Project Abstract

Addressing the critical need for efficient digital support in educational institutions, this project explores the integration of chatbot technology to enhance Swansea University’s IT helpline. Prompted by the increasing demand for accessible and precise IT support, this initiative pioneers the use of automated systems, aiming to elevate service delivery and the educational experience. The project uniquely navigates the challenge of developing effective chatbots with limited annotated datasets, a common hurdle in educational settings. The core objective is to craft and implement a chatbot that seamlessly handles a broad spectrum of IT queries, thereby streamlining the resolution process and optimizing resource allocation.Employing a robust, iterative methodology, the study utilizes historical IT service interactions to develop two models: a rule-based system for structured query resolution and a neural network-based model designed for dynamic response generation. This dual-model approach facilitates a comparative analysis to discern the most efficient strategy for chatbot integration within the IT support framework. Preliminary analyses suggest distinct advantages in both models: the rule-based chatbot is expected to excel in addressing predefined queries with high accuracy, while the neural network model shows promise in adapting to complex and varied inquiries, indicating a significant stride towards creating a more intuitive and engaging user interface.This research underscores the potential of chatbot technology not only in alleviating the current demands on IT helplines but also in redefining the scope of digital support services in academia. By highlighting the comparative strengths and adaptabilities of different chatbot models, the project contributes novel insights into the strategic deployment of chatbots, thereby enriching the dialogue on enhancing educational support mechanisms through technological innovation.

Keywords: Machine Learning, Text Analysis, Human Computer Interaction, Artificial Intelligence

 Conference Details

Session: Presentation Stream 6 at Presentation Slot 9

Location: GH014 at Tuesday 7th 13:30 – 17:00

Markers: Jay Morgan, Trang Doan

Course: MSc Computer Science, Masters PG

Future Plans: I’m looking for work