Module Specification

Master's Final Project

London school of INNOVATION

Module Specification

Master's Final Project


The Final Research Project is an opportunity for Level 7 students to demonstrate a high degree of autonomy by deeply combining the domain knowledge that they already have in their field with a review of the literature and existing methods, other disciplines, and new insights to critically and rigorously test established paradigms and problems through a careful and methodical investigation, drawing upon mixed sources. It will scrutinise their ability to manage a project using practical computing skills and apply the implementation lifecycle, utilising applicable techniques to put forward well-thought findings that contribute to their discipline, introducing some original computational artefacts and solutions, and creating and interpreting knowledge in their field. Research design and soft skills will form the core of the Final Research Project and students will be trained and assessed on their independent organisation and application of research requirements, including risk management, their systematic selection of methods, and consideration of professional, legal and ethical contexts, especially in their handling and application of technology and data. 

 


Code Number of Credits ECTS Credits Framework HECoS code
FP10 60 30 FHEQ - L7

Learning outcomes

Code Attributes developed Outcomes
LO1 Knowledge and Understanding Comprehensive knowledge of advanced concepts in IT, synthesising new research to inform practical solutions
LO2 Intellectual Skills Analyse and apply research and other appropriate techniques with some originality, incorporating feedback and Open Science principles to contribute to scholarly research.
LO3 Technical/Practical Skills Construct a methodological framework, using interdisciplinary approaches and advanced computing techniques.
LO4 Technical/Practical Skills Demonstrate advanced proficiency in data management, analysis, and use of appropriate research methods to solve complex problems.
LO5 Professional/Transferable Skills Communicate research findings effectively to both technical and non-technical audiences, ensuring clarity and impact.
LO6 Professional/Transferable Skills Exhibit a responsible, professional approach to research, adhering to legal, ethical, and data protection standards.

Assessment Patterns

Weighting Format Outcomes assessed
50% Research Module Assessment: Final Report
Students will be required to submit a final report. The purpose of the final report is to assess how students conducted independent research, applied critical thinking, and demonstrated a systematic understanding of their subject of study within computer science in producing their artefact.

The final report also allows students to showcase their originality in applying knowledge and techniques in producing the artefact, as well as their proficiency in utilizing established research methods and tools. It provides an opportunity for students to communicate their research findings, interpretations, and conclusions effectively, both to specialist and non-specialist audiences.

Students will have a workshop in the module on how to prepare, structure, and submit a final report, and your module leader will be able to provide you with further support whilst you work on it. You will be shown examples of successful and unsuccessful final reports. You will also have the opportunity to present your work during your programme modules and receive peer and tutor feedback.

Throughout the programme, students will regularly receive formative assessment tasks and feedback opportunities to gain actionable feedback (from self, peers and staff) on their own work to indicate how to improve future work and learn how to give constructive feedback to other people.
 K LO1
I LO2
P LO5
P LO6
15% Research Module Assessment: Presentation
Students must deliver a presentation on their artefact. The purpose of the presentation is to assess their ability to communicate their research findings, methodologies, and implications effectively to a diverse audience in a concise, professional, and engaging manner.

The presentation stems from the research problem statement set out in the Final Project proposal, which require students to come up with a practical solution in the form of an artefact that uses the implementation lifecycle. It is envisaged that the Final Project will require students to apply the tools and architectures they have learnt in their programme modules to diagnose problems, undertake requirements analyses, and produce an artefact. This presentation will require them to expand on how they strategized and overcame practical, professional, ethical and other issues and constraints they may have come across.

Students will have a workshop in the research module on how to make an effective presentation, and their module leader will be able to provide them with further support whilst they work on their project. They will have the opportunity to present their work in their programme modules and receive peer and tutor feedback.

Throughout such programme modules, students will also regularly receive formative assessment tasks and feedback opportunities to gain actionable feedback (from self, peers and staff) on their own work to indicate how to improve future work and learn how to give constructive feedback to other people.

 K LO1
I LO2
P LO5
P LO6
35% Research Module Assessment: Artefact
For the research project, students must submit an artefact that meets the problem statement that they articulate in their final report. You will have a workshop on the module on how to ideate and design practical solutions for problems using an implementation lifecycle and how to succeed with your project.

Throughout the programme, in particular, their programme modules, students will regularly receive formative assessment tasks and feedback opportunities to gain actionable feedback (from self, peers and staff) on their own work to indicate how to improve future work and learn how to give constructive feedback to other people.
 K LO1
I LO2
T LO3
T LO4
P LO5
P LO6

Student workload

Activity Total hours
Introductory lecture 1.50
Concept learning (knowledge graph) 18.00
Independent reading, exploration and practice 276.00
Individual Research 300.00
One-to-one project supervision meeting 4.50
600.00

Content Structure

Week Chapter Name Chapter Description
Week 1 Training Seminar 1, Introduction to the MSc Final Research Project Module (Week 1) Learning outcomes and content include:

• The objectives of the MSc Final Research Project
• Level 7 learning outcomes and subject benchmark statements
• Overview of assessments and grading criteria
• Building on the feedback received as part of the proposal process and making changes to research design as needed
• Open Science principles
• Problem solving and using and synthesising contemporary subject matter knowledge and concepts within an MSc research project to set up a systematic and critical framework for critical and original research enquiry
• How to conduct an effective literature review and interpret it so that can contribute to that context and shows appropriate conceptual understanding
• Achieving personal, professional and social impact and communicating research to diverse audiences
Week 2 Training Seminar 2, What do I need to show for my MSc Final Research Project Module (Week 1) Learning outcomes and content:

• How to demonstrate initiative and the requisite level of autonomy and self-direction for an MSc research project
• The power of interdisciplinary research and how it works
• Interpreting research paradigms to advance disciplinary boundaries
• What are the core practical computing skills and the implementation lifecycle
• The Scientific Method?
• Designing an effective research and methodological framework
• Project management for researchers, including time, risk and goal management
• Applying and developing the soft skills you already have
• Artefacts that push boundaries
• The importance of soft skills
Week 3 Training Seminar 3, How do I Succeed in My MSc Final Research Project Module (Week 2) Learning outcomes and content:

• Application of methods - the main research methods that can be used and how they can advance Level 7 research
• The effective use of data e.g. primary and secondary sources, data pipelines, processing, sampling, QA of data, choice, cleaning, weight, storage. indexing, analysis, validity, reliability, risk, bias
Week 4 Training Seminar 4, Why are Professional, Legal and Ethical Contexts Important in My MSc Final Research Project Module (Week 2) Learning outcomes and content include:

• What is a responsible researcher
• The importance of the ‘professional context’ in Masters level research
• The relevance of UK data protection legislation and regulations and the GDPR, and how they apply to academics and researchers
• Handing of data
• The School’s ethics process and approval
• Digital skills
• Cyber-security and IT protocols
• ESG and EDI considerations
• Health and safety
Week 5 Training Seminar 5, Completing and Submitting My MSc Final Research Project Module (Mid-Way) Learning outcomes and content include:

• Application Regulations
• Recap of assessments and grading criteria
• Level 7 learning outcomes
• What are assessors looking for
• Submission
• Bibliography
• Plagiarism, integrity, and honesty
• IP
• Defence and communication to different stakeholders and a diverse audience
• Achieving impact
• Open Science principles
• Publishing
• Careers and professional development

Module References

Type Description
Book Berndtsson, Mikael, et al. Thesis projects: a guide for students in computer science and information systems. Springer Science & Business Media, 2007.
Book McGrath, Jim, and Anthony Coles. Your education masters companion: the essential guide to success. Routledge, 2015.
Book Williamson, Kirsty, and Graeme Johanson, eds. Research methods: Information, systems, and contexts. Chandos Publishing, 2017.
Book Zina, O. The essential guide to doing your research project. Sage, 2021.

Methods of teaching/learning


Introductory lecture (1.50 hours)

This is the first weekly session, dedicated to providing a comprehensive introduction to the module. The module leader will present an overview of the subject, elucidating its importance within various digital engineering professions and its interrelation with other modules. Students will need no preparation ahead of attending this session.

The module leader will provide a structured breakdown of the content to be covered in the subsequent 9 sessions. Students will also receive an outline of the essential reference materials, alongside suggestions for supplementary reading. The format and criteria for the summative assessment will be delineated, followed by a dedicated period for questions and answers.

A recording of the session will be available to facilitate async engagement for any other student who missed the class, also offering an opportunity to review the content again.


Concept learning (knowledge graph) (18.00 hours)

Our institution's approach to teaching is primarily based on flipped learning. Ahead of each weekly session (Workshop/Lab), students will be required to study the essential concepts that are used in the coming session so they are familiar with the theories and ideas related to that session. The study material will be in the form of written content, illustrations, pre-recorded lectures and tutorials, and other forms of content provided through the AGS.

This content is self-navigated by the students, accommodating different learning styles and schedules, allowing students to watch or listen to them at their own pace and review them as needed.


Independent reading, exploration and practice (276.00 hours)

This activity challenges students to engage with the reference material and independently explore and analyse academic literature related to the course topic. Students are expected to select relevant sources, practice critical reading skills, and where applicable technical skills, and synthesise information from multiple references. This is an opportunity to enhance research abilities, critical thinking, and self-directed learning skills while broadening and deepening subject knowledge.


Individual Research (300.00 hours)

Part of the credit hours on a module are also made up of self-guided individual research. These hours enable students to look at what components they are going to study on a module and ascertain for themselves what they will believe will additionally benefit their leaning. This may be prior to attending a lecture or workshop, following their use of a concept learning (knowledge graph) where they identify that additional reading may deepen their understanding of a concept, or after a seminar has taken place. Students will also use self-guided individual research to prepare for summative assessments. In the main, as this is self-guided, students will decide for themselves what additional research they will do. This will require them to identify what concepts or knowledge, skills, and competencies they want to deepen, what resources will assist them, such as books, videos, or online sources, how they will use these, and what the outcomes should be. Students may decide to work with their peers in undertaking this individual research – and they can ask their tutors for guidance and help. Students may also have to use some of their self-guided individual research to prepare for lectures, workshops, or assignments, or for work their tutors have set them.


One-to-one project supervision meeting (4.50 hours)

During these meetings, the student presents their recent progress, including any research findings, data analysis, or draft sections of their work. The supervisor provides feedback, addressing both strengths and areas needing improvement. These sessions often involve discussing challenges faced by the student, strategising solutions, and setting goals or deadlines for the next phase of work. The supervisor may also offer insights on relevant literature, methodologies, or academic writing techniques.

Programmes this module appears on

Programme Term Type
1 Data Science and Analytics (MSc) 3 Core
2 Digital Innovation and Entrepreneurship (MSc) 3 Core
3 Software Technical Leadership (MSc) 3 Core
4 AI for Business Transformation (MSc) 3 Core
5 Digital Project Management (MSc) 3 Core
6 AI and Machine Learning (MSc) 3 Core
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change.
Module Spec: Master's Final Project (FP10)