DeepSeek as a tool for developing didactic materials based on literary texts

the article explores the potential of the DeepSeek neural network in the context of teaching English as a foreign language, using O. Henry's short story "The Cop and the Anthem". The scientific novelty of the research lies in the targeted application of artificial intelligence in the process of pedagogical lesson design aimed at studying classical literary works of the English-speaking country, developing vocabulary, speaking skills, and reading comprehension. The study verifies the didactic capabilities of artificial intelligence in solving tasks such as adapting literary works, organizing vocabulary work, and modelling post-reading tasks and exercises. The authors examine the content of the generated material in comparison with the original text; identify the strengths and weaknesses of the practical application of the neural network in reconstructing literary works in the English language. The potential of the neural network for systemizing vocabulary and constructing exercises for studying new lexis is considered; the diversity of post-reading tasks modelled by artificial intelligence is analyzed. The experiment allowed making the following conclusions: the practical application of DeepSeek tools for text adaptation requires careful supervision by the teacher; the neural network helps to automatize teacher's routine tasks in creating post-reading assignments. The relevance of the study is determined by the fact that the integration of artificial intelligence represents one of the dominant trends in the modern educational system. AI-based digital solutions demonstrate relative effectiveness in creating didactic materials. At the same time educators emphasize the need for a balanced and methodologically correct integration of artificial intelligence into teaching practice. The research material is O. Henry's short story "The Cop and the Anthem." The free DeepSeek neural network was selected as the experimental platform: the AI was asked to create an adapted version of the story while preserving its main plot lines, as well as modelling post-reading tasks and exercises for the generated text aimed at learning new vocabulary, checking reading comprehension, and developing communication skills. The research results can be useful for interacting with the DeepSeek neural network in the context of designing didactic materials in the English language intended for Russian students. The conducted research allows making the conclusion that the DeepSeek neural network is capable of modelling learning materials based on literary works in the English language, but requires additional verification of the adapted text's content and quality control of the proposed tasks and exercises.

neural network, DeepSeek, English language, adapted text, post-reading tasks, vocabulary