Neural Network Potential of Image Generation for Actualizing Cultural Codes in Foreign Language Teaching

The article investigates the didactic potential of neural networks for generating images in foreign language teaching, specifically in the context of Russian as a foreign language. It highlights the advantages of visualization in education, such as attracting students’ attention, boosting motivation, and facili- tating understanding of complex linguistic and cultural concepts. Special emphasis is placed on the utilization of neural networks Shedevrum, GigaChat, DALL-E 3, and Canva for creating educational materials enhancing student engagement, promoting critical thinking, and encouraging collaborative interaction. The study underscores the pivotal role of these adaptive technologies in personalizing learn- ing and refreshing the cultural codes of the target language. The cultural code con- cept, demonstrating the inseparability of communication, language and culture, is considered to be most important in the implementation of linguacultural approach to foreign language teaching. Key findings reveal that the creative deployment of neural networks or generative AI substantially enhances the effectiveness of foreign language instruction. Shedevrum, GigaChat, and DALL-E platforms offer better opportunities for creating visual materials suitable for educational purposes. The article concludes by advocating for the integration of generative AI in foreign language classrooms to enrich teaching practices and elevate student motivation. Future research directions include exploring strategies for optimally leveraging generative AI in educational contexts tailored to both teachers and learners.