Engineering Mathematics and Scientific Computing
| Module title | Engineering Mathematics and Scientific Computing |
|---|---|
| Module code | ENE1011 |
| Academic year | 2025/6 |
| Credits | 30 |
| Module staff | Dr Mark Callaway (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 12 | 11 |
| Number students taking module (anticipated) | 60 |
|---|
Module description
Mathematics is at the heart of all Science and Engineering subjects, providing the logical foundations and quantitative tools for modelling and analysis. The modern engineer also leverages the power of computing to solve otherwise intractable problems. This module introduces the fundamental mathematics and scientific computing skills that will underpin engineering applications throughout your programme of study.
You will learn about matrix methods, differential equations, integral transforms and statistics – mathematical tools that are vital for 21st-century engineers. Training in scientific computing with Microsoft Excel and the Python programming language will equip you with powerful modelling and data processing skills - this will mirror mathematical content, building knowledge of specialist packages to implement mathematical methods.
Module aims - intentions of the module
This module aims to provide you with the mathematical tools to tackle modern engineering problems. It will allow you to develop strong quantitative skills, such that mathematical tools become second nature so you can focus directly on engineering challenges and concepts. An important aspect of this is to provide a solid foundation in programming so that it can help you develop new ways of engineering thinking and cutting-edge solutions to ever-changing societal challenges.
Programmes that are accredited by the Engineering Council are required to meet Accreditation of Higher Education.
Programmes (AHEP4) Learning Outcomes.
The following Engineering Council AHEP4 Learning Outcomes are covered on this module (shown in brackets):
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. ILOs 1, 19 & 37 - Apply a comprehensive knowledge of mathematics and engineering principles to the solution of complex problems (B1, C1 & M1)
- 2. ILOs 2, 20 & 38 Formulate and analyse complex problems to reach substantiated conclusions (B2, C2, M2)
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. ILOs 3, 21 & 39 - Select and apply appropriate computational and analytical techniques to model complex problems (B3, C3 & M3)
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 4. ILOs 18, 36 & 54 Plan and record self-learning and development as the foundation for lifelong learning/CPD (B18, C18 & D18)
Syllabus plan
Refresher Unit on Algebra;
Functions;
Complex Numbers;
Vectors;
Matrices;
Differentiation;
Power Series;
Integration;
Fourier Series;
Ordinary Differential Equations;
Fourier Transforms & Laplace Transforms;
Statistics and Probability for Engineers.
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 88 | 212 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning and Teaching activities | 44 | Lectures: 2 hours per week |
| Scheduled Learning and Teaching activities | 22 | Computing workshops: 1 hour per week |
| Scheduled Learning and Teaching activities | 22 | Tutorials: 1 hour per week |
| Guided Independent Study | 212 | Reflection on learning and teaching activities, preparation for assessment, and further reading |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Online maths quizzes | One quiz per topic | Automated written feedback with verbal on request | |
| Computing worksheets | One worksheet per topic | Solutions provided and verbal feedback during workshops |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 30 | 70 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Coursework: Worksheets | 30 | 2 x 10-20 hours | 3-4 | Written with verbal on request |
| Exam 1 | 20 | 1 hour | 1-2 | Written with verbal on request |
| Exam 2 | 50 | 2 hours | 1-2 | Written with verbal on request |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Coursework: Worksheets | Coursework: Worksheets (2 x 10-20 hours, 30%) | 3-4 | Referral/deferral period |
| Exam 1 | Exam 1 (1 hour, 20%) | 1-2 | Referral/deferral period |
| Exam 2 | Exam 2 (2 hours, 50%) | 1-2 | Referral/deferral period |
Re-assessment notes
Referred and deferred assignments will mirror the original modes of assessment.
Indicative learning resources - Basic reading
• James, G., Modern Engineering Mathematics, 5th, Pearson Education Limited, 2015.
• Stroud, K.A., Engineering Mathematics, 7th, Palgrave Macmillan, 2013. 978-1-137-03120-4
• Sundnes, J., Introduction to Scientific Programming with Python, Springer Open, 2020ISBN 978-3-030-50356-7
Indicative learning resources - Web based and electronic resources
• ELE.
| Credit value | 30 |
|---|---|
| Module ECTS | 15 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 4 |
| Available as distance learning? | No |
| Origin date | 12/02/2025 |
| Last revision date | 13/08/2025 |