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Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title Engineering Mathematics II
Module Code EEG1008 (ITS: EM122)
Faculty Engineering & Computing School Mechanical & Manufacturing Eng
NFQ level 8 Credit Rating 5
Description

The aims of the modules are - To develop further the students’ abilities in mathematics, in particular calculus, linear algebra and complex numbers. To deepen the students’ appreciation of the central role that mathematics plays in the development and practice of engineering. To further motivate the comprehension and use of important analytical concepts, calculus methods and linear mathematics fundamental to engineering. To help students to further develop the skill of analysing problems in a rational (rigorous, logical) and methodical manner. To further develop the students’ ability to transfer their mathematical understanding (and the associated methods) to diverse engineering application areas. To develop the students’s abilities in mathematical computation, realisation and visualisation using Matlab. To help students towards self-diagnosis and self-help in filling gaps in their mathematical education.

Learning Outcomes

1. Describe in their own words, using appropriate mathematical notation and relevant engineering examples, the primary mathematical tools used in the treatment of engineering problems (e.g. notions of linearity, linear algebra and functional approximation);
2. Apply standard techniques of linear algebra, complex numbers and calculus
3. Apply a repertoire of problem-solving skills, including the ability to generalise and transfer ideas, appropriate to simple engineering applications of mathematical concepts
4. Apply self-learning skills for the use of mathematical techniques in engineering contexts, with particular reference to (i) recognising and remedying gaps in their mathematical knowledge and (ii) developing strategies for life-long learning
5. Use mathematical terminology and formulae to communicate effectively to other technically literate people


WorkloadFull time hours per semester
TypeHoursDescription
Lecture36Formal lectures
Laboratory4Matlab based practical assessment of numerical methods in mathematics
Tutorial12Review of theory through exercises
Online activity40Set of 4 online homeworks (which include immediate feedback)
Independent Study33No Description
Total Workload: 125
Section Breakdown
CRN20138Part of TermSemester 2
Coursework25%Examination Weight75%
Grade Scale40PASSPass Both ElementsN
Resit CategoryRC3Best MarkN
Module Co-ordinatorConor BrennanModule TeacherJeremiah Murphy
Assessment Breakdown
TypeDescription% of totalAssessment Date
ParticipationComputer based Homework12.5%Every Week
In Class TestComputer based quiz12.5%Sem 2 End
Formal ExaminationEnd-of-Semester Final Examination75%End-of-Semester
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
RC1: A resit is available for both* components of the module.
RC2: No resit is available for a 100% coursework module.
RC3: No resit is available for the coursework component where there is a coursework and summative examination element.

* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Advanced vector operations/applications

Matrix Algebra

Complex Numbers

Limits and continuity

Differentiation and application including differential calculus

Extrema and sketching

Taylor series & approximation

Anti-differentiation and area

Definite and indefinite Integrals

Fundamental theorem of calculus

Applications involving the integral as a Sum

Systematic techniques for integration

Introduction to first and second order ordinary differential equations

Analytic solution methods for ODEs, Numerical methods in the solution of ODEs

Indicative Reading List

Books:
  • Anthony Croft, Robert Davison, Martin Hargreaves: 2001, Engineering mathematics, 3rd, Pearson, 970, 978-01302685-8-7


Articles:
None
Other Resources

None

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