Module: Computer Programming I

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title	Computer Programming I
Module Code	CA116
School	School of Computing
Module Co-ordinator	Semester 1: Stephen Blott Semester 2: Stephen Blott Autumn: Stephen Blott
Module Teachers	Stephen Blott
NFQ level	8	Credit Rating	10
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Repeat examination
Any reassessment will take the form of a single lab exam.

Description

This module introduces students to basic computer programming. Students will learn the fundamentals of computer programming, and how to write, run and debug their own programs. Students will also learn the fundamentals of computational problem solving. This module involves lectures and a significant amount of supervised laboratory work.

Learning Outcomes

1. Master the basic techniques of programmatic problem solving.
2. Write programs and run them from the command line.
3. Recognise compiler and/or runtime errors and be able to resolve errors so discovered.
4. Distinguish correct program behaviour from incorrect behaviour.
5. Debug source code, locate errors and fix them.
6. Master the following programming concepts: variables, control flow (if statements, for and while loops), functions and/or methods.
7. Understand and be able to use arrays and strings.
8. Implement basic programming idioms, such as linear search of an array.

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	36	Traditional lecture
Laboratory	48	Supervised computer programming
Directed learning	24	Unassessed directed independent learning
Assignment Completion	20	Completion of bucket-list problems
Independent Study	122	No Description
Total Workload: 250

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.

Bucket List
Students will be provided with a “bucket list” of computational problems to solve independently and at their own pace. Solutions to these bucket list problems will contribute to each student’s continuous-assessment mark.

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.

Assessment Breakdown
Continuous Assessment	60%	Examination Weight	40%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Loop Exam	Lab exam 1. This will usually take place during week six of semester, but may vary due to factors such as the delivery schedule and public holidays.	20%	Week 4
Loop Exam	Lab exam 2. This will usually take place during week twelve of semester, but may vary due to factors such as the delivery schedule and public holidays.	20%	Week 8
Loop Exam	Lab exam	20%	Week 12

Reassessment Requirement Type
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 1

Indicative Reading List

Other Resources

None

Programme or List of Programmes

COMSCI	BSc in Computer Science
DS	BSc in Data Science

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