This research article explores the adoption of elaborate generative chatting systems in the development of educational chatbots which are intended to enhance learning experiences and student interaction. The article is aimed at tracing the process from the outdated rule-based approaches to cutting-edge generative models which encompass GPT, BERT, as well as Transformers. The article concentrates on chatbots used as a part of education management context today and reveals their application, functionalities, and unrealized potentials. The objective is to analyze what can be achieved with such advanced systems, consider if they are proper for learning and teaching environments and identify the challenges and possibilities arising from their adoption. A methodology is used covering a systematised literature review, including search methods, selection criteria, and studies analysis of the relevant studies. The key finding illustrates the impact of highly intelligent dialogue systems on students’ learning through personalization, technology-aided instruction, and active conversation with the students. Challenges imply computational resource demand, data privacy issues, and potential bias in algorithms. In their recommendations, the authors insist that ethics in AI, personalized learning techniques, and metacognition as well as working in groups are the key elements. As future directions, it includes an article on the framework that comprises AI models, specific education domains and longitudinal studies to find out whether AI drives educational technologies have long term effects on students. Dealing with them will push the boundaries of chatbot capabilities and create a responsible introduction to AI.
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