The Use of Large Language Models in Language Learning and Assessment

The advent of large language models (LLMs) has revolutionized the fields of natural language processing (NLP) and artificial intelligence (AI), with significant implications for language learning and assessment. This paper explores the deployment of LLMs in the educational technology sector, particularly focusing on their application in language learning contexts. We examine how LLMs, such as Open AI’s GPT-۴ and other alternatives, can be harnessed for content creation, automated assessment, and personalized feedback, thereby offering innovative solutions to enhance language education. Furthermore, we discuss the potential societal and ethical implications surrounding the use of LLMs, including biases, data privacy concerns, and the risk of oversimplifying educational challenges. By analyzing current applications and identifying future directions for research and development, this paper contributes to a nuanced understanding of how LLMs can transform language learning while ensuring ethical considerations are prioritized in their implementation.

Keywords:

large language models , education technology , natural language processing , text generation , automated assessment