Background: Simulations are a useful resource for learning A-Level Physics. Part of my current research involves re-creating some original physics experiments from the 1920's - 30's where the apparatus no longer exists. This project is suitable for anyone who is considering entering the teaching profession, as a teacher of computing. You will work with teachers and/or A-Level physics students supported by a tutor from the Institute of Educaton. You will use the Unreal engine and write code in C++ using our Simulation Framework code base.

Aims: (i) To create a simulation of one or more physics experiments, (ii) To create associated learning resources, (iii) To evaluate these resources with students and/or teachers.

Objectives: This project could run as 'Action Research' where you iteratively design, build and test (evaluate with students and or teachers) your product.

Lit. Review: There is a huge amount of journal articles available. Many focus on physics simulation, others focus on the use of game engine technology in education.

Secondary Data: Other simulation resources.

Primary Data: Evaluation of your simulation and associated resources. This could be via a focus group, or via questionnaires.

Technology: Unreal-4 (lab machines) or Unreal-5 using our MAS22 softwareEv framework.

Ethical Approval: Requires enhanced Ethical Approval since this project involves collecting data from people.

The Internet of Things and Digital Twins are becoming hot industry topics. It would be great for us to build our capabilities in these fields, with a view to expanding our teaching and research options. A useful project would be to explore low cost (even free!) options to that would enable academic researchers and students to explore topics such as medium/long range wireless networks (such as LoRa), IoT system simulation, or Digital Twin development. 

ChatGPT has been in the news since it was released in November 2022. It has been the object of a lot of hype (a user-friendly combination of Google and Wikipedia; the ability to collate and draw conclusions from mountains of data) as well as disaster predictions (the end of traditional academic assignments).

But what can it do? And how do people see it? There are many questions that could be asked.

When given a complex prompt (more than just a request for factual information) ChatGPT will give a different response each time it is asked. Investigate the variations in response to the same prompt delivered repeatedly. Do the responses converge or diverge? You will need to generate several suitable prompts, and investigate the responses to each over an extended period of time.

Because it is designed to do nothing more than deliver plausible-sounding text, ChatGPT has (as yet) no concept of truth or factual accuracy. This means that it will sometimes produce factually inaccurate statements (‘hallucinations’) not derived from its training data (the Internet as at Summer 2021 – which probably contained more than a few inaccuracies, both accidental and deliberate). If these ‘hallucinations’ are uncritically added to the pool of (mis)information available to humanity, they will act like ‘fake news’ and pollute our data sources. How frequent are these hallucinations? Do they occur more frequently in some subject areas, and less frequently in others?

What do people think of ChatGPT? Does their opinion depend on age/gender/educational background…? Will it be a tool to make life easier? Or a threat to privacy? What evidence is there to support each of these two opposing positions, or any other position on ChatGPT?

Investigate how ChatGPT compares with Google Bard, Microsoft Bing (or any other easily available AI chatbot). On what sort of tasks do they perform differently, and how, and why? Are the differences significant/important? You may find it best to investigate and compare performance on a small number of tasks.

Background: Game and Simulation levels can get very large, it soon becomes laborious for the level designer to populate the level with assets, especially buildings in the Editor by hand. The process can be made hugely more efficient by creating buildings and towns procedurally, using code. This of course requires designing building elements (walls, floors) which seamlessly join together. Also, there must be a sufficient range of elements to create a number of different buildings, e.g., a block of apartments with different layouts and number of rooms.

Aims: (i) To develop a C++ framework to deploy with Unreal 4 or 5 to allow architects to rapidly design and create a building, an estate or even a city. (ii) To get an evaluation of the strengths and weaknesses of your framework using human participants.

Objectives: for you to decide but I would expect you to conduct a study of design principles for buildings, perhaps looking at floor-plans of buildings available from estate agents. Another ‘deliverable’ is full documentation allowing future level developers and researchers apply your framework (otherwise, what’s the point?)

Lit. Review: There are a number of journal articles available. Other valid source of information are Wikis. Blogs, GDCs and current (Unreal 4, Unreal 5) information about procedural buildings.

Secondary Data: Frameworks, algorithms and code developed by others.

Primary Data: Evaluation of your framework by yourself, using objective measures such as lines of code, code complexity, time saved by using a procedural approach

Research Questions: for you to decide but must be linked to your primary data collection.

Technology: Unreal-4 / 5

Ethical Approval: Straightforward since no human participants are involved.

You are using a system to store project suggestions from members of staff in a format that students can access, and so select themselves a final year project. Chris Bowers has put a lot of work into developing this system, but I'm sure there is room to make it even better. This project will involve finding out what improvements users would like to see, implementing as many as possible of them, and evaluating the outcome. It may involve developing a completely new system, or (with Chris Bowers' agreement) improving his system.