Innovation in Language Learning
AI-Driven Approaches to L2 Learning: Technology Applications and Perspectives
Simone Filippetti, Università per Stranieri di Perugia (Italy)
Talia Sbardella, University for Foreigners of Perugia (Italy)
Giorgia Montanucci, University for Foreigners of Perugia (Italy)
Abstract
This paper investigates the impact of AI-powered interactive scenarios on Italian language acquisition. By simulating real-life conversations and providing instant feedback, AI-driven tools create an immersive and adaptive learning environment. Current research suggests that these technologies can effectively enhance learners’ proficiency and foster engagement and motivation, offering a personalized learning path tailored to individual needs and learning styles. Essential elements include Natural Language Processing (NLP) for facilitating diverse and contextually relevant interactions, and machine learning algorithms for continuously adapting the learning experience based on learner performance and progress. Additionally, AI-driven analytics can provide valuable insights into learner behaviors and outcomes, enabling more targeted instructional strategies. The contribution explores recent advancements in AI applications for online language learning and presents case studies showcasing their successful implementation in educational settings, highlighting the transformative potential of AI in language education.
Keywords: ICALL, NLP, AI-supported language learning
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