Description

The Erasmus+ project VETAssIst (Artificial Intelligence as VET Teacher Assistant), funded under the KA220-VET action, explores the integration of Artificial Intelligence (AI) as a support tool for teachers in Vocational Education and Training (VET). The project addresses the growing need for educators to adapt their teaching roles and practices in a context where AI is reshaping education systems worldwide.

The main objective of VETAssIst is to design, test, and implement AI tools that act as teaching assistants in VET classrooms. These tools are not meant to replace teachers, but to support them in tasks such as lesson planning, assessment, progress monitoring, and providing personalized learning opportunities to students. By doing so, the project contributes to a transformation of the teacher’s role from being primarily a content transmitter to becoming a facilitator, mentor, and mediator of the learning process.

Key activities of the project include:

• Mapping and evaluating available AI tools applicable to VET contexts.
• Developing guidelines for teachers on how to critically and ethically integrate AI into their practice, with attention to issues such as transparency, data privacy, and pedagogical relevance.
• Providing training modules for teachers to enhance their digital literacy and ability to effectively use AI tools in classrooms.
• Conducting pilot implementations in VET centers across partner countries to test the usability, benefits, and challenges of AI integration.

The project outputs include a comprehensive inventory of AI tools for VET, a set of good practice guidelines for teachers, and practical training resources to build educators’ competence in using AI. Moreover, lessons learned from pilot studies provide real-world evidence on the impact of AI on teaching practices, highlighting opportunities (such as personalization and workload reduction) as well as risks (algorithmic bias, over-dependence on technology, and ethical concerns).

VETAssIst is highly relevant as a case study for training modules aimed at educators, since it aligns with European frameworks such as EntreComp (competences related to self-awareness, self-efficacy, and learning through experience) and DigComp (information and data literacy). It offers an evidence-based approach to how AI can be embedded in vocational education while maintaining a human-centered perspective.

Through its results, VETAssIst demonstrates that AI can be a powerful ally for teachers when integrated critically and responsibly, supporting innovation in education without compromising the ethical and pedagogical principles that underpin quality teaching and learning.

Reference Link

https://vetassist.mpt.bme.hu/