detail

Dip (PD) Mathematics

Academic Year 2016/17

A programme specification is required for any programme on which a student may be registered. All programmes of the University are subject to the University's Quality Assurance and Enhancement processes as set out in the DASA Policies and Procedures Manual.

Programme Title

Dip (PD) Mathematics

Final Award
(exit route if applicable for Postgraduate Taught Programmes)

Postgraduate Diploma

Programme Code

MTH-PD

UCAS Code

JACS Code

G100 (DESCR) 100

Criteria for Admissions

2(i) UK honors equivalent first degree in: Mathematics, or a related discipline. Applicants with non-standard qualifications will be considered on an individual basis.
International applicants or applicants who have not completed their primary or higher degree at an institution where the language of instruction and of assessment is English, will require an IELTS test with an overall score of 6.0 and a minimum of 5.5 in each of the four test components (taken within the past two years), or an alternative English Language qualification acceptable to the University. Non-EEA nationals must also meet UK visa requirements. For details of alternative qualifications which may be acceptable for both University and immigration purposes

ATAS Clearance Required

No

Health Check Required

No

Portfolio Required

Interview Required

Mode of Study

Full Time

Type of Programme

Postgraduate

Length of Programme

1 Academic Year(s)

Total Credits for Programme

60

Exit Awards available

INSTITUTE INFORMATION

Awarding Institution/Body

Queen's University Belfast

Teaching Institution

Queen's University Belfast

School/Department

Mathematics & Physics

Framework for Higher Education Qualification Level 
http://www.qaa.ac.uk/publications/information-and-guidance

Level 7

QAA Benchmark Group
http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/subject-benchmark-statements

Mathematics, Statistics and Operational Research (2015)

Accreditations (PSRB)

Date of most recent Accreditation Visit

External Examiner Name:

External Examiner Institution/Organisation

Professor D A Jordan

University of Sheffield

Professor Y Fyodorov

Queen Mary, University of London

REGULATION INFORMATION

Does the Programme have any approved exemptions from the University General Regulations
(Please see General Regulations)

N/A

Programme Specific Regulations

Students are permitted one resit of each module, if having failed a module a student chooses to proceed to the next stage before the resit results of that module are known they do so at their own risk.
Students are normally only allowed two attempts at passing a module

Students with protected characteristics

N/A

Are students subject to Fitness to Practise Regulations

(Please see General Regulations)

No

EDUCATIONAL AIMS OF PROGRAMME

To train both UK and overseas graduates in a range of topics of pure and applied mathematics at an advanced level

To equip graduates with the necessary base, including, through an extended independent investigation, research skills, upon which to embark on a research degree in a mathematical subject

To develop the knowledge and skills of graduates to further their prospects for a career as professional mathematician or mathematics-oriented professional

LEARNING OUTCOMES

Learning Outcomes: Cognitive Skills

On the completion of this course successful students will be able to:

Demonstrate proficiency in the conduct of small investigations at all stages from set-up to final report

Teaching/Learning Methods and Strategies

Cognitive skills associated with mathematics programmes are embedded within every single module, as formal reasoning underpins any mathematics module and additional mathematical modelling skills are a fundamental outcome associated with each module.

Methods of Assessment

Assessed as part of the introduction to research and project modules

Learning Outcomes: Knowledge & Understanding

On the completion of this course successful students will be able to:

Demonstrate knowledge and understanding of advanced-level topics in at least one of the following areas: pure mathematics, applied mathematics

Teaching/Learning Methods and Strategies

The knowledge required is provided to students during formal lectures, which are supplemented with tutorials and assignments that have as aim for student to develop understanding about the topics and the ability to apply the knowledge. Some modules are further supported by practical classes. Tutorials, assignments and practical classes offer students to opportunity to receive feedback on their work and their development.

Methods of Assessment

Coursework, practical work and formal examinations

Learning Outcomes: Subject Specific

On the completion of this course successful students will be able to:

Use abstract mathematical concepts

Teaching/Learning Methods and Strategies

The subject-specific skills associated with mathematics programmes are embedded within every single module, as formal reasoning underpins any mathematics module and additional mathematical modelling skills are a fundamental outcome associated with each module.

Methods of Assessment

Subject-specific skills are implicitly assessed within each mode of assessment, such as exams, coursework and practical work, as higher levels of skill in understanding abstract mathematical concepts.

Learning Outcomes: Transferable Skills

On the completion of this course successful students will be able to:

Use appropriate computational tools efficiently in the solution of mathematical problems, where applicable, and in the presentation of these

Teaching/Learning Methods and Strategies

Computation can form a part of topics covered in the introduction to research modules. Computation is also a key component of the “Methods for partial differential equations” module.
Computer technology is also used extensively for dissemination of project findings through word-processing (and presentation?) software in the introduction to research modules.

Methods of Assessment

The use of computation is assessed directly in modules with a numerical analysis content, and can also be employed in the introduction to research module.
The use of word-processing (and presentation?) software is embedded within the assessment of the introduction to research modules

Learning Outcomes: Cognitive Skills

On the completion of this course successful students will be able to:

Analyse problems and situations in mathematical terms

Teaching/Learning Methods and Strategies

Cognitive skills associated with mathematics programmes are embedded within every single module, as formal reasoning underpins any mathematics module and additional mathematical modelling skills are a fundamental outcome associated with each module.

Methods of Assessment

The analysis skills are assessed indirectly in any module, including the introduction to research modules, through the ability to identify what methods are required to answer problem questions.

Apply mathematical knowledge accurately in the solution of examples and problems

Teaching/Learning Methods and Strategies

The quality of an answer is directly compatible with the degree to which these cognitive skills have been developed through student interaction with the material in assignments and scheduled classes

Methods of Assessment

The skills to apply mathematical knowledge accurately is assessed in any module, including the introduction to research modules, through the ability to apply the knowledge in more confined and in looser contexts. Higher-level skills will result in higher marks through increased accuracy and an increase in the range of problems that a student is able to obtain solutions to.

Learning Outcomes: Knowledge & Understanding

On the completion of this course successful students will be able to:

To read and master topics presented in the mathematical literature. Initiate mathematical research

Teaching/Learning Methods and Strategies

The introduction to research modules aims to develop students’ problem solving-skills, their reporting skills and their skill in using literature resources through individual and group work

Methods of Assessment

Dissertations and oral presentation within the introduction to research modules

Learning Outcomes: Subject Specific

On the completion of this course successful students will be able to:

Demonstrate awareness of the applications of advanced-level mathematics within science at large, as appropriate to the mathematics studied
Demonstrate high-level analytic reasoning
competently

Teaching/Learning Methods and Strategies

At more advanced levels of mathematics, the material presented will become increasingly abstract, requiring greater need and opportunity through lectures, tutorials, assignments and the introduction to research modules to become familiar with abstract thinking.

Methods of Assessment

Subject-specific skills are implicitly assessed within each mode of assessment, such as exams, coursework and practical work, as higher levels of skill in understanding abstract mathematical concepts

Use a range of mathematics-oriented computational tools

Teaching/Learning Methods and Strategies

The introduction to research and computer practical will provide opportunities for students to develop skills in the use of computer tools to assist mathematical research.

Methods of Assessment

Understanding how problems can be phrased in mathematical terms, analytic mathematical reasoning and use of IT will lead to higher-quality assessment submissions.

Learning Outcomes: Transferable Skills

On the completion of this course successful students will be able to:

Explain advanced-level mathematics to a non-specialist audience in both oral and written form

Teaching/Learning Methods and Strategies

Students in the introduction to research module have an opportunity to give an oral presentation. Appropriate supervisors in the introduction to research modules will also provide the student with opportunities to obtain feedback on their reports.

Methods of Assessment

This is primarily assessed in the introduction to research modules through the dissertation and the oral presentation.

Adopt an analytical approach to problem solving

Teaching/Learning Methods and Strategies

The development of an analytic approach to problem solving is embedded within every single module in the programme, as the underpinning formal reasoning skills are catered for in any mathematics module. The additional mathematical techniques for solving certain types of problems are a fundamental outcome associated with each module.
The quality of answers is directly compatible with the degree to which an analytic approach has been developed through student interaction with the material in assignments and scheduled classes

Methods of Assessment

The analytical skills in problem solving are assessed indirectly in any module, including the project modules, through the ability to identify what methods are required to answer problem questions. Higher-level skills will result in higher marks through better transfer of mathematics from one context to another

Learning Outcomes: Knowledge & Understanding

On the completion of this course successful students will be able to:

Demonstrate accuracy in reasoning and/or modelling within these advanced-level topics

Teaching/Learning Methods and Strategies

The knowledge required is provided to students during formal lectures, which are supplemented with tutorials and assignments that have as aim for student to develop understanding about the topics and the ability to apply the knowledge. Some modules are further supported by practical classes. Tutorials, assignments and practical classes offer students to opportunity to receive feedback on their work and their development.

Methods of Assessment

Coursework, practical work and formal examinations

MODULE INFORMATION

Programme Requirements

Module Title

Module Code

Level/ stage

Credits

Availability

Duration

Pre-requisite

 

Assessment

 

 

 

 

S1

S2

 

 

Core

Option

Coursework %

Practical %

Examination %

2

20

YES

12 weeks

N

YES

0%

0%

100%

1

20

YES

12 weeks

N

YES

100%

0%

0%

1

20

YES

12 weeks

N

YES

0%

0%

100%

1

20

YES

12 weeks

N

YES

0%

0%

100%

2

20

YES

12 weeks

N

YES

0%

0%

100%

1

20

YES

12 weeks

N

YES

0%

0%

100%

1

20

YES

12 weeks

N

YES

0%

25%

75%

1

20

YES

12 weeks

N

YES

0%

0%

100%

2

20

YES

12 weeks

N

YES

0%

0%

100%

2

20

YES

12 weeks

N

YES

0%

0%

100%

2

20

YES

12 weeks

N

YES

0%

0%

100%

2

20

YES

12 weeks

N

YES

0%

0%

100%

2

20

YES

12 weeks

N

YES

0%

0%

100%

1

20

YES

12 weeks

N

YES

100%

0%

0%

Notes