A Critical Look at the Promises of Large Language Models in Education

Large Language Models (LLMs) have sparked considerable excitement across various sectors, with education being a particularly prominent area of discussion. Proponents suggest that LLMs could revolutionize learning by personalizing instruction, automating assessment, and providing intelligent tutoring. This paper offers a critical examination of these promises, evaluating the potential benefits alongside the inherent risks and limitations of deploying LLMs in educational contexts. We discuss the current capabilities of LLMs relevant to education, such as content generation, summarization, and interactive dialogue, and explore their proposed applications. Concurrently, we highlight critical concerns including algorithmic bias, potential for plagiarism, impact on critical thinking skills, data privacy issues, and the need for robust ethical guidelines. Through a balanced analysis of current research and practical challenges, we argue for a nuanced approach to integrating LLMs into education, emphasizing the importance of human oversight, pedagogical soundness, and equitable access to technology.