PROJECT IN PEOPLE-CENTRED AI (ONLINE) - 2025/6

Module Overview

This is an individual student project module giving each masters student an opportunity to explore in depth a problem in the field of people-centred AI. Each student will carry out a project in a selected area pertaining either to AI technology or its applications to a particular domain. The module provides a framework as well as a vehicle for exercising key aspects of project work such as literature and technology research, project planning, research methods, problem solving, design and implementation, performance assessment, and project evaluation. It also provides a scope for gaining transferable skills such as planning, time management, reporting, etc. The project can be either of a technical nature, focusing on the development of core AI technology, or be concerned with the application of AI in a particular domain, with consideration of the implications and benefits for people. This module is complementary to other taught modules in order to apply the learning gained into undertaking an independent piece of research and/or development. The project is unsupervised, i.e. you will not be assigned a supervisor. Instead, regularly online workshops will be organized to support students and answer specific questions as they arise.

Module provider

SOL - Computer Science and Elec Eng

Module Leader

GUILLEMAUT Jean-Yves (CS & EE)

Number of Credits: 30

ECTS Credits: 15

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Module Availability

Crosses academic years

Prerequisites / Co-requisites

None

Module content

The project forms an integral and important part of the MSc online programme. It is intended to occupy some 300 hours spread over the second year of study. Each student will carry out a project relating to either AI technology (e.g. building on aspects from the Fundamentals of Machine Learning or Applied Machine Learning modules) or its applications to a particular domain (e.g. building on aspects from the Topics in People-Centred AI or Law, AI and Technology modules).
Each offered project will be closely aligned with the scope of one of the taught modules (which ideally will have been taken by the student during their first year of study), which will provide a foundation for the research undertaken. The project will therefore provide an opportunity to extend knowledge in that module and develop considerable expertise in a specific area of People-Centred AI. The project will be primarily self-driven, but regular online workshop will be run by teaching fellows throughout the project duration to support students and answer specific questions as they arise. The project will be conducted in parallel with other modules.

Assessment pattern

Alternative Assessment

None

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate the following:

• Command of the subject and its impact on the world including societal implications of AI.


• Subject specific skills and practices.


• Scholarly and professional skills and attitudes that demonstrate a lead into employability.


• Commitment to developing lifelong continuing professional development (CPD).


• Ability to communicate findings of work carried out.

Thus, the summative assessment for this module consists of:

• A ‘Final Report’ worth 100% providing a comprehensive description and analysis of the research conducted over the course of the entire project.

Formative assessment and feedback:
Students will primarily receive formative assessment/feedback during regular online workshops with a teaching fellow experienced in the subject. The student will also complete a training needs analysis which will help them in understanding specific training requirements for their project. At the initial stage of the project, students will submit a short first report which will be an important mechanism to agree on a project plan and establish clear objectives. At an interim stage of the project they will complete an interim review form, which will detail progress to date and will provide an opportunity to receive feedback from a teaching fellow on progress and evaluate if it is satisfactory to date with advice on what to achieve. These will all be beneficial to the students in helping them gauge progress against the objectives and inform the next stages of their research at important checkpoints in the project timeline.

Module aims

• To provide an in-depth understanding of, and experience of, research and development, within the field of people-centred AI.
• To apply theoretical principles and research methods to a specific problem.
• To provide an opportunity for the student to plan and tackle an extended masters-level research and/or development problem, and to gain experience of the process of doing this, including experience in having to work independently on project-related activities, and experience of needing to produce a report.
• The module also aims to provide opportunities for students to learn about the Surrey Pillars listed below.

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to allow students to achieve the specified learning outcomes by means of study and research & development work. The project will be run in a self-driven manner, with regular workshops providing an opportunity to clarify their understanding and answer questions as they arise. In this way, a student can gain experience in applying knowledge achieved during academic studies to particular theoretical or practical problems. As part of this process, the student will need to critically evaluate the relevant literature, marshal ideas for research evaluation, and produce a reliable and coherent report. The experience of the intense project completion will demonstrate a wide range of professional skills that contribute to students’ employability as well as their resourcefulness and resilience. The practical element will involve either the coding of software or the processing/analysis of data to form and document results that will utilise crucial digital capabilities of the student.
The learning and teaching methods include the following:

• Introductory captured content and guided learning materials.


• Training needs analysis undertaken by the student at the outset when starting a project and completing a project plan.


• Student-centred information retrieval from the current state of the art literature.


• Research by the student on hardware, software, information or science, as relevant to the nature of the project.


• Regular online Q&A workshops to support independent learning.


• Experience of the project-management process.


• Experience of preparing a written project report.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: EEEM080

Other information

We are committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:
Sustainability:  One or more of the 17 of the United Nation’s goals of sustainability could be met by the specific project set. The extend to which the goals are supported will depend on the extent of the uses of the outcomes of the work. Students will be encouraged to identify where these benefits lie in their chosen topic.
Global and cultural intelligence: Students will take on a body of work for their project report and to meet the objectives successfully, they will develop independently some contribution to knowledge. High quality results may have the potential to contributed to a publication, patent or report that would benefit the wider community while substantially enhancing the student’s track record. Such outputs will have the potential for global impact as will be accessible on such a scale.
Digital capabilities: Dependent on the project it will in the majority of cases include skills in programming and/or processing of data to generate meaningful results and present them in a dissertation. Furthermore, the report will be written electronically and will require competent use of a word processor or LaTeX compiler to neatly and clearly present a body of work as an academic document. Other skills in use of spreadsheets and data files would be likewise required to assist documentation.
Employability: The ability to take on a body of work as well as independently produce and analyse a set of results are all crucial to the employability that a student will develop throughout the course of completing a dissertation.
Resourcefulness and resilience: To complete 300 hours of work within an intensive degree programme alongside other work in taught modules will demonstrate a level of resilience that has exhibited the ability to handle substantial pressure. The need to draw information and knowledge from many sources, develop a competence in a software based or practical tasks to reach the required level of achievement is a primary way in which a successfully completed report will form resourcefulness.

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.