Russian Scientists Merge AI and Pedagogy to Reinvent Language Learning
Researchers at Moscow State University have developed an AI-driven method for teaching foreign languages that adapts to every learner. Early tests show the system outperforms classical instructional approaches.
Russian researchers are combining advanced pedagogical practices with neural-network capabilities to improve language learning. Moscow State University says the algorithm, already successfully tested, builds and reinforces a personalized vocabulary set for each student.
According to the university’s press office, the neural network helps define personalization criteria with greater precision. It first analyzes a student’s language proficiency level, interests, and speech patterns in their native language. Based on this data, a machine-learning model generates an individualized learning program. The experiment ran inside a chatbot, and results showed the method was more effective than traditional approaches.
Speech Training
After the initial testing phase, researchers created a virtual trainer where students interact with a chatbot in dialogue mode. The AI system uses open-source speech-recognition libraries and large language models to provide feedback in real time.
As noted by Anna Avramenko, associate professor at MSU’s Department of Linguistics and Information Technologies and head of the research project “Artificial Intelligence Technologies in the Digitalization of Education,” the new method represents “a synthesis of cutting-edge AI developments and proven pedagogical practices.”
