Module: Programming for Mathematics

Module Specifications

Academic Year 2025 - 2026

Module Title	Programming for Mathematics
Module Code	CSC1168 (ITS: CA167A)
Faculty	Engineering & Computing	School	Computing
NFQ level	8	Credit Rating	5

Description

This module aims to give the students a foundation in programmatic problem solving and procedural programming in Python. While Introductory, the focus is on thorough understanding of the basic concepts. Students have weekly, automatically low stakes assessed programming exercises which provide immediate formative feedback, to develop competence and practical skills in the concepts being covered. These will culminate in a Python programming portfolio. This enables the students to bring themselves up to date, before moving on. Summative assessment includes two laboratory exams. A final summative exam at the end of the Semester which will assess concepts, constructs and practice of programming in Python

Learning Outcomes

1. Analyse a problem and write its solution using in Python programming language
2. Write programs and run them from the command line.
3. Write programmes in Python using the programming structures Sequence, Selection and Iteration
4. Distinguish correct program behaviour from incorrect behaviour (debug, locate and fix errors at compile or runtime)
5. Write programmes using advanced data types and their methods in Python (Strings, Lists, Dictionaries, Input/Output Streams, Files )
6. Implement basic programming idioms, such as linear search of an aggregate in Python

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Lecture	24	Blended Delivery (Online/Campus) based lectures and demonstrations
Tutorial	24	Small group tutorials to work through laboratory tasks
Laboratory	4	Programming Lab Exams
Laboratory	24	Drop In Programming Labs with tutor support
Independent Study	49	Independent learning and programming portfolio development
Total Workload: 125

Section Breakdown
CRN	11938	Part of Term	Semester 1
Coursework	50%	Examination Weight	50%
Grade Scale	40PASS	Pass Both Elements	N
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Brian Davis	Module Teacher

Type	Description	% of total	Assessment Date
Assessment Breakdown
Laboratory Portfolio	Programming Portfolio in Python - Semester 1 Lab Assignments. Students should be able to design an algorithm and write a programme using Sequence, Selection and Iteration. they should also be familiar with reading and understanding simple Python code.	5%	Every Week
Loop Exam	Python Lab Exam 1: Students sit a lab exam after covering sequence, selection, iteration (including linear search) . Designed to assess their understanding and ability to implement these features. Occurs at Week 6 although this may vary due to public holidays and university closure.	15%	Week 6
Loop Exam	Python Lab Exam 2: Students sit a lab exam after covering lists, functions, dictionaries, file processing. Designed to assess their understanding and ability to implement these features. Occurs towards Week 11 although this may vary due to public holidays and university closure.	20%	Week 11
Formal Examination	End-of-Semester Final Examination - Computer Based Lab Exam	60%	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

Python Programming Fundamentals
Writing, running and debugging Python programs. Basic data types including numeric types, booleans and strings, the operations on those types, their operators and their precedence. Python arrays and tuples and their operations. Selection and Iteration. Defining and calling functions in Python Text-oriented input/output from standard input and to standard output.

Problem Solving
Computational problem solving: translate programming problems from problem statement to functional solution/implementation. The use of Python arrays and tuples in algorithms and problem solving. Introductory algorithms, including linear search, binary search, insertion sort and selection sort. Iterative solutions to basic computational problems.

Resources
With the amount of material available on-line, it is unnecessary to recommend a particular textbook. Students will be provided with detailed notes and references to third-party materials where appropriate.

Indicative Reading List

Books:

Cay S. Horstmann,Rance D. Necaise: 2019, Python for Everyone, 3e, 1119572819

Articles:
None

Other Resources

1: Website, Python Software Foundation, 2022, Python.org,