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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:

  1. Understand the principles of computational thinking: abstraction, decomposition, and algorithmic thinking
  2. Learn to identify inputs, processes, and outputs for a given problem
  3. Gain proficiency in creating, interpreting, correcting, and refining algorithms using pseudocode, flowcharts, and a high-level programming language
  4. Identify common errors in algorithm design and implementation
  5. 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

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