AI, semiosis, and the future of language acquisition: A global approach to educational semiosphere
AI, semiosis, and the future of language acquisition: A global approach to educational semiosphere

Summary/Abstract: This study explores the role of artificial intelligence in second language (L2) acquisition and the tremendous opportunities that it creates for personalized learning. As the 2030 EU agenda for quality education suggests, the emphasis of research and practice with AI-based approaches should be to foster the learning process. For this reason, the theoretical aspect of this research examines how AI can be situated in the L2 context for promoting personalized learning experiences. The study, specifically, evaluates the effectiveness of the current role of AI in L2, critically reviewing its reflection on the ethical implication of AI in education using a semiotic anal ysis. The objective is to understand how AI adapts to students’ cognitive and individual needs to be used as a methodology in learning frameworks. Additionally, the research raises two questions which address the role of AI in Barthes’s (1977) author-reader approach, proposing a semiosis-based learning model adapted from Eco’s encyclopaedia (1976, 1984) and Lotman’s concept of semiosphere (1985). This model aims to ensure deeper personalized learning by reversing traditional pedagogic approaches and analysing the role of each element (student, teacher, text, and AI) inside the educational sphere. In conclusion, the study highlights how AI-driven tools can be integrated into L2 education, facilitating communication, content creation, and engagement with new topics in an inclusive manner. Artificial Intelligence, Second Language Acquisition, Semiotic Analysis, Semiosphere, Quality Education ysis. The objective is to understand how AI adapts to students’ cognitive and individual needs to be used as a methodology in learning frameworks. Additionally, the research raises two questions which address the role of AI in Barthes’s (1977) author-reader approach, proposing a semiosis-based learning model adapted from Eco’s encyclopaedia (1976, 1984) and Lotman’s concept of semiosphere (1985). This model aims to ensure deeper personalized learning by reversing traditional pedagogic approaches and analysing the role of each element (student, teacher, text, and AI) inside the educational sphere. In conclusion, the study highlights how AI-driven tools can be integrated into L2 education, facilitating communication, content creation, and engagement with new topics in an inclusive manner.

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