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Programme Specification
Postgraduate
Applicable to postgraduate programmes
Please click here for guidance on completing this specification template.
Part A: Programme Summary Information
1. Title of programme: Advanced Computer Science with Internet
Economics with a Year in Industry
2. Programme Code: CSCN
3. Entry Award(s):
Credit: Level:
☐ MA
☒ MSc 240 Level 7, of which up to 30
credits may be at level 6
☐ PGDip
☐ PGCert
☐ DPS
☐ CPS
☐ Other (please
specify below:
4.
Exit Awards: Credit: Level:
☒ PGDip 120 Level 7, of which up to 30
credits may be at level 6
☒ PGCert 60 Level 7, of which up to 15
credits may be at level 6
☐ CPS
Exit awards will automatically bear the name of the entry award. If an exit
award is to be unnamed (i.e. it will show only the qualification achieved) or
if it is to have a different name from the entry qualification you must
indicate this below:
5. Date of first intake: September 2016
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6. Frequency of intake: Annually in September
7. Duration and mode of
study:
Full time, 24 months
8. Applicable framework: University Framework for Postgraduate
Modular Provision
Framework exemption
required: Please indicate the applicable boxes:
☒
No (please go to section 9)
☐
Yes (please provide a brief summary
below)
Date exemption
approved by AQSC:
9. Applicable Ordinance: General Ordinance for Module Masters’
Degree, Postgraduate Diplomas and
Postgraduate Certificates
New/revised Ordinance
required:
☒
No (please go to section 10)
Please indicate the applicable boxes:
☐
Yes (please provide a brief summary
below)
Date new/revised
Ordinance approved by
Council:
10. Faculty:
Faculty of Science and Engineering
11: Level 2
School/Institute:
School of Electrical Engineering, Electronics,
and Computer Science
12. Level 1 unit: Department of Computer Science
13. Campus: Liverpool campus
14. Other contributors from
UoL:
University of Liverpool Management School
(ULMS)
15: Teaching other than at
UoL:
None
16: Director of Studies: To be appointed
17: Board of Studies: Board of Studies in Computer Science
18: Board of Examiners: The Computer Science Postgraduate Board of
Examiners
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19. External Examiner(s):
Name
Institution
Position
Dr Andrew Fish
University of Brighton
20. Professional, Statutory
or Regulatory body:
None
21: QAA Subject benchmark
Statements(s):
QAA Subject Benchmark Statement: Master’s
Degrees in Computing 2011
22. Other reference points: BCS Course Guidelines and Course
Accreditation Criteria
23. Fees: The tuition fees for the 2-year programme are
the same as the standard 1-year MSc
programme since the taught modules are the
same and the year in industry is equivalent to
the summer project for the 1-year MSc
programme
http://www.liv.ac.uk/study/postgraduate/fina
nce/#tuition-fees
24. Additional costs to the
student:
The student would be expected to be paid a
salary during their industrial placement.
However, the student would be responsible for
any additional costs such as associated with
obtaining an industrial placement and
relocation.
25: AQSC approval:
Part B: Programme Aims & Objectives
26. Aims of the Programme
The MSc in Advanced Computer Science with Internet Economics with a
Year in Industry is a two year programme aimed at providing students with
an in depth understanding of the area of Computational Economics with
applications related to Electronic Commerce. More specifically the
programme is designed to allow students to gain a specialist qualification in
an area of on the intersection of computer science and economics which has
seen a recent rapid growth and in which there is expected to be a significant
skills shortage. The programme has a single entry route (MSc). Students
wishing to attain PGCert or PGDip entry awards should enrol on the one
year MSc Advanced Computer Science with Internet Economics programme
which has identical first and second semesters as the two year programme.
The aims of the programme are as follows:
No. Aim:
1 To provide postgraduate students with a deep and systematic understanding of
the current academic research in the intersection of Economics and Computer
Science together with applicable aspects of this research area.
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2 To provide a comprehensive and broad overview of modern contemporary
applications of the game theoretic and algorithmic paradigms related to the
Internet.
3 To build a solid theoretical and practical academic foundation linked to some
concrete applications within electronic commerce.
4 To prepare students to become professionals in the cutting-edge area of
algorithmic game theory, and possibly to continue to a research degree.
5 To augment and to enrich students’ knowledge with specialized analytical tools
to be used in the realization and effective use of complex electronic commerce
computer systems.
6 To develop the abilities of the students to work independently and with others
to research, design, implement and execute creative solutions to practical
problems.
27. Learning Outcomes
No. Learning outcomes – Master’s degree
1 A deep and systematic understanding of the foundational subareas of the
programme, related to economics, optimization, and game theory. 2 A deep and systematic understanding of the terminology, paradigms, and
current state of knowledge of the subject of algorithmic game theory, which is
the academic research area in the intersection of Economics and Computer
Science.
3 The ability to effectively use theoretical paradigms related to optimization,
algorithmics, game theory and economics in a context of practical, business
related applications.
4 The ability to critically evaluate current knowledge and to apply it effectively in
a professional context.
5 A critical awareness of current issues and methodologies to enable participation
in the design, implementation and evaluation of electronic commerce systems.
6 In-depth understanding of the practical and technical issues involved in the
analysis, design and implementation of computer systems within appropriate
specialised areas.
7 The ability to plan and carry out a major project within an appropriate area of
specialisation, requiring original thought and substantial aspects of research,
creative design and realisation, presenting the outcome in a detailed report
which evaluates the work critically in the context of current knowledge and
practice.
8 An ability to work independently, and with others, to analyse, design and
implement solutions to real world problems using advanced methodologies in
the intersection of Economics and Computer Science.
Learning Outcomes
No. Learning outcomes – Postgraduate Diploma (exit award)
1 A deep and systematic understanding of the foundational subareas of the
programme, related to economics, optimization, and game theory.
2 A deep and systematic understanding of the terminology, paradigms, and
current state of knowledge of the subject of algorithmic game theory, which is
the academic research area in the intersection of Economics and Computer
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Science.
3 The ability to effectively use theoretical paradigms related to optimization,
algorithmics, game theory and economics in a context of practical, business
related applications.
4 The ability to critically evaluate current knowledge and to apply it effectively in a professional context.
5 A critical awareness of current issues and methodologies to enable participation in the design, implementation and evaluation of electronic commerce systems.
Learning Outcomes
No. Learning outcomes – Postgraduate Certificate (exit award)
1 A deep and systematic understanding of the foundational subareas of the
programme, related to economics, optimization, and game theory.
2 A deep and systematic understanding of the terminology, paradigms, and
current state of knowledge of the subject of algorithmic game theory, which is
the academic research area in the intersection of Economics and Computer
Science.
27a. Mapping of subject-based learning outcomes:
Learning
outcome No.
Module(s) in which
this will be
delivered
Mode of assessing
achievement of learning
outcome
PSRB/Subject
benchmark
statement (if
applicable)
1 COMP310, COMP315
Written examination
COMP323, COMP523
COMP526, COMP557
COMP559
Practical assessments/
Written examination
COMP589, COMP599
Practical assessments/
Demonstration/
Presentation/Dissertation
ECON915 Class tests/Written
examination
2 COMP323, COMP557
COMP559
Practical assessments/
Written examinations
3 COMP310, COMP315
Written examinations
COMP323, COMP523
COMP526, COMP527
COMP557, COMP559
Practical assessments/
Written examinations
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ECON915 Class tests/Written
examination
4 COMP310, COMP315 Written examinations
COMP323, COMP523
COMP524, COMP526
COMP527, COMP557
COMP559
Practical assessments/
Written examination
COMP516
Essay/Class tests/
Presentation
COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
5 COMP315 Written examination
COMP323, COMP517
COMP557, COMP559
Practical
assessments/Written
examinations
6 COMP310, COMP315
Written examinations
COMP323, COMP517,
COMP523, COMP524
COMP526, COMP527
COMP557, COMP559
Practical assessments/
Written examinations
COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
7 COMP516
Essay/Class
tests/Presentation
COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
8 COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
28. Skills and Other Attributes
No. Skills and attributes:
1 Specialist Skills
1.1 Algorithm design and analysis in general.
1.2 Mathematical modelling of complex distributed and competitive scenarios and
game theoretic tools for predicting and analysing stable solutions in such
settings.
1.3 Mathematical modelling of optimisation problems and tools for efficiently
solving such problems.
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1.4 Game theoretic modelling of recommendations systems (e.g., Google’s
PageRank system), which are present in most of the e-commerce Internet
systems.
2 Key Skills
2.1 Deal with complex issues at the forefront of the academic discipline of
Algorithmic Game Theory in a manner, based on sound judgements, that is
both systematic and creative; and be able to communicate conclusions clearly
to both specialists and non-specialists.
2.2 Demonstrate self-direction and originality in tackling and solving problems
within the domain of Algorithmic Game Theory, and be able to act autonomously in planning and implementing solutions in a professional manner.
2.3 Continue to advance their knowledge and understanding, and to develop new
skills to a high level, with respect to continuing professional development as “a self-directed life-long learner” across the discipline of Algorithmic Game Theory.
2.4 Make use of the qualities and transferable skills necessary for employment
requiring: (a) the exercise of initiative and personal responsibility, (b) decision
making in complex and unpredictable situations, and (c) the independent learning ability required for continuing professional development.
2.5 Participate within the professional, legal and ethical framework within which
they would be expected to operate as professionals within today’s fast-changing sector of electronic commerce and Internet applications.
28a. Mapping of skills and other attributes:
Skills and
other
attributes
No.
Module(s) in which
this will be delivered
and assessed
Learning skills,
research skills,
employability
skills
Mode of assessing
achievement of the skill
or other attribute
1.1 COMP323, COMP517
COMP523, COMP524
COMP526, COMP557
Learning skills
Research skills
Practical assessments/
Written examination
1.2 COMP310
Research skills Written examination
COMP323, COMP524
COMP559
Practical assessments/
Written examination
ECON915 Class tests/Written
examination
1.3 COMP323, COMP523
COMP526, COMP527
COMP557
Research skills Practical assessments/
Written examination
1.4
COMP315
Research skills
Learning skills
Written examination
COMP323, COMP557
COMP559
Practical
assessments/Written
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examination
2.1 COMP323, COMP557,
COMP559
Leaning skills
Employability
skills
Practical assessments/
Written examination
COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
2.2 COMP323, COMP523
COMP526, COMP557
COMP559,
Employability
skills
Practical
assessments/Written
examination
COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
2.3 COMP323, COMP557,
COMP559
Learning skills
Employability
skills
Practical assessments/
Written examination
COMP516
Essay/Class tests/
Presentation
COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
2.4 COMP516
Learning skills
Employability
skills
Essay/Class
tests/Presentation
COMP517
Practical assessments/
Written examination
ECON915
Class tests/Written
examination
COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
2.5 COMP310, COMP315
Employability
skills
Written examinations
COMP323, COMP527
Practical assessments/
Written examination
COMP516
Essay/Class tests/
Presentation
COMP598, COMP599 Practical assessments/
Demonstration/
Presentation/Dissertation
ECON915 Class tests/Written
examination
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29. Career opportunities:
The programme is aimed principally at graduates who either plan to become
high-profile professionals working in IT industry or for those who plan to
continue to a research degree in this cutting-edge research area. This
programme may also be appropriate for those professionals who are already in
IT-related employment and wish to broaden and deepen their knowledge. It is
intended that the programme will underpin and enhance their knowledge and
understanding of the subject matter that is relevant to their profession, bringing
it up to date with current development, and augmenting it with specialised
knowledge in areas related to electronic commerce. The expectation is that this
enhancement, together with the skills they will exercise in the programme, will
provide a basis for their further career development towards senior technical
and managerial positions in the profession, and for those aiming at a research
degree, it will provide a strong foundational background and exposition to
research topics in the area.
There has been a strong demand coming from the industry for high-profile
professionals specialized in this area on the interface of Computer Science and
Economics, and it has been observed worldwide that this area became
increasingly important and popular as the topic of PhD study. To address the
facilitation of close links with industry for those students whose goal is to
pursue an industrial career, the programme offers a unique opportunity of
undertaking their final project as an industrial placement. Both our university
and our department will offer help with finding interesting and relevant
placements, using our extensive network of industrial contacts.
Part C: Entrance Requirements
30. Academic Requirements:
From 2013 the minimum entry requirement is a 2:1 Honours degree (or above)
from an accepted University or other Institute of Higher Education in a subject
area closely related to Computer Science, Economics, or the intersection of
these two subject areas. Applicants who do not offer a 2:1 (or higher) Honours
degree will still be considered if their performance in mathematics and/or
foundational Computer Science and/or foundational Economics courses during
their studies is at least in the 2:1 range. The applications will be considered in a
case-by-case basis.
Students with an Economics (and related) Honours degree are required to have
a mathematical element in their first degree equivalent to first year
undergraduate basic Mathematics, e.g., basic set theory, basic logic, basic
graph theory. This requirement is fulfilled by the students offering BSc degrees
in Computer Science.
Students offering the BSc Honours degree in e-Finance from the University of
Liverpool (or similar) are also eligible to enter the MSc in Advanced Computer
Science with Internet Economics with a Year in Industry programme and are
categorised as Computer Science entrants.
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Applicants who have computing related BSc Honours degrees, but where those
degrees provide only partial coverage of the content and/or do not achieve the
standard of a UK Computer Science BSc degree will be considered on a case-
by-case basis.
Overseas qualifications will be considered using NARIC to verify their nature
and standard.
From 2012-13 entry, candidates from non-English speaking countries are
expected to have IELTS >= 6.5 with minimum 5.5 in each component (other
English Language Tests are also accepted, see Guidance on the University
website for details).
31. Work experience:
It is University Policy to encourage mature entry. Relevant work experience will
be taken into consideration. Each case is considered on merit, but in such cases
work experience is taken into account
32. Other requirements:
None
Part D: Programme Structure
33. Programme Structure:
The programme MSc in Advanced Computer Science with Internet Economics
with a Year in Industry is divided into two equally weighted yeas (years 1 and
2). The first year runs concurrently with the normal first and second
undergraduate semesters, and comprises taught modules to a total of 60
credits per semester (120 credits in total). The placement takes place in the
second year typically running concurrently with the normal first and second
undergraduate semesters. This counts for a further 120 credits, making a total
of 240 credits over the two year period.
This programme is designed for two broad potential groups of entering
students, i.e., for those with BSc Honours degree in Economics (or related
subjects) and those holding BSc Honours degree in Computer Science.
Computer Science entrants
Students with a first degree in Computer Science (or a related subject) are
expected to pursue the following programme of study (`’ indicates a required
module):
Module Code
Module Title Credit Value
Level Co-requisites
Pre-requisites
Pre-requisite
for
Year 1 – Semester 1
COMP516 Research Methods in Computer Science ()
15 7 - First degree in Computer Science or closely related subject
COMP598 COMP599 COMP524 COMP525
COMP557 Optimisation () 15 7 - - -
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ECON915 Microeconomic Theory ()
15 7 - First degree in Economics or equivalent field2
-
Students who have not previously taken COMP323 (or an equivalent) as part of their undergraduate programme take
COMP323 Introduction to Computational Game Theory ()
15 7 - COMP109 or equivalent mathematical module
COMP598 COMP599
Students who have taken COMP323 (or an equivalent) as part of their undergraduate programme take
COMP523 Advanced Algorithmic Techniques ()
15 7 - - -
Year 1 – Semester 2
COMP526 Applied Algorithmics ()
15 7 - COMP516 -
COMP559 Computational Auctions and Mechanism Design ()
15 7 - COMP516 COMP323/523 COMP557 ECON915
-
Plus options totalling 30 credits from the following four modules provided pre-requisites are satisfied
COMP310 Multi-Agent Systems 15 6 - - -
COMP315 Technologies for E-Commerce
15 6 - - -
COMP524 Safety and Dependability
15 7 - - -
COMP527 Data Mining and Visualisation
15 7 - - -
Year 2 – Semester 1 and 2
Module Code
Module Title Credit Value
Level Co-requisites
Pre-requisites
Pre-requisite
for
COMP598 MSc Placement Experience
60 7 - Successful
completion of first year
taught modules
-
COMP599 MSc Industrial Project 60 7 - -
Note 1: Students can choose at most one optional module at level 6. Students
who took COMP323 as part of their undergraduate programme, replace
COMP323 by COMP523.
Note 2: ECON915 normally has a prerequisite of an Economics undergraduate
degree. It has been agreed with the Management School that a Computer
Science degree will be considered to be equivalent for students on the MSc
Advanced Computer Science with Internet Economics.
Economics entrants
Students with a first degree in Economics (or a related subject) are expected to
pursue the following programme of study (`’ indicates a required module):
Module Code
Module Title Credit Value
Level Co-requisites
Pre-requisites
Pre-requisite
for
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Year 1 – Semester 1
COMP323 Introduction to Computational Game Theory ()
15 6 - - -
COMP516 Research Methods in Computer Science ()
15 7 - First degree in suitable subject
COMP702 COMP524 COMP525
COMP517 Object-Oriented Software Development ()
15 7 - First degree in suitable subject other than Computer Science
COMP524 COMP525 COMP526 COMP527
COMP557 Optimisation () 15 7 - - -
Year 2 – Semester 2
COMP526 Applied Algorithmics () 15 7 - COMP516 -
COMP559 Computational Auctions and Mechanism Design ()
15 7 - COMP516 COMP323 COMP557
-
Plus options totalling 30 credits from the following four modules provided pre-requisites are satisfied (at most one module at level 6 can be taken)
COMP310 Multi-Agent Systems 15 6 - - -
COMP315 Technologies for E-Commerce
15 6 - - -
COMP524 Safety and Dependability 15 7 - COMP516 COMP517
-
COMP527 Data Mining and Visualisation
15 7 - COMP516 -
Year 2 – Semester 1 and 2
Module Code
Module Title Credit Value
Level Co-requisites
Pre-requisites
Pre-requisite
for
COMP598 MSc Placement Experience
60 7 - Successful
completion of first year
taught modules
-
COMP599 MSc Industrial Project 60 7 - -
Note: In exceptional circumstances, and with the approval of the programme
Director of Studies, alternative modules available within the Computer Science
provision may be substituted for optional and required modules, except
COMP516, COMP598 and COMP599.
34. Industrial placement/work placement/year abroad:
Preparation for the year in industry will begin in Year 1 through COMP516
“Research Methods in Computer Science” which is a 15 credit module.
During the placement which is a 30-week minimum placement, the student
should complete two-60 credit modules: (i) COMP598 MSc Placement
Experience and (ii) COMP599 MSc Industrial Project. In order to receive
the MSc degree, the student should pass both modules. COMP598 is a
pass/fail module and will not contribute to the MSc degree classification
and cannot be considered as a PG Dip exit award module since its
emphasis is on gaining industrial experience. COMP599 is focused on doing
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an industrial research project and it will be chosen by the student by the
end of semester 2 in Year One. In situations where a student is not able to
find a placement by the end of semester 2, or fails to complete the
industrial placement, the student will be able to transfer to the standard
version of the programme and commence a new project at the University.
The placement and project will take place from an agreed starting date
(typically September, but an earlier date is acceptable) to next May, in an
appropriate IT environment. The department will have a dedicated advisor
working with UoL’s Careers and Employability Services, so as to assist
students in gaining a placement. As noted above if a student has failed to
find a placement and project, the student will transfer to the one-year MSc
Advanced Computer Science with Internet Economics programme.
All placements, and the project work to be carried out as part of the
placement, will be agreed by the students and industrial placement
partners, and approved by the MSc Programme Director. Each student on
placement will have an industrial supervisor in the company and an
academic supervisor within the Department. A dedicated liaison
advisor/coordinator will be appointed by the School/Department.
The supervisor at the University, working with the industrial supervisor,
will be responsible for the assessment of the placement experience and the
industrial project modules (COMP598 and COMP599). The placement
experience module (COMP598) will be assessed in terms of a portfolio
containing a number of documents as articulated in the COMP598 module
specification. For the project module the assessment comprises: (i) an
interim report (35% in January), (ii) an oral presentation (15% in May),
and (iii) a final report (50% in May).
35. Liaison between the Level 2 Schools/Institutes involved:
The Director of Studies for the programme MSc Advanced Computer
Science with Internet Economics acts as liaison with the University of
Liverpool Management School (ULMS) regarding matters relating to the
one module that ULMS provides for this programme
Part E: Learning, Teaching and Assessment Strategies
36. Learning, Teaching and Assessment Strategies:
The MSc Advanced Computer Science with Internet Economics with a Year
in Industry programme complies with:
a. University of Liverpool Policy on Standards and Quality in Learning and
Teaching
b. University of Liverpool Learning and Study Skills Strategy
c. University of Liverpool Code of Practice on Assessment
(all at http://www.liv.ac.uk/tqsd/pol_strat_cop/index.htm)
d. Department of Computer Science Learning and Teaching Strategy:
http://www.csc.liv.ac.uk/department/LTAS.html
The majority of the modules on the programme are research-oriented in
that the subject matter is founded on the current research work
undertaken by the department, and, in particular, the programme closely
relates to the research groups on Economics and Computation, Algorithms
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and Optimisation and Robotics and Autonomous Systems. A research-led
feature of the programme is also manifested in the final project COMP599,
which is meant to apply the foundational knowledge learned by the
students during the first year in context of practically motivated industrial
applications.
The programme is divided into three main parts: Foundational (Semester
1), Core (Semester 2) and the MSc Project. The first part provides an
update of knowledge for the entering students – on economics for CS
students, and on programming for Economics students; then the
Foundational part provides a broad introduction to optimization and
(computational) game theory, which are the basis for the Core part and
the Final Project. Module COMP323 covers a comprehensive introduction to
non-cooperative and economic game theory and it also covers a number of
topics in algorithmic game theory, and these are continued, broadened and
further developed in the Core part via modules COMP558 and COMP559.
Module COMP557 on optimisation provides the basis for the algorithmic
and computational aspect of the programme. In particular this programme
puts emphasis on the algorithmic aspects and this is also reflected by the
requirement that students take at least one of the elective algorithmic
modules, COMP523 and COMP526. All elective modules provide further
knowledge augmented by specific applications to tighten the connections
to Computer Science. Having gained this knowledge during the first year,
the students are expected to demonstrate its use during the project phase
in the second year when they will realise their MSc project within an
industrial placement.
The Department has made use of techniques associated with e-learning for
many years. In this programme (as in all others), lecture material,
assignments, and model solutions are all made available online.
Continually assessed work is often submitted electronically, allowing
plagiarism detection to be performed automatically. A computer-based
system is also used for all attendance monitoring at lectures and tutorials.
36a. Learning, Teaching and Assessment methods:
The learning and teaching strategy for the programme comprises a
mixture of formal lectures, practical and tutorial sessions, and student
centred learning, and project work. Additional support is from WWW based
materials, selected textbooks and directed reading of research literature
(taken from scientific journals and conference proceedings). The
programme operates under the approved teaching and learning strategy of
the Department of Computer Science.
The programme is assessed by a combination of traditional written
examinations and continuous assessment, including marked essays and
computer programming problems. In more detail, modules in the
Computer Science programme are assessed as follows (according to the
nature of the module):
i. Examination only where the assessment is based entirely on
examination, which is held at the end of the semester in which
the module is taught.
ii. Continuous Assessment.
iii. Examination and continuous assessment.
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The MSc project COMP599 includes an element of assessment by oral,
poster and/or demonstration presentation of project work. The mark
produced for a module is subject to scrutiny by the Computer Science
Postgraduate Boards of Examiners including the External Examiner for this
programme. Decisions on progress are also controlled by the university's
published regulations.
The Department currently does not conduct any “viva voce” examinations.
Details of the assessment method for each module can be obtained from
the Department of Computer Science Student Handbook. For information
on adjustments to examination arrangements for disabled students see
Appendix K of the University Code of Practice on Assessment.
37. Assessment information for students:
Code of Practice on Assessment
The University has a Code of Practice on Assessment which brings together the
main institutional policies and rules on assessment. The Code is an
authoritative statement of the philosophy and principles underlying all
assessment activities and of the University's expectations in relation to how
academic subjects design, implement and review assessment strategies for all
taught programmes of study.
The Code of Practice includes a number of Appendices which provide more
detail on the regulations and rules that govern assessment activity; these
include:
The University marks scale, marking descriptors and qualification descriptors;
The framework for modular, postgraduate programmes;
Information about students’ progress, including guidance for students;
The procedure for assessment appeals;
Regulations for the conduct of exams;
The University’s policy on making adjustments to exam arrangements for
disabled students.
The code of practice relating to external examining (see also below)
The Academic Integrity Policy, which covers matters such as plagiarism and
collusion and includes guidance for students;
The policy relating to mitigating circumstances which explains what you should
do if you have mitigating circumstances that have affected assessment; and
The policy on providing students with feedback on assessment.
Please click here to access the Code of Practice on Assessment and its
appendices; this link will also give you access to assessment information that is
specific to your cohort:
A summary of key assessment information is also available in the ‘Your
University’ handbook.
Marking criteria:
Marking on level 6 modules offered by the Department of Computer
Science is carried out using the following marking descriptors:
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For practical exercises
and projects
For exercises, presentations,
projects, and written
examinations:
90-100% Displays an exceptional
degree of originality and
creativity and/or
exceptional analytical and
problem solving skills.
Solution must have novel
aspects. The methodology
employed is well-developed and correct.
Shows critical understanding of
current knowledge. For level 6
this should include relevant
recent research papers.
Perceptive, focused treatment of
all issues/questions presented in
a critical and scholarly way.
80-89% Displays a level of
originality and creativity
and/or the ability to
suggest realistic solutions
to novel problems. The
methodology employed is
well-developed and correct.
Evidence of wide reading. For
level 6 this should include
relevant research papers and
books. Perceptive, focused
treatment of all issues/questions
presented in a critical and
scholarly way.
70-79%
Demonstrates ability to
analyse, interpret and
organise information to
produce coherent
accounts or solve complex
problems. All aspects of a
suitable methodology
evident and used
correctly.
Comprehensive knowledge and
understanding of the subject
together with the ability to put
the work into context and to
critically evaluate selected
aspects of the work.
Arguments/answers will be
clear, competently structured,
and accurate.
60-69%
Demonstrates ability to
analyse, interpret and
organise information to
produce coherent
accounts or solve
relatively complex
problems. Use of a
suitable methodology
evident and used
correctly, with minor
omissions.
Good knowledge and
understanding of the subject,
with no major gaps or
omissions, but minor gaps or
omissions may occur.
Arguments/answers will be
clear, competently structured,
and largely accurate.
50-59%
Displays ability to
analyse, interpret and
organise information to
produce coherent
accounts or solve well-
defined problems of some
scope. Most aspects of a
suitable methodology
evident and used
correctly, some omissions
occur but without
negative impact on the
result of the work.
Satisfactory knowledge and
understanding of the essentials
of the subject, with an ability to
integrate information into a
clear, well-structured account,
but lacking in breadth or depth,
or with some significant aspects
omitted. Arguments/answers
must be clear, although they
may not be well-developed or
reflect a wider appreciation of
the subject. Some errors and
omissions are likely to be present.
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40-49%
Demonstrates an ability to
solve limited, well-defined
problems of a familiar
type. Most aspects of a
suitable methodology
evident, but minor flaws
in its use or omissions
with some negative
impact on the result of
the work.
General knowledge and
understanding of the subject but
very limited in depth or breadth.
Arguments/answers are likely to
be somewhat lacking in
structure. There are likely to be
errors and omissions and the
evidence provided to support
arguments will be very limited.
35-39%
Fails to demonstrate an
ability to solve limited,
well-defined, problems of
a familiar type. Aspects of
a suitable methodology
evident, but flaws in its
use or omissions which
negatively impact on the
result of the work.
Knowledge and understanding
of the subject are fragmentary,
some aspects showing a very
basic level of understanding but
other aspects displaying
fundamental errors.
Arguments/answers are lacking
in structure. There are errors
and omissions and the evidence
provided to support arguments
is very limited.
30-34%
Fails to demonstrate an
ability to solve simple,
well-defined problems of a
familiar type. Lack of the
use of a suitable
methodology or flaws in
its use which negatively
impact on the result of
the work.
Knowledge and understanding
of the subject are fragmentary,
with an insufficient number of
aspects showing a very basic
level of understanding and too
many aspects displaying
fundamental errors and
omissions. Arguments/answers
are lacking in structure. There
are errors and omissions and
the evidence provided to
support arguments is very
limited.
20-29%
Fails to demonstrate an
ability to solve simple,
well-defined, problems of
a familiar type under
guidance. Serious lack of
the use of a suitable
methodology or flaws in
its use which negatively
impact on the result of the work.
Very limited range of knowledge
with many important gaps and
omissions. Shows incomplete
understanding with numerous
errors of interpretation.
Arguments/
answers have little structure,
contain serious errors, and
there is no support for
arguments.
10-19%
Little evidence of the use
of a suitable
methodology.
Shows only the most limited
and fragmentary knowledge of
the subject with little or no
understanding of essential
principles and concepts. Work is
likely to be unstructured and ill-
presented. Arguments/ answers
are only loosely related to
issues/questions or only cover a
seriously inadequate part of the
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issues/questions.
0-9%
No evidence of the use of
a suitable methodology.
Virtually devoid of any evidence
of knowledge or understanding
of the subject. No or almost no arguments/answers.
Marking on level 7 modules offered by the Department of Computer
Science is carried out using the following marking descriptors:
Grade
Description
Key features
Outstanding
80%+
Outstanding work. Factually almost
faultless; clearly directed; logical;
comprehensive coverage of topic;
strong evidence of reading/research
outside the material presented in the
programme; substantial elements of
originality and independent thought; very well written.
Distinction
Grade:
Originality; Well-
directed
independent
thought
Excellent
70%-79%
Excellent work. Logical;
enlightening; originality of thought or
approach; good coverage of topic;
clear, in-depth understanding of
material; good evidence of outside
reading/research; very well written
and directed.
Very Good
60%-69%
Very Good work. Logical; thorough;
factually sound (no serious errors);
good understanding of material;
evidence of outside reading/research;
exercise of critical judgement; some
originality of thought or approach; well written and directed.
Pass Grade:
Essentially correct
and complete:
Competence;
Critical judgement
Good
50%-59%
Good work. Worthy effort, but
undistinguished outcome. Essentially
correct, but possibly missing
important points. Largely derived
from material delivered in the
programme, but with some evidence
of outside reading/research; some
evidence of critical judgement; some
weaknesses in expression or presentation.
Marginal Fail
40%-49%
Inadequate work. Incomplete
coverage of topic; evidence of poor
understanding of material; Poor
presentation; lack of coherent
argument.
Compensatable
Fail:
Significant
weaknesses, but
serious effort
Fail
0%-39%
Unsatisfactory work: Serious
omissions; significant errors/
misconceptions; poorly directed at
targets; evidence of inadequate effort.
Fail:
Little or no
achievement of
learning outcomes
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38. Student representation and feedback:
Student representation and feedback are facilitated through:
1. The University Academic Advisor scheme.
2. The Department’s Postgraduate Staff-Student Liaison Committee
(which operates in accordance with the University's code of practice
on student representation).
3. Module questionnaires completed by students at the end of each
taught module.
4. Programme questionnaires completed by students at the end of
their studies.
Full details can be found in the Department of Computer Science Student
Handbook
Part F: Status of Professional, Statutory or Regulatory Body Accreditation
39. Status of Professional, Statutory or Regulatory Body Accreditation:
None
Part G: Diversity & Equality of Opportunity and Widening Participation
40. Diversity & Equality of Opportunity and Widening Participation:
The programme design, structure and content are consistent and
compliant with the University’s Diversity and Equality of Opportunity
Policy.
ANNEX 1
Annex Of Modifications Made To The Programme
Please complete the table below to record modifications made to the programme.
Description of
modification (please include
details of any student
consultation undertaken or
confirm that students’
consent was obtained where
this was required)
Minor or
major
modifications
Date
approved
by
FAQSC
Date
approved by
AQSC (if
applicable)
Cohort
affected
Changes for 2011-12:
COMP526 is now a required
module for entrants with a
Computer Science first
degree, and COMP523 is now
a required module for
entrants with a Computer
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Science first degree that
have previously taken
COMP323 (or an equivalent
module).
Changes for 2014/15
COMP558 (Network Games)
has been removed from the
programme curriculum.
Instead, students have more
choice in semester 2 and
they choose options totalling
30 credit points from among
the following modules:
COMP310, COMP315,
COMP524, COMP527,
provided that they take at
most two modules at level 6
in their MSc study and that
the pre-requisites are
satisfied. So far they had a
choice of one among these
four modules.
Minor