Module Code & Title: CMP9139 Research Methods
Contribution to Final Module Mark: 100%
Description of Assessment Task and Purpose:
This assignment is concerned wilh research data gathering, analysis and interpretation — you wil
obtain a dataset, investigate quantitative methods for analysing this data using inferential
statistics, design an appropriate methodology, conduct your own data analysis using appropriate
software, reflect upon the results, and present your findings. The assessment involves writing a
4-page report in the format of a scientific article, and a presentation on the same subject,
Your first task is to acquire a non-trivial research dataset. This task might involve the design of a
methodology for collecting data as a primary part of the research — for example, by constructing
a survey to elicit data from a chosen user group. Alternatively you may take a pre-existing
dataset from another source, which should be acknowledged in your report, where you then
focus more on the analysis of this data. There are a wide range of sources that could be used. A
few indicative examples of possible datasets could include (bul are not limited to):
“fantasy football” player performance statistics,
«multi-user virtual realty data,
«performance statistics versus ground-truth data for a computer-vision recognition system,
. et.
The choice of dataset can be oriented towards your own personal interests, such as data
elating to your Research Project, etc. but you must submit only original work which has not
een submitted for any other assignment, or which is intended to be used for anothe
assignment (e.g. for your Research Project). If in doubt, please discuss the choice of dataset
with a member of the module delivery team at the earliest available opportunity.
The next task is to investigate the existing research methods and background literature fo
acquiring and analysing similar datasets. Please note that the focus of this task should be more
than the domain-specific methods used for solving a particular research problem (e.g. if a
esearch paper describes the development of an artificial neural network system for stock
market prediction, we are most interested in the methods used to evaluate the system
performance in predicting stock market trends, not the details of the neural network model itself)
There is no need to develop any artefact to generate the dataset that you subsequently analyse.
Please note also that the iterature review should focus on literature relating to your own
esearch question, not “textbook” literature on research methods in general
Based on the background research, design and implement an appropriate methodology fo
analysing your chosen dataset. You will need to identify an appropriate research question (o
questions) and/or hypothesis to test. For example (and not limited to these examples):
«evaluating the effect of the full moon on behaviour,
deciding whether hospital carpeting results in more infections,
selecting the best means to stop smoking,
testing whether acetaminophen or ibuprofen helps faster with headaches
etc
Please note: you must apply inferential statistics to draw conclusions about the population unde
consideration from the sample data, for example, by applying techniques introduced in the
module such as confidence intervals or statistical tests (t-Test, ANOVA, Spearman Co
elation,
etc). Your analysis must be non-trivial — for example, just applying descriptive statistics such as
mean and standard deviation would not be sufficient. Descriptive statistics should however be
used to justify the choice of techniques. If you are in doubt, please discuss the choice of
methodology with a member of the module delivery team at the earliest available opportunity.
Take care to justify the choice of research techniques in your report, including discussion of the
alternatives considered. You should make sure to explain and describe the techniques applied
with sufficient clarity to allow other researchers to replicate your findings if desired. Please make
sure to describe the approach and software that you used to ca
y out statistical testing.
Consider how to best present you results, e.g. using tables, graphs, etc. Discuss the results
obtained and the conclusions infe
ed with respect to the original research hypothesis o
question. Finally, reflect on the value of quantitative approaches in respect to your study. How
does this differ from qualitative approaches, and how could the latter be valuable?
There are two elements for submission to this Assessment
1. Submission of a report (maximum 4 pages in length using the assigned template,
including figures and references), in the style of a scientific paper. Instructions and
guidance for this appears below.
2. Submission of presentation slides. This involves submission of a presentation file (single
Powerpoint file, appropriate for a 5-minute presentation). Instructions and guidance fo
this appears below.
Learning Outcomes Assessed:
On successful completion of this component a student will have demonstrated competence in
the following areas:
[LOY] Identify an appropriate area for study contextualised by the award being studied.
[LOZ] Critically evaluate, select and apply research methods in the specialist area of study.
1LO3] Demonstrate practical skill in the development of a research proposal and literature.
survey.
Knowledge & Skills Assessed:
Subject Specific Knowledge, Skills and Understanding: Literature searching, Referencing,
Numeracy, Project Planning, Techniques and Skills (statistics, data analytics), Subject-specific
knowledge.
Professional Graduate Skills: Independence and personal responsibility, adaptabilty, ve
al
communication, written communication, creativity, critica thinking. IT skills, self-reflection and
life-long learning, problem solving, effective time management, working under pressure to meet
deadlines, leadership.
Emotional Intelligence: Self-awareness, self-management, motivation, resilience, self-
confidence.
Career-focused Skills: Skills (see above) and attributes (see above) required by employers.
‘Assessment Submission Instructions:
The deadline for submission of this work is included in the SoCS Submission dates spreadsheet
on Blackboard. There are two files to be submitted for this assessment
1. Submission of your report must be made electronically through Blackboard to the
Assessment Item 1 upload area for this module. It must be a single PDF file with a
maximum length of four pages.
2. You must also submit your presentation as a single Powerpoint ppbd.opt file (no othe
format will be accepted) in the Supporting Documentation area for Assessment Item 1
“This file must be named with your full name and student ID number.
DO NOT include this
iefing document with your submission.
Date for Return of Feedback:
As stated on SoCS submission spreadsheet.
Format for Assessment:
Report:
Write a 4-page report using the IEEE conference paper format (see:
hitps:/Jwww.leee.ora/conferences/publishina/templates. html where both LaTeX and Word
templates may be obtained) with a maximum of 4 pages including figures and references.
Appendices or additional pages are not permitted. The report should be written in your own
words and follow the general format of a scientific paper. The report should have the following
sections (with a suggested length for each — this is only guidance, not a requirement):
. Tile
«Abstract
«Introduction (approx. % page), including motivation for the topic, choice of dataset, and
esearch hypothesis or question(s)
«Related Work, comprising a literature survey of existing research methods considered fo
data acquisition and analysis with respect to the chosen dataset (less than 1 page).
«Methodology (less than 1 page), including a thorough description of the research
techniques applied in practice.
Results (less than 1 page).
Conclusion (approx. % page), including further discussion of the results and you
‘conclusions with respect to the original research hypothesis or question.
«References
Your written work for this part of the assessment must be submitted via Blackboard (PDF
format), to the Assessment tem 1 submission area, according to the Submission Instructions
above
Presentation:
You are required to submit a set of slides for a presentation of your work: it should be
appropriate to support a five-minute summary of the assignment report. The presentation slides
should
iefly motivate your dataset choice and research question(s), justify the analysis method
you have employed, and discuss the outcome of your analysis (mi
oring the structure of the
eport). As a suggestion, around one slide for each of these aspects would be sufficient. For this
part of the assessment you must submit your presentation file (single file in .pptx!.ppt format) to
the Supporting Documentation area for Assessment ltem 1, according to the Submission
Instructions above.
Feedback Format:
Feedback will be provided on Blackboard based on fulfilled criteria outlined in the associated
CRG. Further feedback may also be provided to students who request clarifications.
‘Additional Information for Completion of Assessment:
Students are encouraged to use any lecture and their own personal notes to assist them with the
completion of the assessment. Also, students are allowed to use any li
ary andlor online
esource as a guide on how to solve the assessment problems. Additional resources should be
appropriately acknowledged if used.
Assessment Support Information:
Students are encouraged to seek assistance from any member of the delivery team fo
discussion and clarifications as required, as a means to complete the assessment.
Important Information on Dishonesty & Plagiarism:
University of Lincoln Regulations define plagiarism as 'the passing off of another person's
thoughts, ideas, writings or images as one's own... Examples of plagiarism include the
unacknowledged use of another person's material whether in original or summary form.
Plagiarism also includes the copying of another student's work’
Plagiarism is a serious offence and is treated by the University as a form of academic
dishonesty. Students are directed to the University Regulations for details of the procedures and
penalties involved.
For further information, see www plagiarism org