Implementing Generative AI and Large Language Models in Education

The recent advancements in Generative AI have been highlighted by the emergence of Large Language Models (LLMs) like ChatGPT. We track this evolution from the initial recurrent neural networks to the development of architectures like Transformers and Generative Pre-trained Transformers (GPT). ChatGPT, with its impressive ability to comprehend, process, and produce natural language, has piqued the interest of educators, students, and institutions within the education sector through its creation of high-quality textual responses.This marks the beginning of a new era in educational possibilities: we emphasize the beneficial effects of ChatGPT in learning environments, noting its utility in programming assistance, its clarity in concept explanation, and its role in enhancing automated learning processes. We also recognize potential drawbacks, including the risks of over-reliance, plagiarism, and the inherent constraints of these models in tackling mathematical and linguistic problem-solving tasks.In exploring the Paradox of Automation, we examine the implications of an over-reliance on AI in education. We seek to understand the importance of preserving critical thinking skills and ensuring that technology serves as a tool for augmenting human capabilities rather than supplanting them. Our analysis acknowledges that, while AI, including ChatGPT, can assist in content generation and problem-solving, it is essential for students to cultivate their abilities in analytical thinking, content verification, and error correction.