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A. NATURE OF THE AWARD
Awarding Institution: Kingston University
Programme Accredited by: Institute of Mathematics and its Applications
Final Award(s): BSc (Hons)
Intermediate Awards: CertHE, DipHE, Ordinary Degree
Field Title: Mathematics
FHEQ Level: Honours
Credit rating by level: Minor field: 45 credits @ level 1, 45 credits @ level 2 and 45 credits at level 3
Half field: 60 credits @ level 1, 60 credits level 2 and 60 credits @ level 3
Major field: 75 credits @ level 1, 75 credits @ level 2 and 75 credits @ level 3
JACS code: G1000
QAA Benchmark Statement(s): The Mathematics Field described below complies with the MSOR Subject Benchmark Statement (QAA 2002).
Minimum Registration: 3 years
Maximum Registration: 9 years
Faculty: Computing Information Systems & Mathematics
School: N/A
Location: Penrhyn Road
Date Specification Produced November 2004
Date Specification Revised: November 2004
B. FEATURES OF THE FIELD
Title:
The field is available in the following forms:
 BSc (Hons) Mathematics with x
BSc (Hons) Mathematics and x
BSc (Hons) x with Mathematics
where x is a second subject.
2. Modes of Delivery
The field is may be studied in the following alternative patterns
 Full time
 Part time
Mathematics is offered as a three year full time course, although it is possible for students to switch between full time and part time mode attendance.
3. Features of the Field
The School of Mathematics offers a field (with minor, major and half modes) in Mathematics (MA) within the Joint Honours programme of the Undergraduate Modular Scheme (UMS). The MA field can be combined with fields in Computing, Economics, Environmental Studies, French, Geography, Human Geography, Internet Computing or Statistics (in half mode only). In addition, the major using a slightly modified list of options, combined with the minor in Business leads to a degree in Mathematics with Business (SJMATWBUS).
C. EDUCATIONAL AIMS OF THE FIELD
In keeping with the ethos of the School, the field will cover the fundamental mathematical and statistical methods students interested in solving scientific or business problems require, together with the development of the necessary computing and analytical skills. The field will constitute a coherent, academically sound programme of study which will assist students in their general personal development and produce graduates suited for employment in many careers where mathematical, statistical or computing skills are used, or to go onto postgraduate studies. Embedded within the provision is the opportunity for the development of a range of key skills.
There will be three main strands to the core of the field, these being:
the study of differential equations;
use of mathematical and numerical methods;
the approach of mathematical modelling.
Numerical methods will be integrated into modules containing analytical methods, but successful students will not be able to opt out of either of these topics.
The field shares the general aims and objectives of the UMS and the particular aims and objectives applicable to all Joint degrees in the Faculty of Science. The MA field aims will be to develop students abilities to:
a. attain a body of knowledge and skills in the mathematical sciences in order to understand the basic principles and methods of the subject and the ability to apply them to a range of problems in business, science or engineering;
b. identify relationships between the various subject areas in the mathematical sciences they have studied;
c. seek, use and communicate relevant information effectively in oral, visual and written forms;
d. work in groups and individually, and to work for and with nonmathematicians;
e. extend their knowledge in the mathematical sciences by further formal study (for academic or professional qualifications) or by effective use of published work.
Specific aims for each module within the field are given in the module descriptions.
D. LEARNING OUTCOMES (OBJECTIVES) OF THE FIELD
The learning outcomes of the MA field are to produce graduates who are able to:
1. Knowledge and Understanding
demonstrate an appropriate mastery of theory and techniques of the mathematical sciences to be able to apply them to a variety of problems;
2. Cognitive (thinking) Skills
formulate problem solutions;
identify appropriate mathematical methods and any relevant computer applications, to assist in the solution of problems;
demonstrate research skills;
3. Practical Skills
All students develop practical skills at level 1 in a core computing module. These are subsequently used in MA modules which have computing packages embedded as tools.
4. Key Skills
On completion of the field students will have acquired transferable skills to:
a. Communication Skills
receive and respond to a variety of information e.g. taking part in discussions; selecting, extracting and collating information from appropriate sources; presenting information in a variety of formats/media;
b. Numeracy
apply numerical skills and techniques to quantitative situations e.g. collecting data (where appropriate); evaluating quantitative data; performing basic calculations;
c. Information, Communication and Technology
make effective use of computer systems to aid data manipulation and presentation e.g. presenting different forms of information; searching for and storing information; online communication;
d. Teamwork
work effectively as a member of a team, appreciating the value of their own and others contributions;
e. Independent Learning
display self management and organisation leading to attainment of objectives within timelines and personal development e.g. developing research and information handling skills; developing self awareness; monitoring and reviewing own progress.
Table 1 below identifies the key skills associated with summative assessment components for core modules and options from the subject areas of Mathematics, Statistics and Computing. It should be recognised that, in addition, students will be developing these skills extensively away from these summative assessment exercises: in classes, in formative assessment exercises, in private study and in extracurricula activities. Modules shown in bold text are core to all MA field programmes.
The learning and teaching strategies of the field seek to ensure that students learn actively and effectively, thus laying the foundation for future careers and/or further study.
CommunicationNumeracyICTTeamworkIndependent LearningLevel 1MA1010AMathematical Science IC, GC, G, T, EGG, EMA1020BMathematical Science IICC, T, ECEMA1030BIntroduction to Linear AlgebraC, T, ECEMA1050AModern Techniques for MathematicsII, TI, TIST1210AIntroduction to Probability and StatisticsC, T, ECEST1220BIntroductory Statistical InferenceG(R, P)G(R, P), T, EG(R, P)G(R, P)G(R, P), ECO1000AFundamental Programming Concepts I, LCI, L, TI, L, TCO1040BObjectOriented Programming with Java C, RC, RC, R, TLevel 2MA2010AMathematical Methods IC, EEMA2020BOrdinary Differential EquationsC, EEMA2030AConcepts of MathematicsC, P, RC, P, RP, RPMA2040BMathematical Modelling IG(R, O, P)G(R, O, P), TG(R, O, P)G(R, O, P)G(R, O, P)MA2110BReal Analysis IC, EEMA2120BApplied Group TheoryC, EEST2210ARegression ModellingG(R)G(R), T, EG(R)G(R)G(R), EST2220AStatistical DistributionsCC, EEST2333BExperimental DesignCC, ECC, EST2343BMedical StatisticsI(R)I(R), T, EI(R)I(R), EST2353BOperational Research TechniquesCC, ECECO2060BDatabasesG(R,O)G(R,O), TG(R,O)ELevel 3MA3010APartial Differential Equations & Approximation TheoryCC, ECC, EMA3090AMathematical Modelling IIC, G(R, O)C, G(R, O), TC, G(R, O)G(R, O)G(R, O)MA3200AMathematical ProgrammingG(R)G(R), T, EG(R)G(R)G(R), EMA3210BIntroduction to Calculus of Variations and Optimal ControlG(R, O)G(R, O), EG(R, O), EG(R, O)G(R, O), EMA3130BOptimisationCC, ECEMA3150BFunctional Analysis and Variational MethodsC, GC, G, T, EGG, EMA3170BFluid Dynamics in ActionC, EEMA3180BReal Analysis IIC, EEMA3190BSpace DynamicsC, EEMA3990A/BProjectC, D, O, RC, D, O, RC, D, O, RDC, D, O, RMA3980A/BProject (Group)C, D, O, RC, D, O, RC, D, O, RD, O, RC, D, O, RST3310ATime Series and ForecastingG(R)G(R), T, EG(R)G(R)G(R), EST3320AStochastic ProcessesI(R)I(R), C, EI(R)I(R), C, EST3333BExperimental DesignCC, ECC, EST3343BMedical StatisticsI(R)I(R), T, EI(R)I(R), EST3353BOperational Research TechniquesCC, ECEST3360BStochastic Modelling in FinanceC, I(R)C, I(R), EI(R)I(R)ST3370BFurther Inference & Bayesian MethodsCC, EEST3380BMultivariate Data AnalysisCC, ECE
Table 1  Key Skills Summary
Key:
C  Coursework Assignment,
D  Project Development,
E Examination,
I  Individual Case Study or SelfStudy/Research Exercise,
G  Group Case Study or SelfStudy,
L  Library Workbook,
O  Oral Presentation/Interview,
P  Poster Presentation,
R Report,
T  Inclass Test.
E. FIELD STRUCTURE
The MA field structure aligns with the specifications of the UMS. It is offered in minor, half and major modes with an optional work placement year between levels 2 and 3. The MA field draws on the Statistics and Computing modules for some of its provision. When it is combined with one of these as second fields, some modules which will be optional in the standalone MA field will become core in the combined programme. The opportunity for a level 1, second semester option in Mathematics with Business will offer a slight departure from the standalone MA major. These special cases of field combination are detailed in the diagrams at the end of this section. The modules at each level total to a credit value of 120 points.
The sandwich year is an optional element in the programme, taken between levels 2 and 3. Students who opt for the sandwich mode will spend a minimum period of 36 weeks in an approved placement in industry or commerce.
F. FIELD REFERENCE POINTS
Level 1
At Level 1, students will be introduced to a wide variety of topics, laying the necessary foundation for further work in this field. The study of mathematical methods will include calculus, linear algebra, ordinary differential equations, an introduction to numerical methods and exposure to symbolic algebra and linear algebra packages. Core statistics and computing modules are included to underpin those subjects and to provide prerequisites for later options. Level 1 is common to minor, half and major modes of the MA field.
In the first semester a significant proportion of the content of Mathematical Science I is designed to overlap selected Alevel material in accordance with the School aim of widening participation.
The level 1 modules contributing to the field are:
Semester A
Module TitleCodeCore/OptionMathematical Science IMA1010ACoreIntroduction to Probability & StatisticsST1210ACoreFundamental Programming ConceptsCO1000ACoreModern Techniques for MathematicsMA1050AOption
Semester B
Module TitleCodeCore/OptionMathematical Science IIMA1020BCoreIntroduction to Linear AlgebraMA1030BCore
Level 2
Three core modules will run through each of the 3 modes of the MA field at level 2. The first semester module, Concepts of Mathematics, will make students engage in logical argument, mathematical proof and the modelling cycle whilst enhancing their communication skills. Mathematical Methods I will build on the Level 1 work, introducing additional techniques and providing a foundation for numerical and analytical treatments of ordinary and partial differential equations later in the field. Then, in semester 2, the study of ordinary differential equations is extended to systems in the second semester where a symbolic algebra package will be used to assist qualitative understanding with graphical representations.
For those students on the half or major field (H/M), there will be the opportunity to extend their knowledge in one option module from Mathematical Modelling I, Real Analysis I or Applied Group Theory. Fortran90 Programming is also offered for those wishing to broaden their computing skills.
For those students on the major field (M), there will be the additional opportunity to extend their knowledge in one further option module from Regression Modelling, Operational Research Techniques or to enhance their computing proficiency with Visual Basic (or Java in the case of SJMATWBUS).
The level 2 modules contributing to the field are:
Semester A
Module TitleCodeCore/OptionMathematical Methods IMA2010ACoreConcepts of MathematicsMA2030ACoreIntroduction to Visual BasicTS2140AOption (M)Regression ModellingST2210AOption (M)Statistical DistributionsST2220AOption (M)Software Development with JavaCO2090AOption (SJMATWBUS)
Semester B
Module TitleCodeCore/OptionOrdinary Differential Equations: Analytical and Computational MethodsMA2020BCoreMathematical Modelling IMA2040BOption (H/M)Real Analysis IMA2110BOption (H/M)Applied Group TheoryMA2120BOption (H/M)Operational Research TechniquesST2353BOption (H/M)Experimental DesignST2333BOption (M)Medical StatisticsST2343BOption (M)DatabasesCO2060BOption (H/M)Fortran90 ProgrammingCO2130BOption (H/M)
Level 3
The sole core taught module on all modes of the field at Level 3 will extend the students study to partial differential equations and approximation theory. There is increasing scope for individual preferences to be followed in the MA options which include further mathematical modelling and real analysis in addition to optimisation. Students on the major mode who choose (with counselling) appropriate level 2 ST options, can progress to study topics such as medical statistics and stochastic modelling in finance. As with all the Science Faculty fields, there is a project module, usually occupying 2 of the 8 level 3 modules, although Mathematics with Business students may opt for an additional taught Business module and undertake a single semester project.
The level 3 modules contributing to the field are:
Semester A
Module TitleCodeCore/OptionPartial Differential Equations and Approximation TheoryMA3010ACoreMathematical Modelling IIMA3090AOption (H/M)Mathematical ProgrammingMA3200AOption (H/M)Stochastic ProcessesST3310AOption (M)Time Series & Forecasting MethodsST3320AOption (M)Systems Analysis & DesignCI3121Option (H/M)
Semester B
Module TitleCodeCore/OptionIntroduction to Calculus of Variations and Optimal Control TheoryMA3210BOptionOptimisationMA3130BOptionFunctional Analysis and Variational Methods for PDEsMA3150BOptionIntroduction to Fluid DynamicsMA3170BOptionReal Analysis IIMA3180BOption (H/M)Space DynamicsMA3190BOption Operational Research TechniquesST3353BOption (H/M)Experimental DesignST3333BOption (M)Medical StatisticsST3343BOption (M)Stochastic Modelling in FinanceST3360BOption (M)Further Inference & Bayesian MethodsST3370BOption (M)Multivariate Data AnalysisST3380BOption (M)
G. LEARNING AND TEACHING STRATEGIES
The learning and teaching strategies reflect the field aims and learning outcomes, student background, potential employer requirements and the need to develop a broad range of technical skills, with the ability to apply them appropriately. The strategies ensure that students have a sound understanding of some important areas in mathematics and statistics and have acquired the transferable skills expected of modernday undergraduates.
150 hours of study time is allocated to each module. Typically, this includes 55 hours of contact time per module at level 1 and 44 hours at levels 2 and 3, leaving the remainders for selfdirected or guided study time. There is more contact at level 1 to provide initial academic support and students are encouraged to develop as independent learners as they progress through their degree course. Contact time can consist of lectures, tutorials, problems classes, practicals or PAL sessions, dependent on individual module requirements. Generally, subject material and corresponding techniques will be introduced in lectures; for many modules, practical activities are regarded as essential to the understanding of the material and the development of relevant skills. In problems classes students typically work through formative exercises under guidance and in PAL sessions second year students help those at level 1 to develop their study skills.
Level 1 MA modules have an associated study guide containing core material and formative exercises. The latter, and worksheets in computing practical sessions, help develop selfpaced learning and independent study. Most higher level modules have lecture notes available in hardcopy or on BlackBoard, which is the universitys learning management system. The School produces KU Tables, which give basic mathematical and statistical formulae and a number of statistical tables; these may be used in lectures, problem classes, tests or examinations.
Students will be expected to develop their skills, knowledge and understanding through independent and group learning, in the form of both guided and selfdirected study. In most modules students will be given regular formative exercises or practical work through which they can develop learning skills, knowledge and techniques. Further they will have the opportunity to work individually and in groups on assignments, practicals, case studies and projects. These activities and their assessment are designed to enable students to meet the specific learning outcomes of the field.
A particularly important component of the degree is the project, which develops the students confidence and ability to carry out individual and/or group pieces of scholarship or research and then communicate their results in both written and oral forms. The project may be solely mathematicsbased or, preferably of an interdisciplinary nature, on a topic which draws on the integration of both fields studied.
H. ASSESSMENT STRATEGIES
Assessment enables students abilities to be measured in relation to the aims of the field; assessment also serves as a means for students to monitor their own progress at prescribed stages and enhance the learning process.
The assessment strategy has been devised to reflect the aims of the field and to complement the learning and teaching strategies described above. Throughout the field students are exposed to a range of assessment methods, thus allowing them to develop technical and key skills and enabling the effectiveness of the learning and teaching strategies to be evaluated.
The methods of assessment have been selected so as to be most appropriate for the nature of the subject material, teaching style and learning outcomes in each module. Some modules are assessed entirely by incourse work, while others have, in addition an endofmodule examination. No module is assessed by an endofmodule examination alone. In particular, the balance between the various assessment methods for each module reflects the specified learning outcomes.
The assessments are designed so that students achievements of the field learning outcomes can be measured. A wide range of assessment techniques will be used to review as accurately and comprehensively as possible the students attainments in acquiring sound factual knowledge together with the appropriate technical competence and understanding, so that they can tackle various types of problems.
Components of Assessment
In the field as a whole, the following components may be used in the assessment of the various modules:
 Multiple choice or short answer inclass tests: to assess competence in basic techniques and understanding of concepts
 Long answered structured questions in coursework assignments: to assess ability to apply learned techniques to solve simple to medium problems and which may include a limited investigative component
 Long answer structured questions in endofmodule examinations: to assess overall breadth of knowledge and technical competence to provide concise and accurate solutions within restricted time
 Practical exercises: to assess students understanding and technical competence
 Individual case studies: to assess ability to understand requirements and to provide solutions to realistic problems. The outcomes can be:
 Written report, where the ability to communicate the relevant concepts, methods, results and conclusions effectively will be assessed.
 Oral presentation, where the ability to summarise accurately and communicate clearly the key points from the work in a brief presentation will be assessed.
 Poster presentation where information and results must be succinct and eyecatching.
 Groupbased case studies: contain all of the assessment objectives of individual case studies and in addition to assess ability to interact and work effectively with others as a contributing member of a team
 Project: The individual or group project module is similar to an extended case study. The problems tackled may be of a more openended nature, allowing students to increase their knowledge of mathematics or of the second field by studying a topic in greater depth and/or by applying techniques learned in a new situation. As such the assessment here will place a greater emphasis on ability to plan work, manage time effectively, and research background information, although students will also be expected to produce written reports and to be interviewed about their work.
In addition to any specific criteria, the following features are expected in work that is submitted for coursework assignments:
 Technical competence: the generated system or solution performs the requirements stated in the best possible implementation.
 Completeness: all aspects of the work are attempted and full explanations of all reasoning are given.
 Clarity: all explanations are clear and concise. Arguments follow a logical sequence and are laid out in a clear format.
 Neatness: all reports are produced using a wordprocessor. Tables, graphs and diagrams are neat and suitably labelled. Assignments with a high mathematical content may be submitted in neat handwriting.
Assessment Procedures
It is School policy that incourse work is returned to students within three working weeks. Feedback can be model solutions and/or comments on the work. All examination papers, coursework and tests are internally moderated and those for levels 2 and 3 also externally. Projects are doublemarked; examination scripts are checked to ensure that all work has been marked and scores correctly totalled.
The formal assessment procedure is specified in the general regulations of the UMS.
Assessment Summary
Table 2 indicates the methods of assessment to be used in all the field modules. Core modules are given in bold text. Further details are given in the module descriptions.
Module TitleCodeTestsWritten
AssignmentsPractical/
Case StudyExaminationLevel 1Mathematical Science IMA1010A***Mathematical Science IIMA1020B***Introduction to Linear AlgebraMA1030B***Modern Techniques for MathematicsMA1050A**Introduction to Probability & StatisticsST1210A***Fundamental Programming ConceptsCO1000A**Level 2Mathematical Methods IMA2010A**Concepts of MathematicsMA2030A*Ordinary Differential Equations: Analytical and Computational MethodsMA2020B**Mathematical Modelling IMA2040B***(Group)*Real Analysis IMA2110B**Applied Group TheoryMA2120B**Regression ModellingST2210A**(Group)Statistical DistributionsST2220A***Operational Research TechniquesST2353B**Experimental DesignST2333B*(Group)*Medical StatisticsST2343B***Software Development with JavaCO2090A***DatabasesCO2060B*(Group)*Fortran90 ProgrammingCO2130B**Introduction to Visual BasicTS2140A**Level 3Partial Differential Equations and Approximation TheoryMA3010A**Mathematical Modelling IIMA3090A***(Group)Mathematical ProgrammingMA3200A**Introduction to Calculus of Variations and Optimal Control TheoryMA3210B**OptimisationMA3130B**Functional Analysis and Variational Methods for PDEsMA3150B**Fluid Dynamics in ActionMA3170B**Real Analysis IIMA3180B**Space DynamicsMA3190B**Stochastic ProcessesST3310A***Time Series & Forecasting MethodsST3320A*(Group)*Operational Research TechniquesST3353B**Experimental DesignST3333B*(Group)*Medical StatisticsST3343B***Stochastic Modelling in FinanceST3360B***Further Inference & Bayesian MethodsST3370B**Multivariate Data AnalysisST3380B**Systems Analysis & DesignCI3121**
Table 2  Assessment Summary (Indicative)
I. ENTRY QUALIFICATIONS
1. The minimum entry qualifications for the field are:
The general entry requirements for the field are those applicable to all programmes within the UMS.
2. Typical entry qualifications set for entrants to the field are:
For the MA field a minimum of 200 points, including two 6unit awards, with an ALevel in mathematics are required.
A foundation year is available for students without formal entry qualifications. Mature applicants and those with qualifications not specified above will be considered individually.
J. CAREER OPPORTUNITIES
In addition to providing a route to studying for higher degrees, the MA field graduate will be equipped for employment, for example, as:
Commercial, industrial and public sector managers
Business and finance associate professionals
Actuaries
Chartered accountants
Statisticians
Business analysts
Scientific and engineering professionals
Marketing, sales and advertising professionals
Teaching professionals.
K. INDICATORS OF QUALITY
School subject log, reviewed by Faculty Course Quality Assurance Committee (annual)
External examiners report, reviewed by Faculty Course Quality Assurance Committee (annual)
Field validation event panel (2002)
QAA MSOR Subject Review (2000).
L. APPROVED VARIANTS FROM THE UMS/PCF
No variations from UMS required. In addition, approved Faculty progression regulations apply.
FIELD SPECIFICATION KINGSTON UNIVERSITY
FILENAME Mathematics, major, half and minor fields 20052006
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