School of Computing: Assessment brief
Module title Data Mining and Text Analytics
Module code COMP5840
Assignment title Assessment for COMP5840 Data Mining and Text Analytics, Semester
2 2022/23
Assignment type and
description
Assessment 1: Test1 submitted as Minerva MCQ Test,
20% weight, 1 hour to complete, release week4 10:00 Wednesday
22.2.23, deadline 10:00 Thursday 23.2.23
Assessment 2: Test2 submitted as Minerva MCQ Test,
20% weight, 1 hour to complete, release week8 10:00 Wednesday
22.3.23, deadline 10:00 Thursday 23.3.23
Assessment 3: Report on team project, submitted by team leader as
Minerva Assignment,
60% weight, approx 10 hours per student to complete, release week4
Wednesday 22.2.23, deadline week10 10:00 Thursday 4.5.23
Rationale Summative assessment of student knowledge and understanding of the module syllabus.
Word limit and
guidance
Test1: 20 questions. Test2: 20 questions. Report: up to 12 pages
Weighting Test1: 20% Test2: 20%. Report: 60%
Submission deadline Test1: 10:00 Thursday 23.2.23 Test2: 10:00 Thursday 23.3.23
Report: 10:00 Thursday 4.5.23
Submission method Test1 submitted as Minerva MCQ Test Test2 submitted as Minerva MCQ Test
Report submitted by team leader as Minerva Assignment
Feedback provision Yes: Test1, Test2 answers will be presented in a lecture; Report feedback via Minerva Assignment
Learning outcomes
assessed
These exercises will enable you to: learn theory, methods and
terminology used in data mining and text analytics; investigate how to
apply AI methods, resources and techniques for implementing and
evaluating data mining and text analytics in a practical applied research
project; summarize and present your knowledge and ideas to a peer
audience, in a research proposal report.
Module lead Prof Eric Atwell
Other Staff contact Dr Noorhan Abbas
1. Assignment guidance
You are advised to attempt all three assessments: Test1, Test2, Report. There is no exam.
2. Assessment tasks
For Test1 and Test2, each student will take an individual online test in Minerva. The tests will
include Multiple Answer Questions: each question has several suggested answers, and for each
possible answer you must decide if it is correct or not. If you require special arrangements and/or
extra time due to a disability or other special circumstances, please make sure you notify lecturer
Eric Atwell AND student support well in advance so they can prepare accordingly.
For the Report, you will develop a research project proposal, using data mining and text analytics
theory, methods and technologies for a practical application of your choice. Lectures and online
learning resources will include examples of data mining and text analytics methods, techniques,
resources, and applications. You can also include other tools and techniques in your research
proposal, as appropriate.
You should work in a TEAM of 4-6 students: choose your partners, choose a team name, then write
your TEAM NAME next to YOUR NAME on the Class List, a shared file linked from Minerva.
If you don’t have partners, look at the Class List or post to the discussion forum to find others
without a team, and ask them to join you. If you cannot work in a team and need to work alone, you
can do so, but you must let the lecturer know: email e.s.atwell@leeds.ac.uk
Each team must collaborate in developing a research project proposal, and produce a joint team
report; all partners get the same grade. Every student must also take the individual tests 1 and 2.
When writing an applied data mining and text analytics research proposal, you can learn from
advice provided by the Engineering and Physical Sciences Research Council. EPSRC is a major UK
supporter and funder for research projects in Engineering and Physical Sciences, including AI. The
EPSRC website gives guidance on writing research project proposals, see
https://epsrc.ukri.org/funding/applicationprocess/preparing/writing/
https://epsrc.ukri.org/funding/applicationprocess/preparing/writing/caseforsupport/
A standard proposal to EPSRC includes several forms and tables, but the core document is
“Proposed research and its context” to include 6 parts:
Background,
Contribution to knowledge,
Importance,
Research hypothesis & objectives,
Programme and methodology
And Workplan diagram, eg Gantt Chart
You should use these headings to structure your report, and write a section for each of these: max 3
pages for Programme and methodology, max 1 page each for other 5 sections, plus 1 page for
References; maximum 9 pages in total.
In addition, as an Appendix of up to 3 pages, describe your use of data mining and text analytics
tools in developing your Report. This could include: tools used in a small pilot study to trial the
methods proposed; use of tools like Google Scholar or ChatGPT in searching for background
information and drafting the report (include examples of query and results); use of tools like
Grammarly or Word to check and correct grammar and style.
3. General guidance and study support
See Minerva Learning Resources for the module for guidance and study support.
The EPSRC website has further guidance on the sections of the Proposed Research and Context:
Background: Introduce the proposal topic and explain its context. Explain how this work relates to
past and current research in the UK and abroad.
Contribution to knowledge: Describe how your research would be novel and benefit national and
international research, including opportunities to engage with research in other disciplines to
broaden the reach of the new knowledge.
Importance: Explain how the project may contribute to current or future economic success; to future
development of key emerging industries; or addresses key societal challenges.
Research hypothesis and objectives: Set out your research idea or hypothesis. Explain why the
proposed project is novel and timely, e.g. emphasising the scientific ambition, or any potential
transformative outcomes. Identify the overall aims of the project and the measurable objectives
against which the outputs, outcomes and impacts of the work will be assessed.
Programme and methodology: Describe the work programme including research and user
evaluation. Identify the contribution of each member of the research team including any project
partners and stakeholders. Provide objectives and milestones that you will use to monitor progress
and explain how the project will be managed.
The research work programme should make use of an appropriate methodology for AI projects,
such as CRISP-DM; and should include use of at least two data mining and/or text analytics
methods, tools or techniques introduced in the module (eg SketchEngine, Weka, ChatGPT)
1-page workplan diagram must match the written description of the research work programme,
showing start, end and duration of each phase or work-package.
EPSRC Evaluation Criteria: When a research project proposal is submitted to EPSRC, they check
it meets the requirements, then send the proposal to several independent experts for Peer Review.
These peer reviewers then give written feedback on strengths and weaknesses of the proposal, and
marks or scores in the range 0-6.
4. Assessment criteria and marking process
The mark scheme for your report will reflect the EPSRC grading scheme with marks in the range 0-6
for each criterion, EXCEPT the sections on Programme and methodology, and Appendix: these are
most important, and are triple-weighted, so get mark in range 0-18.
In your research proposal report, we will assess:
Background (0-6 marks)
Contribution to knowledge (0-6 marks)
Importance (0-6 marks)
Research hypothesis and objectives (0-6 marks)
Programme and methodology, including workplan diagram (0-18 marks)
Appendix: use of data mining and text analytics tools in developing your Report (0-18 marks)
TOTAL: up to 60 marks
Return of marks and feedback will be via Minerva grade center, approximately 3 weeks after
submission.
5. Presentation and referencing
Page limits are strict: up to 12 pages in total. Text must be single-spaced spaced Arial 11 with 2cm
margins; you cannot include more text by using smaller fonts or narrower margins. You must
present your ideas for all specified sections, and references must be included within the page limits.
The Team Leader must submit one copy of the team report as a Word or PDF document. The
filename should be the Team name e.g. team leader of TextMiners should submit TextMiners.pdf
References and citations must be in a consistent format. I recommend Kilgarriff referencing style
for Artificial Intelligence papers, see https://blog.kilgarriff.co.uk/?p=71 but you are free to use
another format.
The quality of written English will be assessed in this work. As a minimum, you must ensure:
• Paragraphs are used
• There are links between and within paragraphs although these may be ineffective at times
• There are (at least) attempts at referencing
• Word choice and grammar do not seriously undermine the meaning and comprehensibility of
the argument
• Word choice and grammar are generally appropriate to an academic text
These are pass/ fail criteria. So irrespective of marks awarded elsewhere, if you do not meet these
criteria you will fail overall.
6. Submission requirements
The Team Leader must submit one copy of the team report as a Word or PDF document by the due
date and time using the "Submit My Work" link on Minerva. The filename should be the Team name
e.g. TextMiners.pdf
When submitting, add a text comment with team name, and names of members of the team, so all
team members can be allocated the mark.
7. Academic misconduct and plagiarism
Academic integrity means engaging in good academic practice. This involves essential academic
skills, such as keeping track of where you find ideas and information and referencing these
accurately in your work.
By submitting this assignment you are confirming that the work is a true expression of your own
work and ideas and that you have given credit to others where their work has contributed to yours.
8. Assessment/ marking criteria grid
The mark scheme for your report will reflect the EPSRC grading scheme with marks in the range 0-6
for each criterion, EXCEPT the sections on Programme and methodology, and Appendix: these are
most important, and are triple-weighted, so get mark in range 0-18.
In your research proposal report, we will assess:
Background (0-6 marks)
Contribution to knowledge (0-6 marks)
Importance (0-6 marks)
Research hypothesis and objectives (0-6 marks)
Programme and methodology, including workplan diagram (0-18 marks)
Appendix: use of data mining and text analytics tools in developing your Report (0-18 marks)