is an emergent teaching discipline at pre-university level, it would take many years to have a fully trained group of teachers to confidently teach AI in their practice. In the meantime, current generations of students cannot be left out of AI education, so a solution that provide support to pre-university teachers in the short-term must be developed. To face this issue, in the current project, the VET teachers will be placed in the center of the teaching units’ design and implementation.
A second conclusion gained at the AI+ project, is that it is important to concentrate the learning resources in specific AI topics, because students require time to properly understand AI concepts, which are completely novel for them. Covering a broader spectrum of AI topics but with less depth is even worse in VET education, where students require a targeted training with direct application in the market. Consequently, the project presented here will be focused just on 3 key application areas of AI: computer vision, robotics, and ambient intelligence. Formal training in these topics will open VET students with new opportunities for the labor market in many sectors, like Industry 5.0, Smart Environments, Autonomous Vehicles, and others.
The project partnership of AIM@VET is made up of six teams from three different European countries: Spain, Slovenia and Portugal. It consists of a balanced group of AI experts from three universities and education experts from three VET schools. The development of the learning modules will be led by AI experts from universities and tested by VET teachers and students, organized through “work islands” (WI). Each island includes one university and one VET school from the same country, and it is focused on one key application area of AI. The Slovenian work island will focus on computer vision, the Spanish one on robotics, and the Portuguese one on ambient intelligence.
The three work islands will develop and test a predefined number of teaching units during each academic course from 2023 to 2025. At the end of each, they will connect in training activities (TA) where the teaching units will be tested with mixed groups of students from the three VET schools. A key feature of the strategy is the liaison between the work islands, which will be fostered to ensure collaboration and linkages between the partners involved in the development and implementation of the teaching units. To this end, in addition to the TA, periodical transnational meetings (TM) have been included to agree functional and organizational aspects. This collaboration will be critical in ensuring that the teaching materials’ development and test are done in a homogeneous fashion. The goal is leading to the reliability and soundness of the learning modules, with global considerations that go beyond the specific students in each island. Finally, it must be pointed out that each island will be responsible of the dissemination of the project results towards the educational community by means of specific Mutiplier Events (ME), and through their presence in social media.
As it can be observed, the proposed strategy for the curriculum development aims to ensure the feasibility and applicability of the learning modules. To this end, their design is carried out with the support and feedback of VET teachers as a core feature, so they are not simple adaptations of university materials created by University experts, but specific resources created for this educational level.
