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CM50305: Interdisciplinary thesis formulation report

[Page last updated: 27 October 2020]

Follow this link for further information on academic years Academic Year: 2020/1
Further information on owning departmentsOwning Department/School: Department of Computer Science
Further information on credits Credits: 30      [equivalent to 60 CATS credits]
Further information on notional study hours Notional Study Hours: 600
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Dissertation period
Further information on unit assessment Assessment Summary: CW80OR20
Further information on unit assessment Assessment Detail:
  • Assessment detail for this unit will be available shortly.
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites:
Description: Aims:
The aim of this unit is to train students in:
* problem formulation;
* assessment of the suitability of research methods and computational techniques for finding solutions to a given problem;
* consideration of the implications and impact in the context of artificial intelligence and our society;
* identification of research to address gaps in current methodology; planning a substantial research project;
* writing a research proposal;
* creation of a data management plan for the data that will be generated as part of their project;
* consider ethical implications of the proposed research and gain ethical approval for the proposed work.

Learning Outcomes:

* Students should be able to formulate concise research problems from an informally presented challenge.
* Students should be able to test a methodology on selected aspects of a problem and identify areas of theory or implementation that need further development.
* Students should be able to write a research proposal, including a critical review of related work, and a realistic but challenging programme of planned work.
* Students should be able to create a data management plan for data that will be generated by and/or used in their project.
* Students should be able to gain ethical approval of proposed work.

Problem formulation (F/A)
* Planning research to solve a problem (F/A)
* Critical thinking (F/A)
* Interdisciplinary thinking (F/A)
* Develop a coherent line of argument on key theoretical questions in artificial intelligence/social science/engineering, both orally and in writing (F/A)
* Use appropriate evidence and standards of logic and argumentation to support arguments (F/A)
* Use appropriate standards of referencing, citations and presentation (F/A)
* Data stewardship (F/A)
* Interacting with stakeholders (F)
* Understanding ethical implications of research (F/A)

Each student will create a research proposal for tackling an interdisciplinary research question. The question may initially be presented by a participant, e.g. scientist or industrialist from a partner organisation, at an AI Challenge day or may be originated by the student.

The two criteria for the problem presented are normally that it must have non-academic relevance and implications, and it must fit within the ART-AI remit of having interdisciplinary implications.

This process starts with conversations to elicit the nature of the problem and what aspects of it are feasible to address. Relevant literature is studied, and potential methods are explored.

If an industrial or academic partner is involved, on-site visits are encouraged where relevant to this process. The aim here is not to solve the problem but rather to define a plan for research that will ultimately lead to a solution. Exploratory work and experimental tests/prototypes/studies on selected aspects of the problem will be carried out in order to assess the applicability of existing methodology: if shortcomings are identified, extensions of the underlying theory and methods to deal with these issues should be included in the research proposal. The output from this unit will be a Thesis Formulation Report describing a possible PhD research project. This report will provide background to the problem, a literature review, and a discussion of the academic and broader impacts of the proposed research. Initial development of methods and introductory experiments may be exhibited in detail. The report will also include a data management plan and a completed ethics check-list and if necessary evidence of approval from an ethics committee. Prior to this unit, the student is expected to assemble an interdisciplinary supervisory team and members of this team will monitor preparation of the report. The director of training will oversee the process of assembling this supervisory team. As suggested by the unit title, it is anticipated that students will pursue the research project defined in their Thesis Formulation Report when they continue to the next stage of the ART-AI doctoral training programme.
Further information on programme availabilityProgramme availability:

CM50305 is Compulsory on the following programmes:

Department of Computer Science
  • RSCM-AFM51 : Integrated PhD Accountable, Responsible and Transparent Artificial Intelligence
  • TSCM-AFM51 : MRes Accountable, Responsible and Transparent Artificial Intelligence


  • This unit catalogue is applicable for the 2020/21 academic year only. Students continuing their studies into 2021/22 and beyond should not assume that this unit will be available in future years in the format displayed here for 2020/21.
  • Programmes and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.