Core Module Information
Module title: Modelling and Computation for Smart Places

SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: ELE11117
Module leader: Stathis Tingas
School School of Computing, Engineering and the Built Environment
Subject area group: Engineering and Mathematics
Prerequisites

SQA Engineering Mathematics 4 & 5

Description of module content:

• Mathematical modelling, the scientific method and programming
• Applied linear algebra
• Differential equations
• Engineering Applications of Numerical Methods

Learning Outcomes for module:

LO1: Demonstrate knowledge of and competency in a wide range of computational and analytical methods.
LO2: Analyse the principles of mathematical modelling to engineering problems.
LO3: Propose and compose computational and analytical methods in practice by utiizing programming skills efffectively.
LO4: Critically appraise the performance of numerical methods for solving engineering problems.

Full Details of Teaching and Assessment
2022/3, Trimester 1, FACE-TO-FACE, Edinburgh Napier University
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: FACE-TO-FACE
Location of delivery: MERCHISTON
Partner: Edinburgh Napier University
Member of staff responsible for delivering module: Stathis Tingas
Module Organiser:


Learning, Teaching and Assessment (LTA) Approach:
Learning & Teaching methods including their alignment to LOs
The module covers graduate-level computational and analytical methods in mathematical modelling for engineering students, which will be taught through a combination of face-to-face lectures, tutorials and computer lab sessions. The lecture material will include relevant theory of advanced computational and analytical methods, which will be applied to the modelling of modern engineering problems (LO1 and L02). Understanding will be reinforced and supported with tutorials and computer lab sessions, allowing theoretical and computational solutions of engineering problems to be developed and discussed (LO3, LO4).

Embedding of employability/PDP/Scholarship Skills
The module content reflects current mathematical approaches and techniques used by both industry and academia. As a theoretical and computational course, it will enable students to enhance their intellectual and practical skills, along with transferable skills such as analytical thinking, report writing, communication, problem solving and programming.

Research / teaching linkages
The theory will be developed in the context of a wide range of contemporary, relevant engineering examples and applications, and supported by modern, transferrable scientific computing. Applications and examples taken from current research will form a significant part of the module and the module team will use their own research to illustrate the material delivered in the lectures and in the design of appropriate tutorials and assessments. Current staff research expertise relevant to the module is varied and ranges from multiscale modelling, nonlinear and distributed parameter control theory, through to modelling for healthcare technologies.


Formative Assessment:
Formative assessment will be part of the tutorial and laboratory sessions and will include feedback on mathematical and programming skills as well as critical thinking.

Summative Assessment:
1. Class test (LO: 1, 2)
The skills and knowledge required for the application of computational and analytical methods and mathematical modelling to engineering problems are more readily assessed in a class test.

2. Mini project (LO: 1, 2, 3, 4)
The application of all four learning outcomes to the solution of real engineering problem, and the dissemination and analysis of the solution to the problem are best assessed through the medium of a mini project.



Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Face To Face Lecture 48
Face To Face Tutorial 24
Independent Learning Guided independent study 128
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Class Test 30 1, 2 5 HOURS= 02.00, WORDS= 0
Project - Written 70 1,2,3,4 13 , WORDS= 5000
Component 1 subtotal: 100
Component 2 subtotal: 0
Module subtotal: 100
2022/3, Trimester 2, FACE-TO-FACE, Edinburgh Napier University
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: FACE-TO-FACE
Location of delivery: MERCHISTON
Partner: Edinburgh Napier University
Member of staff responsible for delivering module: Stathis Tingas
Module Organiser:


Learning, Teaching and Assessment (LTA) Approach:
Learning & Teaching methods including their alignment to LOs
The module covers graduate-level computational and analytical methods in mathematical modelling for engineering students, which will be taught through a combination of face-to-face lectures, tutorials and computer lab sessions. The lecture material will include relevant theory of advanced computational and analytical methods, which will be applied to the modelling of modern engineering problems (LO1 and L02). Understanding will be reinforced and supported with tutorials and computer lab sessions, allowing theoretical and computational solutions of engineering problems to be developed and discussed (LO3, LO4).

Embedding of employability/PDP/Scholarship Skills
The module content reflects current mathematical approaches and techniques used by both industry and academia. As a theoretical and computational course, it will enable students to enhance their intellectual and practical skills, along with transferable skills such as analytical thinking, report writing, communication, problem solving and programming.

Research / teaching linkages
The theory will be developed in the context of a wide range of contemporary, relevant engineering examples and applications, and supported by modern, transferrable scientific computing. Applications and examples taken from current research will form a significant part of the module and the module team will use their own research to illustrate the material delivered in the lectures and in the design of appropriate tutorials and assessments. Current staff research expertise relevant to the module is varied and ranges from multiscale modelling, nonlinear and distributed parameter control theory, through to modelling for healthcare technologies.


Formative Assessment:
The first formative assessment will be a 10-minute presentation on one computational approach relevant to the module, used in a peer reviewed journal paper.
The second formative assessment will be worked in groups of peers. Each group will work towards developing the algorithm and implementing the programming code for one computational approach relevant to the module.


Summative Assessment:
Mini project (LO: 1, 2, 3, 4)
The application of all four learning outcomes to the solution of real engineering problem, and the dissemination and analysis of the solution to the problem are best assessed through the medium of a mini project.



Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Face To Face Lecture 36
Face To Face Tutorial 36
Independent Learning Guided independent study 128
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Project - Written 100 1,2,3,4 13 , WORDS= 5000
Component 1 subtotal: 100
Component 2 subtotal: 0
Module subtotal: 100

Indicative References and Reading List - URL:
ELE11117 Modelling and Computation for Smart Places