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Mastering Algorithms and Computational Thinking with Python
A full day GCSE Computer Science workshop preparing for unit 2.1 Algorithms
Workshop name: Mastering Algorithms and Computational Thinking with Python
Duration: Full day
Objectives:
- Understand the principles of computational thinking: abstraction, decomposition, and algorithmic thinking
- Learn to identify inputs, processes, and outputs for a given problem
- Gain proficiency in creating, interpreting, correcting, and refining algorithms using pseudocode, flowcharts, and a high-level programming language
- Identify common errors in algorithm design and implementation
- Master standard searching algorithms (binary search, linear search) and sorting algorithms (bubble sort, merge sort, insertion sort)
Session 1: Introduction to Computational Thinking
- Welcome and Overview
- Introduction to the workshop objectives and schedule
- Importance of computational thinking in computer science
- Principles of Computational Thinking
- Explanation of abstraction, decomposition, and algorithmic thinking
- Examples illustrating each principle
- Identifying Inputs, Processes, and Outputs
- Understanding problem-solving methodologies
- Practice exercises to identify inputs, processes, and outputs for given problems
Session 2: Algorithm Design and Representation
- Structure Diagrams
- Introduction to structure diagrams for visualising algorithms
- Creating and interpreting structure diagrams
- Pseudocode and Flowcharts
- Explanation of pseudocode and flowcharts as tools for algorithm representation
- Hands-on exercises to create, interpret, correct, and refine algorithms using pseudocode and flowcharts
Session 3: Errors and Debugging
- Identifying Common Errors
- Discussion on common errors in algorithm design and implementation
- Techniques for identifying and correcting errors
- Trace Tables
- Introduction to trace tables for tracing algorithm execution
- Practice exercises to create and interpret trace tables for given algorithms
Session 4: Standard Searching Algorithms
- Binary Search
- Explanation and implementation of the binary search algorithm
- Analysis of its time complexity
- Linear Search
- Explanation and implementation of the linear search algorithm
- Comparison between binary search and linear search
Session 5: Standard Sorting Algorithms
- Bubble Sort
- Introduction to the bubble sort algorithm
- Step-by-step implementation and analysis of its time complexity
- Merge Sort
- Explanation and implementation of the merge sort algorithm
- Analysis of its time complexity and comparison with bubble sort
Session 6: Insertion Sort and Workshop Recap
- Insertion Sort
- Explanation and implementation of the insertion sort algorithm
- Analysis of its time complexity and comparison with other sorting algorithms
- Workshop Recap and Q&A
- Review of key concepts covered throughout the workshop
- Address any remaining questions or difficulties
- Additional resources for further study