Förster, FelixFelixFörsterIbrahim, JaffarJaffarIbrahimMaack, AlexanderAlexanderMaackLandwehr, JulianeJulianeLandwehrKaiser, LydiaLydiaKaiserBursac, NikolaNikolaBursac2026-07-032026-07-032026-0719th International Design Conference, DESIGN 2026https://hdl.handle.net/11420/63796Learning MBSE is hindered by abstraction and complex tools. This paper identifies barriers via literature review and interviews to design a RAG-based chatbot acting as a “smart view” for contextual guidance. Evaluated through a semester-long field study and a controlled experiment, the prototype shows high usability and reduces cognitive load. While performance is comparable to traditional e-books, the RAG-enabled system effectively mitigates entry-level barriers and aids authentic project work through stepwise tutoring, offering a scalable, interactive complement to MBSE education.en2732-527XProceedings of the Design Society202629412950Cambridge University Press (CUP)https://creativecommons.org/licenses/by-nc-nd/4.0/model-based systems engineering (MBSE)artificial intelligence (AI)engineering educationlarge language model (LLM)systems engineering (SE)Social Sciences::371: Teachers, Methods, and Discipline::371.3: Methods of instruction and studyDrivers and barriers of learning MBSE: design and validation of a RAG-based AI chatbot leveraging smart viewsConference Paper10.1017/pds.2026.1065210.15480/882.17419