Transcript
Page 1: Programme Specification Postgraduateintranet.csc.liv.ac.uk/teaching/programmes/Specifications/June-2016/CSCN.pdf · Programme Specification Postgraduate Applicable to postgraduate

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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


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