CS5804 Research Project Management CW Assessment 2025/26 | Brunel University London

CS5804 Research Project Management

Table Of Contents

Main Objective of the Assessment
Description of the Assessment
Learning Outcomes and Marking Criteria
Format of the Assessment
Submission Instructions
Avoiding Academic Misconduct
Expectations of Artificial intelligence Use
Late Coursework

MAIN OBJECTIVE OF THE ASSESSMENT

The coursework for CS5804 (Research Project Management) is an individual research proposal. This assignment assesses the following learning outcomes (LOs):

1.    Critically reflect upon and argue convincingly for the study of a chosen problem area (LO1).
2.    Formulate and critically justify an appropriate research design applicable to the chosen problem area (LO2).
3.    Demonstrate a practical and critical understanding of the key issues and challenges to managing a research project (LO3).

This coursework is designed to prepare you for the dissertation part of your MSc studies, where a key element to a successful MSc dissertation is a well-thought-out project proposal. In this assignment, you have three suggested topic areas. You can also choose your own topic area for this assignment, if you so wish, as long as it is relevant to your degree programme. For your dissertation, you will also have a free choice, subject to obtaining the necessary agreement from your supervisor.

DESCRIPTION OF THE ASSESSMENT

You will be required to produce a research proposal. The topic of your research proposal can either be chosen from below or you can identify your own topic. Please make sure that the topic you choose is aligned to the particular MSc that you are doing.  

Suggested Topic Area 1: Assessing the Evidence about e-Participation

E-participation is a generic term which refers to the use of Web-based technologies, such as online social networks, to enable citizens to engage in political activity with the ultimate aim of influencing policy making. Examples include organising social movements, for example, to oppose government policy, such as funding cuts; various forms of online deliberation and discourse, for example, eConsultation and eVoting; trades union activity; and citizen journalism. Typical research questions in this area focus on the following issues:

• What evidence is there that online interactions, such as those outlined above, foster social inclusion and enable democratic decision making? What alternative research findings exist?
  
  
• Does e-participation enable new forms of organising, and if so, how enduring are these new forms?

Suggested Topic Area 2: Learning Analytics Data Analysis

A course instructor has implemented several new features in a learning management system (LMS) to supplement the current activities undertaken by students studying a module. The instructor wishes to investigate the efficacy of each of these new and existing features as single entities and in combination with each other to increase student attainment. This information will assist the instructor in deciding which features to continue with and augment, and which to drop from the repertoire of activities undertaken by the students. The instructor collected data on which students engaged with which features on the LMS, how many times they accessed and engaged with a particular feature, and their final grades. The instructor also has access to the previous cohort’s final grades to allow comparisons to be made when none of these features were enacted. All of the data is available in CSV files. Students are anonymised and identified by number only.
Typical research projects in this area address the following hypotheses:

• Hypothesis: Specific instructional features are more effective than others at increasing student attainment either singly or in combination with each other.
  
  
• Null Hypothesis: No specific feature or features make any difference to student attainment; it is influenced solely by the number of times a student accesses the materials.

Suggested Topic Area 3: Design for Emotional and/or Physiological Signals

Wearable devices and smart phones are increasingly being enabled to detect data from their users and the environment. This can include human physiological signals (such as heart rate) but research is also exploring whether human displays of emotion can be detected (for example from facial expression, tone of voice). Typical research questions in this area focus on the following issues:

• What kinds of applications could benefit from the integration of such technology?
• What are the legal and ethical implications?
• Are there user acceptance issues?
• How can the effectiveness of such applications be evaluated? 

Additionally, as part of this coursework you are required to undertake (and pass) an online Academic Misconduct Quiz. This can be (re)taken as many times as you need till you get the requisite score to pass the Quiz, the Completion Certificate of which needs to be included as an appendix in your submission - failure to do this will result in FAILING CS5804.

Assignment Structure

Your research proposal should include a literature review; a justification for your choice of research methods; a strategy for collecting data or recruiting participants; and a plan of work for completing your project (e.g. if you are planning for a dissertation with a Spring 2026 start the project should end by mid-September 2026; however projects with other start/end dates and durations can be proposed). You should do this by answering the following questions:

1.    What work has been done already in the topic area and what are the compelling unanswered questions? Your answer should demonstrate that your research question is one that needs further work.
2.    What research methods will you use? Do you think that any other research methods could be used? Justify your selection using appropriate references.
3.    What type of data will you need to collect? If your project requires you to conduct some research using participants, what types of participant will you need? How will you recruit them?
4.    How long will your project take? You should answer this question by including a Gantt chart. Your Gantt chart should include no more than 10 key activities, with dates, and be accompanied by a short description of each activity.
5.    What good project management principles will you use to ensure its success? Do the stages of the GANTT chart include milestone(s) and deliverable(s), as appropriate? Have you identified a risk matrix for your project, with the likelihood of risks to your project, their potential effect on the project, as well as identified measures to mitigate the risks?

Your research proposal should be no longer than 2500 words, excluding references and the Gantt chart.

LEARNING OUTCOMES AND MARKING CRITERIA

FORMAT OF THE ASSESSMENT

Your research proposal should adhere to the following format:

1.    A cover page with your student ID, the module code and title, the academic year and a proposed title for your research project;

2.    Introduction (LO1);

3.    Background/Related Work (LO1);

4.    Methodology - a description and justification of the activities involved in your project (LO2);

5.    Project risk analysis (LO3);

6.    A Gantt chart. (LO3);

7.    A list of all the references used in your proposal, following the Harvard style;

8.    Appendix: Academic Misconduct Quiz Completion Certificate

SUBMISSION INSTRUCTIONS

You must submit your coursework as a PDF file on WISEflow by Friday 7th August 2026  at 11am.  You can follow the link to WISEflow through the module’s section on Brightspace or login in directly at https://uk.wiseflow.net/brunel.  The name of your file should follow the normal convention and must therefore include your student ID number (e.g., 0612345.pdf).  It can also include the module/assessment block code (e.g., CS2801_0612345.pdf).  

AVOIDING ACADEMIC MISCONDUCT

Before working on and then submitting your coursework, please ensure that you understand the meaning of plagiarism, collusion, and cheating (including contract cheating) and the seriousness of these offences.  Academic misconduct is serious and being found guilty of it results in penalties that can reduce the class of your degree and may lead to you being expelled from the University.  Information on what constitutes academic misconduct and the potential consequences for students can be found in Senate Regulation 6.
You may also find it useful to read this PowerPoint presentation which explains, in plain English, the different kinds of misconduct, how to avoid (even accidentally) committing them, how we detect misconduct, and the common reasons that students give for engaging in such activities.  
If you are experiencing difficulties with any part of your studies, remember there is always help available:

• Speak to your personal tutor.  If you’re not sure who your tutor is, you can find the information on eVision or you can ask at the Student Hub (studenthub@brunel.ac.uk).
  
  
• The Student Hub can also provide advice on support and welfare issues.

EXPECTATIONS OF ARTIFICIAL INTELLIGENCE USE

The University has general guidance on using artificial intelligence in your studies.  
We will not stop you from learning from different resources, e.g., online tutorials, videos, code repositories, or generative AI programs like ChatGPT or Gemini. However, none of these must be used unethically to pass off others’ (or AI’s) work as your own.

So, be transparent in your use of AI programs as you would any other resource. Use it for guidance and support and be aware that it may generate erroneous responses. In your assignments, we expect you to be able to explain everything you present, justify why you did things a certain way, argue its limitations, and describe alternative solutions. We want to hear your authentic voice in your work; do not rely on AI to do this for you.

LATE COURSEWORK

The clear expectation is that you will submit your coursework by the submission deadline stated in the study guide. In line with the University’s Coursework Submission Policy (revised in January 2025), coursework submitted up to 48 hours late will be accepted but the penalties set out in the ‘Late Submission’ section of the policy will be applied. Work submitted over 48 hours after the stated deadline will automatically be graded NS (non-submission).

Please refer to the Computer Science student information pages and the Coursework Submission Procedure pages for information on submitting late work, penalties applied and procedures in the case of Extenuating circumstances.