Recent advances in Natural Language Processing (NLP), especially the introduction of ChatGPT, have the potential to revolutionise the education sector. However, the effective use of these technologies in university education requires careful consideration and systematic exploration. This project is aimed at exploring the application of NLP and generative pretrained transformer based models (GPTs) to enhance student experience in higher education. The project will focus on two main areas: using GPTs to provide personalised feedback to students and assist teachers in designing better course content and assessments, and using GPTs or similar models to analyse student feedback to extract actionable intelligence. The final part of the project will involve linking these two strategies to create a seamless experience.
While the opportunities for the use of generative models is tremendous, there are some important hurdles that must first be overcome. The biggest of these is the tendency of generative models to “hallucinate”. Hallucination is the phenomenon whereby GPTs generate text that is not aligned with reality. Given the potential negative impact of such errors in higher education, it is essential to implement rigorous methods that will guide GPTs to adhere to factual, pertinent and most importantly, unbiased information when generating output. Therefore, careful design of such methods including the use of explanation methods to ensure transparency is critical to ensuring the reliability and accuracy of generative models for use in higher education. A careful analysis of the ethics associated with the use of these models will also be within the purview of this project.
This project presents a distinctive opportunity for an individual to make dual contributions to the fields of computer science and education. By developing an innovative and advanced approach to enhancing teaching and feedback, the candidate can play a pivotal role in driving progress in both domains. Importantly, the candidate will have the opportunity to test and deploy their methods at the university in collaboration with the teaching and learning team.
The project will be carried out as part of an interdisciplinary integrated PhD in the UKRI Centre for Doctoral Training in Accountable, Responsible and Transparent AI (ART-AI). The ART-AI CDT aims at producing interdisciplinary graduates who can act as leaders and innovators with the knowledge to make the right decisions on what is possible, what is desirable, and how AI can be ethically, safely and effectively deployed. We value people from different life experiences with a passion for research. The CDT's mission is to graduate diverse specialists with perspectives who can go out in the world and make a difference.
Candidates should normally have a good first degree or a Master’s degree in computer science, maths, a related discipline, or equivalent industrial experience. Good programming skills are essential. A strong mathematical background and previous machine learning experience are highly desirable. Familiarity with bash, linux and using GPUs for high performance computing is a plus.
Formal applications should include a research proposal and be made via the University of Bath’s online application form. Enquiries about the application process should be sent to [Email Address Removed]. Informal enquiries are strongly encouraged and should be directed to Dr Harish Tayyar Madabushi ([Email Address Removed]).
Start date: 2 October 2023.
Continue with Facebook
