Artificial Intelligence in Teaching In-Depth Reading Strategies in a Foreign Language

The article considers an alternative method of teaching in-depth reading strategies in a foreign language using artificial intelligence technologies. Variants of analytical, analytical-synthetic tasks are proposed at three main stages: pre-text, text, and post-text. The objective of the study is to theoretically substantiate and describe the methodology of teaching in-depth reading strategies in a foreign language through the developed variants of analytical and analytical-synthetic tasks at three main stages of working with a text using AI tools. The theoretical and methodological basis of the study consists of the provisions of the communicative-cognitive (I. L. Bim) and personality-oriented (I. S. Yakimanskaya) approaches. The main methods of the study were: theoretical analysis of scientific and methodological literature on the problems of meaningful reading and the use of AI in education; methodological modeling – development of a typology of exercises and stages of working with a text using AI tools; The descriptive-analytical method is a generalization and systematization of the experience of using AI (DeepSeek, YandexArt, AliceAI LingQ) in teaching foreign languages, presented in the works of Russian and international authors (P. V. Sysoev, A. P. Avramenko, R. Thorburn, L. D’Argenio); the method of illustrative examples is a demonstration of specific ways to implement the proposed exercises using content generation in AI systems. This article proposes a typology of pedagogical strategies for teaching in-depth reading in a foreign language: information selection and immersive practical experience in the GenAI environment. Description of the author’s methodology. The developed methodology for teaching in-depth reading strategies using AI is based on three stages of working with text (pre-text, text, post-text), identified by N.N. Smetannikova, and is implemented through a system of analytical and analytical-synthetic exercises. The conclusion notes the need to take into account a number of factors in the process of interaction between students and teachers with AI tools: 1. the use of artificial intelligence exclusively as an additional methodological tool; 2. the use of artificial intelligence by students during classroom work no more than 10–15% of the lesson; 3. formulating accurate prompts to the AI chatbot to obtain more precise results.