Another innovative use case at ROVIT focuses on the simulation of teachers and students through AI-driven virtual agents. The goal is to create realistic, interactive educational environments where different teaching methodologies and learning strategies can be tested safely and efficiently. By simulating diverse learner profiles —including variations in motivation, prior knowledge, and cognitive styles— researchers can evaluate how different instructional approaches perform in various contexts before applying them in real classrooms.

These AI-based simulations also enable the study and enhancement of feedback mechanisms: virtual teachers can adapt their explanations and responses based on the simulated student’s behavior, while virtual learners can provide insights into engagement and comprehension. Ultimately, this use case contributes to the continuous improvement of educational methodologies, allowing for data-driven decisions in pedagogy design and providing a foundation for personalized learning and intelligent tutoring systems.