Problem-Solving Algorithm
- Sciences
- 100 level
- 2 credit units
- 146 pages
- 10 units
This course introduces students to problem-solving strategies using computational approaches. It covers algorithms, heuristics, and the problem-solving process, emphasizing the role of algorithms, flowcharts, and pseudocode. The course explores implementation strategies like recursion, control structures, decomposition, and modularization. Students will learn program testing and debugging techniques to ensure efficient and reliable solutions. The course aims to equip learners with technical skills for handling routine problems and representing solutions in a computer-enabled format.
About this course
- Difficulty
- Intermediate
- Study hours
- 156 hours
- Maths
- Basic
- Content
- Theoretical, practical, problem solving
- Practical work
- Yes
- Assignments
- Tutor marked assessments
- Final examination
What you'll read
The real module and unit structure of CIT108, taken from the course material NOUN publishes.
One paragraph, so you can see how it reads
CIT108 · UNIT 1 ROADMAP TO SOLVING PROBLEM: TYPICAL STRATEGIES
The course materials have important dates for the early and timely completion and submission of the TMAs and attending tutorials. Learners should remember that they are required to submit all their assignments by the stipulated time and date. They should guide against falling behind in their schedules.
What you should be able to do
- Understand problem-solving strategies.
- Design algorithms using flowcharts and pseudocode.
- Apply computational approaches to solve problems.
- Implement solutions using recursion and control structures.
- Test and debug programs effectively.
- Apply decomposition and modularization techniques.
What it prepares you for
- Software Developer
- Programmer
- Systems Analyst
- Software Engineer
- Data Analyst
- Software Development
- Data Science
- Web Development
- IT Consulting
- Computer Programming
Where it gets hard
The units students slow down on, and what makes each one heavy.
- Module 1: Problem Solving Strategies
Unit 3: Computational Approaches to Problem Solving
Computational approaches require understanding of different problem-solving paradigms and their suitability for specific problems.
- Module 3: Implementation Strategies
Unit 1: Recursion
Recursion requires understanding of call stacks and base cases to avoid infinite loops and ensure proper termination.
A suggested way through it
13 weeks, about 56 hours in total. Yours will differ.
- Week 1Module 1: Problem Solving Strategies
Unit 1: Roadmap to Solving Problems: Typical Strategies · 4 hours
Understand problem-solving strategies.. Define algorithm and heuristic.. Describe common problem-solving strategies.. Explain roadblocks to effective problem-solving..
Unit 2: The Problem Solving Process · 4 hours
Understand the computer as a model of computation.. Explain the problem-solving process.. Apply the problem-solving paradigm to routine problems..
- Week 2Module 1: Problem Solving Strategies
Unit 3: Computational Approaches to Problem Solving · 4 hours
Describe computational approaches to problem-solving.. Classify computational approaches.. Evaluate computational approaches.. Apply a computational approach to solve a problem..
- Week 3Module 2: Role of Algorithms in Problem Solving
Unit 1: Abstraction as a Problem Solving Tool · 4 hours
Define abstraction as a problem-solving aid.. Understand the importance of abstraction.. Describe how to perform abstraction.. Explain types of abstraction..
- Week 4Module 2: Role of Algorithms in Problem Solving
Unit 2: Algorithms · 4 hours
Understand the concept of algorithms.. Appreciate the need for algorithms.. Describe algorithm development steps.. Develop algorithms for simple problems.. Evaluate algorithm efficiency..
- Week 5Module 2: Role of Algorithms in Problem Solving
Unit 3: Flowcharts · 4 hours
Understand flowchart concepts.. Apply symbols and notations.. Differentiate flowchart types.. Understand flowchart design conditions.. Undertake simple flowcharting problems..
- Week 6Module 2: Role of Algorithms in Problem Solving
Unit 4: Pseudocode · 4 hours
Understand pseudocode relevance.. Apply pseudocode rules.. Demonstrate pseudocode skills.. Address simple problems..
- Week 7Module 3: Implementation Strategies
Unit 1: Recursion · 4 hours
Understand recursion.. Apply recursion to implement a solution.. Avoid circularity in recursion.. Explain recursion workings and overhead..
- Week 8Module 3: Implementation Strategies
Unit 2: Control Structure: Selection and Iteration · 4 hours
Explain control structures.. Apply selection control.. Implement solutions using iteration.. Combine control structures..
- Week 9Module 3: Implementation Strategies
Unit 3: Decomposition and Modularisation · 4 hours
Appreciate decomposition and modularisation.. Understand decomposition approaches.. Justify modularisation motivations.. Describe modularisation properties.. Discuss modularisation advantages..
- Week 10Module 3: Implementation Strategies
Unit 4: Testing and Debugging · 4 hours
Define and classify program testing.. Explain testing properties.. Appreciate the need for testing.. Understand debugging process and errors.. Apply debugging strategies..
- Week 11Module 1: Problem Solving Strategies
Unit 1: Review of Problem Solving Strategies · 4 hours
Review problem-solving strategies and algorithm design.. Practice algorithm development for various problems..
- Week 12Module 2: Role of Algorithms in Problem Solving
Unit 2: Mastering Flowcharts and Pseudocode · 4 hours
Consolidate understanding of flowcharts and pseudocode.. Apply flowcharts and pseudocode to solve practical problems..
- Week 13Module 3: Implementation Strategies
Unit 3: Advanced Implementation and Debugging Techniques · 4 hours
Practice implementation strategies, testing, and debugging.. Work on assignments and prepare for final examination..
Preparing for the exam
- Create flowcharts and pseudocode for key algorithms.
- Practice solving problems using different computational approaches.
- Review and understand the different types of control structures.
- Focus on testing and debugging techniques.
- Understand the concepts of decomposition and modularization.
- Practice past examination questions and tutor-marked assignments.
Questions students ask about this course
What is CIT108 about?
This course introduces students to problem-solving strategies using computational approaches. It covers algorithms, heuristics, and the problem-solving process, emphasizing the role of algorithms, flowcharts, and pseudocode. The course explores implementation strategies like recursion, control structures, decomposition, and modularization. Students will learn program testing and debugging techniques to ensure efficient and reliable solutions. The course aims to equip learners with technical skills for handling routine problems and representing solutions in a computer-enabled format.
How many units does CIT108 have?
CIT108, Problem-Solving Algorithm, has 10 units across 3 modules, over 146 pages of course material. You can read it one unit at a time.
How many credit units is CIT108?
CIT108 carries 2 credit units, at 100 level in Sciences.
Is CIT108 hard?
CIT108 is rated intermediate level, with basic mathematical content. It is mostly theoretical, practical and problem solving work, and it has a practical component.
How long does CIT108 take to study?
About 156 hours of study, spread across its 10 units.
How is CIT108 assessed?
CIT108 is assessed by assignments, tutor marked assessments and final examination.
What can I do with CIT108?
Software Developer, Programmer, Systems Analyst, Software Engineer and Data Analyst.