ChatEd: A Chatbot Leveraging ChatGPT for an Enhanced Learning Experience in Higher Education

TL;DR

This paper presents ChatEd, an innovative chatbot architecture that combines ChatGPT with traditional retrieval methods to improve personalized student support in higher education, addressing challenges of accuracy and bias.

Contribution

It introduces a novel hybrid architecture integrating ChatGPT with retrieval-based methods for educational chatbots, demonstrating improved support in higher education.

Findings

Empirical evaluations show high promise of the hybrid approach.

The architecture effectively reduces incorrect or biased responses.

Enhanced student engagement and support observed in tests.

Abstract

With the rapid evolution of Natural Language Processing (NLP), Large Language Models (LLMs) like ChatGPT have emerged as powerful tools capable of transforming various sectors. Their vast knowledge base and dynamic interaction capabilities represent significant potential in improving education by operating as a personalized assistant. However, the possibility of generating incorrect, biased, or unhelpful answers are a key challenge to resolve when deploying LLMs in an education context. This work introduces an innovative architecture that combines the strengths of ChatGPT with a traditional information retrieval based chatbot framework to offer enhanced student support in higher education. Our empirical evaluations underscore the high promise of this approach.