Engineering Mathematics and Scientific Computing
| Module title | Engineering Mathematics and Scientific Computing |
|---|---|
| Module code | INT1113 |
| Academic year | 2025/6 |
| Credits | 30 |
| Module staff | Dawn Elizabeth Bird (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 | 11 |
| Number students taking module (anticipated) | 40 |
|---|
Module description
This module introduces modern engineering mathematics by teaching maths alongside programming.
What you learn in this module will support mathematical content in core modules throughout your programme. You will be introduced to core mathematical tools for modelling engineering systems which will be developed further in Year 2. You will learn about statistical methods of analysis that are vital tools for 21st century’s engineers.
An elementary introduction to programming in python will be provided which will equip you with valuable data processing and modelling skills. The teaching of python will mirror mathematical content, building on knowledge of specialist packages for matrices, differential equations and statistics.
Module aims - intentions of the module
This module aims to provide you with all of 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 could help you develop new ways of engineering thinking and cutting-edge solutions to ever-changing societal challenges.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Demonstrate foundational knowledge of linear algebra, calculus, differential equations, and statistics
- 2. Demonstrate knowledge of the key principles of object orientated programming
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. Formulate engineering problems into mathematical statements (B2, B3, C2, C3, M2, M3)
- 4. Structure, write, and test computer programs to solve engineering mathematical tasks (B3, C3, M3)
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 5. Demonstrate strong quantitative and problem-solving skills (B1, C1, M1)
- 6. Demonstrate a strong foundation in scientific computing using Python (B3, C3, M3)
Syllabus plan
- Algebra (Refresher Unit)
- Functions
- Vectors
- Differentiation
- Integration
- Ordinary Differential Equations
- Matrices
- Statistics and Probability for Engineers
- Transformations - Fourier & Laplace
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 152 | 148 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled learning and teaching activities (synchronous) | 132 | Lectures and tutorials |
| Scheduled learning and teaching activities (synchronous) | 20 | Computing workshops |
| Tutorial preparation and guided independent study | 148 | Guided Independent study |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Online ELE Quizzes | 2 hours per week | 1, 5 | Online feedback |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 30 | 70 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Coursework Python workbook(s) | 30 | Approx 20 hours total | 1-6 | Written or Verbal on request |
| Written Examination | 70 | 2 exams, one after each term, January exam 1 hour 30 minutes; May exam 2 hours | 1-5 | Written |
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 | Worksheet (deferral) | 1-6 | Next assessment period |
| Exam | Exam (same duration as deferred element) | 1-5 | Next assessment period |
| N/A | Referral Exam | 1-6 | Next assessment period |
Re-assessment notes
Deferral – if you miss an assessment for reasons judged legitimate by the Mitigation Committee, the applicable assessment will normally be deferred. See ‘Details of reassessment’ for the form that assessment usually takes. When deferral occurs there is ordinarily no change to the overall weighting of that assessment.
Referral – if you have failed the module overall (i.e. a final overall module mark of less than 40%) you will be required to take a referral exam. Only your performance in this exam will count towards your final module grade. A grade of 40% will be awarded if the examination is passed.
Indicative learning resources - Basic reading
Reading list for this module:
|
Author |
Title |
Edition |
Publisher |
Year |
ISBN |
|
Stroud, K.A |
Engineering Mathematics |
8th |
Macmillan International |
2020 |
987-1-352-01027-5 paperback 987-1-352-01028-2 ebook |
|
Stroud K.A. & Booth Dexter J. |
Advanced Engineering Mathematics |
6th |
Macmillan International |
2020 |
978-1-352-01025-1 paperback 978-1-352-01026-8 ebook |
|
ELE |
https://ele.exeter.ac.uk |
||||
| 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 | 19/11/2019 |
| Last revision date | 05/06/2025 |
