Neurodidactics of teaching foreign languages

Topic 1. Neurolinguodidactics as an interdisciplinary field in linguodidactics: object and subject of research, psychological and pedagogical theories; neurolinguodidactic teaching principles; multimodality as the key didactic feature of solutions based on large language models.

Topic 2. Didactic potential of large language models (BERT, GPT‑4, Gemini), NLP‑based solutions, and text‑to‑speech technologies in foreign language (FL) teaching; typology of AI‑based solutions used in FL teaching; types of intelligent learning models in language education: digital tutor, intelligent learning systems, automated monitoring and assessment systems, research environments, dialogue systems, immersive metaverses.

Topic 3. Basic psychological, pedagogical, neuropsychological, linguistic, and didactic principles for developing multimodal intelligent learning models: from non‑linear tests based on LLMs to multimodal intelligent learning systems. AI technologies for didactic processing and analysis of corpora and concordances, and for developing educational materials for language courses (Google Colab, Yandex DataSphere, DeepPavlov Library).

Topic 4. Pedagogical, psychological, and methodological problems and consequences of using AI in foreign language teaching. Development of didactic materials using AI and copyright issues. The impact of AI on university curricula. Designing course programs and lesson plans with the help of AI (Educational Genius; Swotknot; Learnt): advantages and disadvantages.

Midterm assessment

Topic 5. Interactive methods for teaching a foreign language and neurolinguodidactic principles for developing interactive materials to build skills in discussion and debate in a foreign language. Methodological principles for developing didactic voice agents based on AI to develop interaction skills. Analysis of international and domestic experience: MICROSOFT (https://idebate.net/resources/debatabase), SpeakMate, CommonVoice Mozilla (https://commonvoice.mozilla.org/), LJ Dataset Speech (https://keithito.com/LJ-Speech-Dataset/), Stellar AI (https://www.stellarapp.io/), Elevenlabs AI Dubbing.

Topic 6. Game‑based methods for teaching a foreign language and neurolinguodidactic gamification techniques. The quest as a game technology for developing students’ analytical and creative skills. Principles for designing a meta‑quest for learning in immersive environments and metaverses using Universal Data Generator, Perplexity, Notion AI. Analysis of international and domestic experience (ImmerseMe, ALTSpace, Mondly).

Topic 7. Problem‑oriented and project‑based methods for teaching a foreign language to develop students’ professional and universal skills. Neurolinguodidactic principles for designing project tasks and cases for research environments using Perplexity, Cohesive (https://cohesive.so/), AI‑Assist (https://ai-assist.eu/), Notion AI, Universal Data Generator.

Topic 8. Designing an interactive lecture and a digital tutor based on a Telegram bot for feedback, reflection, and creating a glossary of key concepts and terms in the discipline. Designing a flipped classroom model using AI technologies (Teachology). Developing video and graphic materials for lectures using Murf, Synthesia, Gamma, Simple Show Maker, Lexica, Gamma, Kandinsky, DALL‑E 3. Analysis of domestic experience at Tomsk State University (Tomsk, Russia).

Topic 9. Designing a metacognitive scaffolding model for intelligent learning systems: ongoing, interim, and formative assessment, reflection, and feedback. Implementing peer and self‑assessment using AI (Essay Grader, Write and Improve, AcademicGPT, OpenEssayist). Analysis of domestic (HSE) and international experience (IBM, Pearson).