LLM-Based Chatbots in Language Learning
DOI:
https://doi.org/10.26417/919pei96zKeywords:
artificial intelligence, iCALL, personalized language learning, LLM, large language models, natural language processing, machine learning, chatbots, educational technology. adaptive learning, language learningAbstract
Efforts to utilize AI in education, and especially in language education, have their roots in the 60s with the appearance of the first rule-based systems. However, recent advances in Artificial Intelligence (AI) and more specifically the introduction of ChatGPT, have given a new perspective to language learning. The integration of AI, natural language processing, and Machine Learning has enabled adaptive learning environments tailored to individual learners' needs and led to a new generation of advanced tutoring systems and chatbots, able to offer personalized and customizable learning experiences to enhance language learning by increasing learner autonomy, engagement, motivation, and effectiveness. At the same time, research on Large Language Models revolutionized chatbot capabilities, making them integral tools in language learning. Commercial language learning online platforms experienced similar advancements, incorporating AI tools that offer enhanced possibilities for personalized language learning (PLL). This paper examines how the introduction of Large Language Models (LLM) and conversational AI has revolutionized the capabilities of chatbots, introducing the transformative potential of AI technologies to language learning and enabling them to enhance learning experiences, to increase engagement and improve their language proficiency. It also presents the existing specialized online language learning platforms and analyzes the areas in which artificial intelligence tools are currently used in language teaching and the benefits they have brought to users. The paper also discusses the problems, challenges and implications related to LLMs, such as ethical issues, potential biases and privacy concerns that need to be addressed, as well as the areas in which future research must focus, such as the pedagocical exploitation of AI tools and the most effective ways, strategies and pedagogical approaches and methodologies to blend AI-driven learning with traditional instruction, so that the use of artificial intelligence in language education becomes beneficial.Downloads
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2024-06-24
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