SAQA

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SOUTH AFRICAN QUALIFICATIONS AUTHORITY

REGISTERED QUALIFICATION:

Bachelor of Science Honours in Mathematical Sciences

SAQA QUAL ID	QUALIFICATION TITLE
109455	Bachelor of Science Honours in Mathematical Sciences
ORIGINATOR
Sol Plaatje University
PRIMARY OR DELEGATED QUALITY ASSURANCE FUNCTIONARY			NQF SUB-FRAMEWORK
CHE - Council on Higher Education			HEQSF - Higher Education Qualifications Sub-framework
QUALIFICATION TYPE	FIELD		SUBFIELD
Honours Degree	Field 10 - Physical, Mathematical, Computer and Life Sciences		Mathematical Sciences
ABET BAND	MINIMUM CREDITS	PRE-2009 NQF LEVEL	NQF LEVEL	QUAL CLASS
Undefined	120	Not Applicable	NQF Level 08	Regular-Provider-ELOAC
REGISTRATION STATUS		SAQA DECISION NUMBER	REGISTRATION START DATE	REGISTRATION END DATE
Reregistered		EXCO 0821/24	2019-05-29	2027-06-30
LAST DATE FOR ENROLMENT		LAST DATE FOR ACHIEVEMENT
2028-06-30		2031-06-30

In all of the tables in this document, both the pre-2009 NQF Level and the NQF Level is shown. In the text (purpose statements, qualification rules, etc), any references to NQF Levels are to the pre-2009 levels unless specifically stated otherwise.

This qualification does not replace any other qualification and is not replaced by any other qualification.

PURPOSE AND RATIONALE OF THE QUALIFICATION

Purpose:
The purpose of the Bachelor of Science Honours in Mathematical Sciences is to develop critical and independent thinkers who have knowledge on how to model, analyse and solve both quantitative and qualitative problems in science and technology. Qualifying learners will be able to carry out quality research in a number of fields such as applied mathematics, mathematics and statistics. The results from the research will help in:

Shaping public policy (e.g. contraception by analysis of the birth rates, rehabilitation, education sector-qualification evaluation).

Development of new products (e.g. new insurance products).

Planning of market strategies in business (e.g. the management of investment portfolios in finance).

The qualifying learner will be equipped with problem solving skills that will enable them to:

Use a wide range of specialised skills to identify, analyse and solve abstract problems.

Draw conclusions from the results obtained. In addition, the qualification will also prepare the learner adequately for further academic endeavours and be competitive in the global market.

Rationale:
Currently there's a huge demand of mathematical scientists with skills in data analytics and mathematical modelling. This qualification will produce highly skilled graduates who are critical and independent thinkers with knowledge on how to model, analyse and solve both quantitative and qualitative problems in science and technology. The qualification will also address the lack of skills in mathematical sciences and address the shortage of mathematical scientists. This qualification also includes a research component which aims at providing learners with professional research skills that will enable them to embark on a career as a researcher.

A typical learner of this qualification is someone who has a Bachelor of Science (BSc) Degree with any of the following majors: mathematics, applied mathematics or statistics and meets the minimum requirements for entry into an Honours Degree. The qualifying learners can be employed in many industries including: finance, economics, engineering, public health, education, and medicine. In all these areas mathematical scientists work closely with other scientists and researchers to develop mathematical techniques, adapt existing techniques, design experiments, simulations and direct analyses of surveys and retrospective studies.

This qualification will equip the learner with the necessary tools and conceptual foundations in quantitative and qualitative reasoning. Today, mathematical and statistical methods are applied in most of the fields that involve decision making, for making inferences from the collected data. Mathematical skills play a vital role in the calculation of national development goals based on the availability of timely and reliable indices such as Gross Domestic Product (GDP), inflation rate and health outcomes. The mathematical skills are also important in the modelling and future predictions of issues like: drug abuse, epidemiology, climate change, traffic flow and sustainability of the grant system.

LEARNING ASSUMED TO BE IN PLACE AND RECOGNITION OF PRIOR LEARNING

Recognition of Prior Learning (RPL):
The institutional policy and procedures for the Recognition of Prior Learning (RPL) are followed. Learners can apply for RPL against a module, or part/full qualification for learning obtained through forma. Informal and non-formal learning. Learners need to submit a Portfolio of Evidence for assessment, and credits/exemption may be granted for some modules in the qualification, and/or admission may be granted into the qualification. Leanres have the opportunity to appeal against the assessment results where credits or admission were not awarded.

Entry Requirements:
The minimum entry requirement is:

A relevant Bachelor of Science qualification with mathematics or applied mathematics or statistics modules at Level 7.

RECOGNISE PREVIOUS LEARNING?

QUALIFICATION RULES

This qualification consists of three fields of specialisation with compulsory and electives modules at Level 8 totalling 120 Credits.

Compulsory modules for Applied Mathematics (90 Credits):

Numerical Linear Algebra, 15 Credits.

Differential Equations, 15 Credits.

Advanced Mathematical Programming, 15 Credits.

Finite Element Analysis, 15 Credits.

Research Project, 30 Credits.

Electives modules for Applied Mathematics (30 Credits):

Differential Geometry, 15 Credits.

Calculus of Variations, 15 Credits.

Dynamical Systems, 15 Credits.

Compulsory modules for Mathematics (90 Credits):

Discrete Algebra, 20 Credits.

Introduction to Functional Analysis, 20 Credits.

Group Theory, 20 Credits.

Research Project 1 and 2, 30 Credits Research.

Electives modules for Applied Mathematics (30 Credits):

Graph Theory, 15 Credits.

Topology, 15 Credits.

Set Theory, 15 Credits.

Compulsory modules for Statistics (90 Credits):

Advanced Generalised Linear Models, 15 Credits.

Multivariate Analysis, 15 Credits.

Bayesian Analysis, 15 Credits.

Advanced Time Series Analysis, 15 Credits.

Research Project (Year module), 30 Credits.

Electives modules for Applied Mathematics (30 Credits):

Stochastic Processes, 15 Credits.

Spatial Statistics, 15 Credits.

Operations Research Techniques, 15 Credits.

EXIT LEVEL OUTCOMES

1. Demonstrate a deep and detailed knowledge of at least one of the three streams, including a sound understanding of the theories, research methodologies and techniques/skills used in the respective stream, and a sound understanding of how such knowledge/skills is used in real life.
2. Apply problem solving skills, where the learner should be able to exhibit a wide range of methods of enquiry and their suitability to specific investigations, and the learner should be able to select and apply the most appropriate method in any given situational investigation.
3. Demonstrate critical thinking skills, progressing from a procedural and analytical understanding of mathematical sciences to logical reasoning, pattern recognition, generalisation, abstraction and communicate mathematical ideas orally, in writing, with precision, clarity and organisation, using proper terminology and notation.
4. Demonstrate the ability to use a number of software packages.

ASSOCIATED ASSESSMENT CRITERIA

Associated Assessment Criteria for Exit Level Outcome 1:

Explain how concepts in the subjects inter-relate.

Apply understanding of theories to reason inductively and deductively.

Apply knowledge, theories, research methodologies and techniques learnt or developed.

Associated Assessment Criteria for Exit Level Outcome 2:

Explore a range of methods to address a range of challenges faced within the different South African contexts or globally.

Evaluate and discuss possible solution methods for the identified challenges.

Explain the challenges faced within a specified situational investigation.

Utilise and apply methods within a specified situational investigation.

Associated Assessment Criteria for Exit Level Outcome 3:

Produce an assignment/project applying logical reasoning, pattern recognition and abstraction.

Communicate research findings orally and in writing with clarity using proper terminology and notation.

Display good analytical and logical skills showing understanding of mathematical sciences.

Apply the important principles of good ethics, professional practice and effective communication whenever carrying out any project.

Associated Assessment Criteria for Exit Level Outcome 4:

Use various software packages and programming skills.

Apply programming and software package knowledge in solving mathematical problems.

Integrated Assessment:
There are a number of on-going Formative Assessments to monitor learners' progress. These assessments help to enhance and improve teaching. Information gathered from these Formative Assessments will then serve as a basis for more formal Summative Assessments. These assessments provide data that help motivating learners to be actively involved in their own learning.

The outcomes/results of these assessments are used as a means of monitoring learner learning and also to provide feedback to individual learners and are also used to improve the curriculum and instruction methods.

Formative assessment methods may include the following components:

Group work.

Quizzes.

Class tests.

Assignments.

Class projects.

The final mark per module will comprise of the continuous assessment and the final exam. The Research Project shall be submitted for assessment at a determined date and the learner is expected to attend an oral examination of their project. The final grade of the Research Project will comprise of the oral presentation and the project mark.

In order to maintain the quality of qualification, the final examination papers are subjected to both internal and external moderation.

INTERNATIONAL COMPARABILITY

United Kingdom:

In most universities in the United Kingdom, learners are admitted into higher education institutions based on their Advanced Level results.

Country: United Kingdom:
Institution: University of Lancaster.
Qualification: Bachelor of Honours Degree in Statistics and Mathematics.

The University offers a three-year Bachelor of Honours Degree in Statistics and Mathematics with the same number of modules of the Bachelor of Science Honours in Mathematical Sciences in South Africa after combining the undergraduate modules and the one year honours modules.

Country: Australia:
Institution: Murdoch University:
Qualification: Bachelor of Science Honours (Hons) in Mathematics and Statistics.
The Australian system of education is more or less modelled on the British system. The University offers a one-year Bachelor of Science Honours (Hons) in Mathematics and Statistics to learners who have successfully completed the three-year Bachelor of Science (Mathematics and Statistics) qualification.

Country: Canada:
Institution: McGill University.
Qualification: Bachelor of Science Honours in Mathematics, Bachelor of Science Honours in Applied Mathematics and Bachelor of Science Honours in Probability and Statistics.
The Honours qualification is comparable with three honours qualifications offered by McGill University, namely:

Bachelor of Science Honours in Mathematics.

Bachelor of Science Honours in Applied Mathematics.

Bachelor of Science Honours in Probability and Statistics.

The Honours qualifications train the learners to apply mathematical and statistical ideas to solve practical problems that arise in the physical, life and social sciences.

Comparability with the above Honours Qualifications:

The Bachelor of Science Honours in Mathematical Sciences in South Africa is more or less similar to the ones offered by the other universities mentioned above. Additionally, learners will gain experience of scientific writing, and they will practise using software such as LaTeX.

ARTICULATION OPTIONS

This qualification offers the following articulation possibilities.

Horizontal Articulation:

Bachelor of Science Honours in Data Science, Level 8.

Postgraduate Diploma in Survey Data Analysis for Development, Level 8.

Vertical Articulation:

Master of Science in Applied Mathematics, Level 9.

Master of Science in Mathematics, Level 9.

Master of Science in Mathematical Statistics, Level 9.

Master of Science in Statistical Science, Level 9.

MODERATION OPTIONS

N/A

CRITERIA FOR THE REGISTRATION OF ASSESSORS

N/A

NOTES

N/A

LEARNING PROGRAMMES RECORDED AGAINST THIS QUALIFICATION:

NONE

PROVIDERS CURRENTLY ACCREDITED TO OFFER THIS QUALIFICATION:

This information shows the current accreditations (i.e. those not past their accreditation end dates), and is the most complete record available to SAQA as of today. Some Primary or Delegated Quality Assurance Functionaries have a lag in their recording systems for provider accreditation, in turn leading to a lag in notifying SAQA of all the providers that they have accredited to offer qualifications and unit standards, as well as any extensions to accreditation end dates. The relevant Primary or Delegated Quality Assurance Functionary should be notified if a record appears to be missing from here.

1.	Sol Plaatje University