On the one hand it is impossible to underestimate the influence of generative artificial intelligence(AI) tools on the educational process. Students and learners by nature will always try to use techniques to limit their efforts to reach a goal. So educators are facing the problem of modifying the pedagogical approaches, so that they could include implementation of AI tools in an ethic way, helping student to reach learning outcomes.

On the other hand, project based learning (PBL) is a well-known didactic format in engineering education as it allows to provide students a reality based project environment. PBL is a student-centered model of teaching and learning by doing (student)projects. Projects are to be understood as complex tasks, based on challenging questions or problems. Projects typically run from 2 weeks to one semester. It involves learners collaboratively, in planning, problem solving, decision making and/or research activities. Students acquire autonomy and responsibility, develop overarching skills and apply knowledge. At the end of the projects students report and/or present their results. Combining the positive outcomes of the use of AI with well-defined project cases, will augment the learning experience, without suffering from the loss of original work for the students.

In the work authors research the possibilities of the retrieval augmented generation for the implementation in project based learning approach for the model based system engineering. This allows to increase the field of application of the existing equipment COCO and improve students motivation.