Module title: Intermediate Mathematics A

SCQF level: 08:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: ELE08103
Module leader: Colin McGill
School School of Engineering and the Built Environment
Subject area group: Electronics Electrical and Mathematics
Prerequisites

Module code: ELE07102 or ELE07103
Module title: Foundation Mathematics
Examples of equivalent learning: Foundation Mathematics equivalent to SCQF level 7

2018/9, Trimester 2, Face-to-Face, Edinburgh Napier University
Occurrence: 001
Primary mode of delivery: Face-to-Face
Location of delivery: MERCHISTON
Partner: Edinburgh Napier University
Member of staff responsible for delivering module: Colin McGill
Module Organiser:


Learning, Teaching and Assessment (LTA) Approach:
Learning & teaching methods including their alignment to learning outcomes
Students are taught in interactive groups. There will be many problems classes giving the student ample opportunity to tackle relevant examples. A Mathematical Computer Package is used to enhance each student's learning. Class tests will allow feedback to help the students improve their study skills.

Embedding of employability/PDP/scholarship skills
The module will enhance numeracy skills by introducing various mathematical topics requiring knowledge and understanding of fundamental ideas, together with an ability to compute a range of operations. The application of mathematics to Engineering problems is intended to improve the student's confidence. Computational skills are further engendered by the use of a Mathematical Computer Package.

Supporting equality and diversity
Twice weekly drop-in MathsPlus sessions are available to provide extra support to students. These are conducted on a one-to-one basis between a lecturer and a student, allowing any diversity of background to be taken into account.

Internationalisation
Mathematics is the universal language of Science and Engineering. The topics taught are basic to Engineering courses and are common across cultures. This includes mathematical concepts, definitions, algebraic and computational skills as well as forms of argument.

Formative Assessment:
The University is currently undertaking work to improve the quality of information provided on methods of assessment and feedback. Please refer to the section on Learning and Teaching Approaches above for further information about this module’s learning, teaching and assessment practices, including formative and summative approaches.

Summative Assessment:
1. Test in week 5 on Calculus and Matrix algebra.
2. Test in week 9 on Series, First Order Differential Equations and Eigenvalues.
3. Invigilated exam

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 126
Face To Face Centrally Time Tabled Examination 2
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Class Test 25 1,2 5 HOURS= 1, WORDS= 0
Class Test 25 2,3,4 9 HOURS= 1, WORDS= 0
Centrally Time Tabled Examination 50 1-6 14-15 HOURS= 2, WORDS= 0
Component 1 subtotal: 50
Component 2 subtotal: 50
Module subtotal: 100

Description of module content:

Calculus: further differentiation including partial differentiation and stationary values
Binomial Theorem and MacLaurin series
First order differential equations
Matrix algebra and Eigenvalues
Introduction to probability and the Normal distribution

Learning Outcomes for module:

On completion of this module you will be able to:
LO1: Perform more complex differentiation and use partial differentiation in evaluating stationary points
LO2: Perform operations of Matrix algebra and compute eigenvalues and eigenvectors
LO3: Apply the Binomial Theorem and compute MacLaurin series for simple functions
LO4: Solve first order differential equations with applications to Engineering problems
LO5: Apply laws of probability to Engineering problems.
LO6: Use the Normal distribution in an Engineering context.

Indicative References and Reading List - URL:

Please contact your Module Leader for details
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