| Unit name | Data Science for Business Dissertation: Individual project |
|---|---|
| Unit code | MGRCM0053 |
| Credit points | 60 |
| Level of study | M/7 |
| Teaching block(s) |
Academic Year (weeks 1 - 52) |
| Unit director | Dr. Shin |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Management - Business School |
| Faculty | Faculty of Social Sciences and Law |
Why Is This Unit Important?
The Individual Dissertation unit is a critical component of the MSc Data Science for Business programme, offering you the opportunity to independently apply your knowledge and skills to a substantial research project. This unit is essential for developing the ability to conduct rigorous academic research, from formulating research questions covering your pathway to analysing data and discussing results. It allows you to demonstrate your ability to apply quantitative data science methods to complex real-world problems, contributing to you academic and professional growth.
How Does This Unit Fit into Your Programme of Study?
The Individual Dissertation unit serves as the capstone experience of the MSc Data Science for Business programme, synthesising the knowledge and skills acquired across all other units. It is strategically designed to enhance your ability to independently solve business problems within the chosen pathway using data science methodologies. The focus on quantitative research aligns with the program’s emphasis on applying data science techniques to derive actionable insights, making this unit integral to preparing you for both academic and professional careers. This is a must-pass unit for a Master's in Data science for business.
An overview of content
In this unit, you will independently develop a research question related to a complex business problem with your specialised pathway, conduct a comprehensive review of the relevant academic literature, and design a research plan to address the problem. You will collect and analyse data using quantitative methods, applying the data science techniques they have learned throughout the programme. The findings will be synthesised and discussed in the context of existing theories, culminating in a dissertation that clearly communicates the research process and outcomes.
How will students, personally, be different as a result of the unit
Upon completing this unit, you will have gained a deep understanding of how to independently conduct rigorous research using data science techniques. You will have enhanced your critical thinking and problem-solving skills by developing research questions and executing comprehensive research plans. Additionally, you will be able to analyse data, synthesise results, and communicate your findings effectively, preparing them for future academic research or data-driven roles in the business world.
Learning Outcomes
1) Develop a research question and execute a research plan to analyse complex real-world problems.
2) Critically review the relevant academic literature and demonstrate your understanding of the relevant theories.
3) Demonstrate your understanding of how to apply data science to your research questions with consideration of the ethical issues.
4) Effectively analyse the collected data and synthesise interpretations of outcomes theoretically and empirically.
5) Communicate the process and outcomes clearly and professionally.
The individual dissertation is intended to promote self-directed learning and inquiry, under the guidance of two project supervisors from both Schools (70% coming from the Business School and 30% from the School of Engineering, Maths and Technology). You will have two supervisors: the leading supervisor from the Business School and one co-supervisor from Data Science. Supervisors provide support, guidance, and formative feedback through a series of group meetings.
Also, you will receive support through drop-in programming and debugging lab sessions.
Tasks which help you learn and prepare you for summative tasks (formative):
A dissertation is primarily an independent piece of work completed by you; your learning is supported through a series of meetings with the two supervisors through which guidance and formative feedback are provided.
Both supervisors will be present at the first dissertation meetings, halfway through, and at the end of the research period. In addition, the Science and Engineering department will provide practical development support from HPT/TSRs, including drop-in programming and debugging lab sessions.
You are required to submit an individual research proposal (2,000 words) as the formative assessment.
You will be required to attend seminars and workshops related to research methods as part of your formative assessment. The following topics will be covered:
Seminar 1: Dissertation Preparation
Seminar 2: Developing research questions
Seminar 3: Writing literature reviews for dissertations
Workshop 1: Literature searching workshops with the library
Workshop 2& 3: Methods Clinics in Business
Tasks which count towards your unit mark (summative):
A formal presentation to supervisors, academic staff, and peers (20 minutes) (10%). [All Learning Outcomes covered]
An individual dissertation (10,000-12,000 words) (90%). [All Learning Outcomes covered]
When assessment does not go to plan:
When a student fails the dissertation and is eligible to resubmit, a student will retake the dissertation project report. Depending on the nature of the failed first attempt, this reassessment could either entail a revised version of the first submitted attempt or an entirely new piece of work (10,000-12,000 words) (90%; covering the same ILOs as the original]. Also, if students only fail the presentation, they will be asked to submit an individual recorded presentation for their dissertation without requiring a complete rewrite of the new dissertation (10%, covering the same ILOs as the original).
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. MGRCM0053).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
