DSM060 Data Science Research Topics Coursework Assignment 2026 | UOL

DSM060 Coursework Assignment

MSC DATA SCIENCE

DSM060: Data Science Research Topics

Coursework assignment: Literature review

This assignment is weighted at 50% of the final mark for the module.

The purpose of this coursework is to help you to:

• reflect on your research interests in the area of data science and select a topic to focus on
• identify specific problems within the topic of your interest
• evaluate suitability of the identified problems for a MSc data science project get practical experience in analysing relevant sources of information
• get practical experience in writing a literature review report.

For the coursework, please select a topic relevant to data science. You may wish to select one of those we discuss in this module: business analytics, artificial intelligence, text mining, and knowledge discovery in databases. You are not limited to those topics and free to consider a wide range of topics.

Then, narrow down the selected topic to particular issues, gaps or areas of discussions. For example, you can narrow the topic of artificial intelligence to the issues of explainability and interpretability. You can select the topic of text mining and narrow it down to the problem of resolving ambiguity of natural language expressions. Whatever you choose, it should be of interest to you and have a potential to lead to a project you may wish to carry out in the near future. You will be then more motivated to explore in depth the selected topic.

A literature review is at the heart of any good research project. It helps to identify unsolved problems and existing gaps, leads to formulating new tasks, and shows directions for solving those tasks on the basis of achievements of previous research. The literature review will help you to:

• understand the history of the subject that you intend to investigate
• understand the significance of the studies that have been already conducted in the field
• become familiar with the vocabulary and various definitions
• become aware of the current research and debates
• identify gaps in the literature and neglected areas.

You should synthesise the various views and opinions expressed by various scholars. We recommend basing your literature review on a wide range of sources, including books, journal articles, conference proceedings, unpublished articles (e.g. preprints submitted to online archives), news articles, blogs. The area of data science is evolving fast, and we advise you to focus on recent publications. Your reference list should include 50-70% of references within the last three-five years.  

Writing a literature review may be time consuming. Therefore, you are welcome to use the material you have prepared during your peer review exercise. You are free to choose not to do so and to focus on an entirely different topic or problem.

Format Requirements

Your literature review report should be word- or TeX (LaTeX)-processed. Please submit your report as a pdf or word document, and figures – as jpeg images. The formatting requirements are:

• a clear font (Arial, Calibri, Times New Roman)
• 12 point size font
• at least 2cm margins
• number the pages of your text in the bottom right corner of each page
• do not use endnotes or footnotes
• the title page, figures, tables (excluding their captions) do not count towards the word limit.

Number of words limit

Please do not exceed the word count limit of 3,000 words (excluding the title page, figures, tables and a list of references). If you submit more than 3,000 words the following penalties apply:

You should not exceed the maximum word limit. Five marks will be deducted if the word count is up to 10% more than the maximum word limit.

If the word count exceeds the maximum word limit by more than 10%, you will receive a mark of zero for your work.

Please do not treat the limit of 3,000 words as a target. However, we do not recommend submitting reports with less than 2,000 words.

The Structure Of A Literature Review Report

The title of your report

Abstract [15 Point]

Give a summary of your literature review. Try to include the following:

• a high-level description of the topic area
• an overview of the problem studied and why this is interesting/relevant/important a high-level description of the approach taken
  a summary of the conclusions.

If possible, try not to exceed 500 words.

A good abstract is difficult to write and can only be completed after the full report has been written. It represents a brief summary of the review you have carried out and its results. By summarising the results of your review, you allow other people to get an idea of what was accomplished without having to read through the whole report. Other scholars can read an abstract to decide if looking at the full report will be worthwhile. The abstract should provide sufficient information about the review that reading the full report is not necessary, although your markers will read the full report.

Keywords: [5 points]

Up to four keywords that are distinctive and important for your report (e.g. text mining, disambiguation).

Background [10 Point]

Describe the topic and the problem which your report will be focusing on.

The first paragraph will usually introduce the general area of the report. The next paragraph(s) will describe the importance of the selected topic, its brief history, and future trajectories. The final paragraph will present a problem or question your review will be dedicated to.

Review Of The Literature [40 Point]

This is the main part of your report. Provide analysis of at least ten previous works in the selected area; where you reference previous research. Use the format ‘Jones and Bloggs (1999) argued…’ or ‘it has been found that… (Patel, 2002)’, i.e. only author surname(s) and date should appear here, and full details of the reference appear in the reference list (see below).

Conclusion And Discussion [20 Point]

Synthesise and summarise findings of your literature analysis. What have been achieved in recent years in the selected area? What are limitations of existing approaches, why do they exist? Can you outline ways for addressing those limitations? Please state if any of your findings may lead to a data science project you may wish to carry out in future.

Acknowledgements

Who are you grateful to? Your supervisor? Your fellow students who provided useful feedback for your review?

References [10 Point]

Cite at least ten references relevant to the selected topic using the Harvard style. Provide an alphabetical list, ordered by first author surname, of all references you cite in the text of this report; the accepted format style for referencing is the Harvard style – search ‘Harvard referencing’ online to find lots of useful resources on how to do this. You may use other generally accepted styles.

https://www.london.ac.uk/sites/default/files/programme-regulations-data-science-msc-2025-25.pdf

Total number of words:

Insert a word count.

The content within the main body of text comprises the overall word count, including in-text citations, references, quotes, heading and sub-headings. The cover page, reference list and any appendices do not count towards the overall word count.

The world limit is 3000 words.

Make sure that you are fully aware of the University guidelines on plagiarism (see the Student handbook). The penalties if you are caught are severe. All material from other sources must be properly referenced and direct quotes must appear in quotation marks.