The International Conference on Smart Technology and Education (STE2026) took place in Brașov, Romania from 11th to 13th March 2026. STE2026 continues the tradition of the former REV Conferences and serves as the annual meeting of the International Association of Online Engineering (IAOE) in cooperation with the Edunet World Association (EWA) and the International Education Network (EduNet). The conference brings together engineers, researchers, and education specialists to discuss emerging trends in technology‑enhanced learning and innovative engineering education.
During the event, Galyna Tabunshchyk presented the paper “AI Driving Education in Model‑Based Systems Engineering” (G. Tabunshchyk, P. Arras et al.). The contribution explores how Retrieval‑Augmented Generation (RAG) can be applied to extract relevant information from large collections of unstructured technical documents.
In many engineering environments (especially those involving prototype machinery or experimental PhD setups) essential information is scattered across various scientific articles, research papers, manuals, datasheets, notes, and other independent sources. Users typically need to navigate all of these documents manually to understand how to operate a system. The proposed RAG‑based approach streamlines this process by creating avirtual user manual that consolidates the necessary knowledge automatically.
This method enables users to access the operational information they need more quickly and efficiently, supporting faster onboarding and smoother engagement with complex experimental setups used in assignments, laboratory work, and project‑based learning.
