COMM424DA - Individual Research Project (2023)

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MODULE TITLEIndividual Research Project CREDIT VALUE60
MODULE CODECOMM424DA MODULE CONVENERUnknown
DURATION: TERM 1 2 3
DURATION: WEEKS 0 13 13
Number of Students Taking Module (anticipated) 90
DESCRIPTION - summary of the module content

This module will allow you to apply the knowledge learned in other modules in a significant data science project. You have two options for the selection of your project report:

Option 1. A research project carried out in the employer’s workplace as part of the apprentice’s day to day activities.

Option 2. If your employer does not support this activity as part of the Degree Apprenticeship, then you are free to complete another data science project on a topic of your choice. It may still be related to your organisation, or alternatively, it may be based on any other case study which allows you to collect data and complete theoretical analysis and/or practical software design and implementation. It may be based on your own idea or area of interest, or it could be on a topic proposed and defined by an Academic at the Computer Science Department of the University.

The module will develop your project planning, management and implementation skills as well as those in independent learning, presentation and writing. This will also be an opportunity to gain experience in the implementation of a data science project within your organisation or elsewhere, and to develop your understanding of the business requirements of such projects if you choose Option 1. The module further aims to build on the knowledge and skills you have acquired in the taught modules of the programme to allow you to investigate an area of particular interest to you. It aims to give you experience of many aspects of research work, including problem formulation, literature review, planning, tool development, experimentation, analysis and presentation of results.

Pre-requisites: Work-based project

Corequisites: None

This module is a part of the dual-qualification MSc Data Science (Professional) / Level 7 Research Scientist Apprenticeship programme. It cannot be taken as an elective by students on other programmes.

The apprenticeship standard and other documentation relating to the Level 7 Research Scientist Apprenticeship can be found here: https://www.instituteforapprenticeships.org/apprenticeship-standards/research-scientist-v1-0.

 

AIMS - intentions of the module

The project report is designed to demonstrate the application of knowledge and skills as it would in the occupation. It collates the raw research findings and demonstrates analysis (statistical and scientific), synthesis, evaluation, literature review and produces recommendations for the business to consider. The report is a significant and complex project in itself and thoroughly tests both higher and lower order knowledge and skills.

The module has several aims:

  • To develop skills in project specification, planning and management
  • To develop an understanding of appropriate data science tools to apply
  • To consider the ethical issues associated with collecting, processing and analysing data
  • To consolidate skills in the implementation of data science techniques
  • To develop skills in the understanding and visualisation of the outputs of data science techniques
  • To develop a greater understanding of where data science fits within the employer’s organisation (not valid for option 2)
  • To develop presentation and writing skills

Most work will be independent study, but you will be supported by a supervisory team through regular meetings and progress reports. The supervisory team will normally consist of relevant academic faculty members from the MSc Data Science programme and, if you choose Option 1, a nominated individual at your employer’s organisation. In the latter case, ordinarily, the employer organisation will provide guidance on the business relevance of the project and together with the academic supervisor will identify project goals. Exceptionally, you may choose an academic data science project based on previously taught module content. In this scenario, the supervisory team will consist solely of an academic supervisory from the MSc Data Science programme.

Work towards project goals will be carried out independently over a 9-month period, supported by regular supervision meetings conducted using online tools (e.g. video conferencing).  A number of “project days” will bring all the cohort together on campus to present progress and hold meetings with academic supervisors. Interim and final presentations of project findings will form part of the project assessment, which will be completed with a substantial report.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module you should be able to:  

Module Specific Skills and Knowledge 

1. Demonstrate knowledge of a research topic of relevance to your MSc programme, acquired through a deep and self-motivated exploration of that topic. 

2. Design and follow systematically the phases of research project development. 

3. Apply sophisticated and appropriate analysis and development techniques at each stage of a project. 


Discipline Specific Skills and Knowledge 

4. Show familiarity with the background and context of a new application area. 

5. Produce full documentation as appropriate to the system and research. 

6. Work in an interdisciplinary area. 
 

Personal and Key Transferable / Employment Skills and Knowledge 

7. Conduct independent study, including library and web-based research. 

8. Reflect critically on processes and products. 

9. Plan an extended project and manage time effectively. 

10. Present work to a non-specialist audience. 

 

SYLLABUS PLAN - summary of the structure and academic content of the module

Activities related to this module will include: 

  • Introduction to the module;
  • Identification of suitable projects from within the student’s organisation or based on previous taught content;
  • Creation of a project plan and specification with your supervisor team;
  • Implementation of the project;
  • Presentation of progress updates to student and supervisor;
  • Meetings with academic supervisor (face-to-face and/or online);
  • Final submission: a report and final presentation.
LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 14.00 Guided Independent Study 586.00 Placement / Study Abroad 0.00
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled Learning Teaching Activities 2 Introductory Session
Scheduled Learning Teaching Activities 12 Supervisory meetings
Guided Independent Learning 300 Project work
Guided Independent Learning 286 Background reading and private study

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Supervisor Meetings 12 1-10 Oral

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 70 Written Exams 0 Practical Exams 30
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Project Proposal 10 Max 4 pages 1, 7, 9 Written
Final presentation 20 15 minutes 1-9 Written
Final Report 70 Max 10 pages 2-7,10 Written

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-assessment
Project Porposal Project proposal 1, 7, 9 Within 8 weeks
Final presentation Presentation 1-8, 10 Within 8 weeks
Final Report Resubmitted final report 1-9 Within 8 weeks

 

 

RE-ASSESSMENT NOTES
Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.
 
Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be required to re-take some or all parts of the assessment, as decided by the Module Convenor. The final mark given for a module where re-assessment was taken as a result of referral will be capped at 50%.
RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Not applicable

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE 60 ECTS VALUE 30
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Monday 11 October 2021 LAST REVISION DATE Wednesday 01 November 2023
KEY WORDS SEARCH None Defined