MSC DISSERTATION - 2019/0
Module code: COMM002
Module Overview
The dissertation consists of a substantial written report, completed by the student towards the end of their programme of studies. This report is based on a major piece of work that involves applying material encountered in the taught component of the degree, and extending that knowledge with the student's contribution, under the guidance of a supervisor. The dissertation lasts over the whole year (both semesters and into summer), and usually involves software development, experimental or theoretical research, or a substantial literature survey on a specific topic.
Module provider
Computer Science
Module Leader
DONGOL Brijesh (Computer Sci)
Number of Credits: 60
ECTS Credits: 30
Framework: FHEQ Level 7
Module cap (Maximum number of students): N/A
Overall student workload
Workshop Hours: 9
Independent Learning Hours: 585
Lecture Hours: 2
Module Availability
Year long
Prerequisites / Co-requisites
Some project titles may require the student to have taken specific modules from the MSc programme. Before they are allowed to submit their final report, a student must:
- have successfully completed the taught component of the MSc programme
- submit their collection of log sheets documenting supervision meetings
- have successfully completed the taught component of the MSc programme
- submit their collection of log sheets documenting supervision meetings
Module content
The dissertation is the result of an expected 600 hrs of work. Most of this is done individually by the student, in locating and reading relevant sources, working on the technical contribution that is the main part of the dissertation, and writing up the final report. Some time is also spent in regular discussions with the supervisor. Further details are given in the module handbook.
Assessment pattern
| Assessment type | Unit of assessment | Weighting |
|---|---|---|
| Project (Group/Individual/Dissertation) | REPORT | 100 |
Alternative Assessment
N/A
Assessment Strategy
The assessment strategy is designed to provide students with the opportunity to demonstrate that they have achieved the module learning outcomes.
Thus, the summative assessment for this module consists of:
- Grades for the final report against previously published assessment criteria.
- Final submission is tentatively due in late summer.
Formative assessment and feedback
Formative feedback is given by the supervisor during regular meetings.
Module aims
- Provide an opportunity for students to pursue a single topic in depth and to demonstrate evidence of research ability at a Masters level. The topic is typically a current problem in the broad area of their MSc programme. Students are encouraged to either research a new concept or apply existing technology to a new field
Learning outcomes
| Attributes Developed | ||
| 001 | Be able to approach an open-ended topic, to research new ideas and experiment with new technologies. | KC |
| 002 | Be able to locate, select, and interpret sources relevant to their topic. | KT |
| 003 | Integrate and build upon the concepts, theories, and knowledge gained in the taught component of their MSc programme. | KC |
| 004 | Demonstrate their command of the subject matter of their dissertation in a written report. | KC |
| 005 | Demonstrate independent, critical and analytical skills, and an ability to evaluate evidence. The exact nature of this depends on the topic of their dissertation, and is typically demonstrated by: | KCP |
| 006 | For software development projects: a justification of the software design, algorithms, and development methodology chosen, and a critical evaluation of the final solution and its comprehensive testing | |
| 007 | For experimental research: a justification of the experiments to be performed and the experimental methodology used, and a critical evaluation of the results obtained | |
| 008 | For empirical analysis: a justification of the data to be collected and the methodology used, and a critical evaluation of the results obtained | |
| 009 | For theoretical research of a mathematical / technical nature: complete proofs and derivations, as necessary, for a novel problem . | |
| 010 | For a literature survey / comparison / review / evaluation: a comprehensive critical comparison of published systems, based on published results; includes a structured comparison and evaluation putting the different viewpoints from the literature into context, clarifying disagreement and consolidating where possible. Generally includes a well-justified recommendation or other conclusion. |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
Provide students with the knowledge, skills, and practical experience covering the module aims and learning outcomes.
The learning and teaching methods include:
- Regular meetings with the allocated supervisor to discuss progress. (approximately 18 meetings of ½ hour each)
- Lecture on research methods (2 hours)
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Reading list
https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: COMM002
Programmes this module appears in
| Programme | Semester | Classification | Qualifying conditions |
|---|---|---|---|
| Information Systems MSc(YEAR LONG) | Year-long | Compulsory | A weighted aggregate mark of 50% is required to pass the module |
| Information Security MSc(YEAR LONG) | Year-long | Core | Each unit of assessment must be passed at 50% to pass the module |
| Data Science MSc(YEAR LONG) | Year-long | Compulsory | A weighted aggregate mark of 50% is required to pass the module |
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2019/0 academic year.