6 Programming Lesson Activities for GCSE Students

Robert Hampton

Written by: Robert Hampton

Reviewed by: James Woodhouse

Published

Last updated

Teaching programming effectively means going beyond theory and giving students hands-on activities that make concepts stick. This article shares proven programming activities that engage students, help them understand key concepts, and build problem-solving skills.

Beginner Activities: Laying the Foundations

These activities introduce fundamental programming concepts in an interactive way.

1. Tracing Code with Dry Runs

Objective: Help students understand how code executes step by step.

How to do it:

  • Provide a simple program with missing outputs.

  • Ask students to trace the code and predict the output before running it.

  • Compare their predictions with actual results to highlight misconceptions.

Example: Tracing a simple Python loop that prints numbers from 1 to 5.

# Predict the output before running the code

for i in range(1, 6):

    print("Number:", i)

Reflection Questions:

  • What happens if we change the loop condition?

  • How does tracing code help debug errors?

Why is this technique effective?

Encouraging active engagement with code, rather than passively reading, means students are forced to think critically about how the program behaves. Instead of just executing a program and watching what happens, they strengthen their problem-solving skills by predicting the outcome first.

For the student, they get:

  • A deeper understanding of how programs flow

  • Improved accuracy in predicting code behaviour

  • Confidence in debugging and testing code

This technique helps students tackle GCSE exam-style questions that require code tracing and output prediction. For example, Question 7 asks, “Give the first three numbers that will be printed by the algorithm.” By practising this method, students develop the skills to accurately follow execution flow, anticipate outputs, and answer such questions with confidence.

2. Debugging Challenges

Objective: Improve students' ability to find and fix errors in code.

How to do it:

  • Give students a program with common errors (syntax, logic, runtime).

  • Ask them to identify and correct the mistakes.

  • Encourage discussion on debugging strategies.

Example: A Python function with incorrect indentation causing an error.

def greet(name):

print("Hello, " + name)

greet("Alice")

The print statement inside the function is not indented.

Example: A Python function to check if a number is even, but it incorrectly returns True for odd numbers.

def is_even(number):

    if number % 2 == 1:

        return True

    else:

        return False

print(is_even(4))  # Expected: True

print(is_even(7))  # Expected: False

The condition number % 2 == 1 should instead check for 0 to correctly identify even numbers.

Reflection Questions:

  • What types of errors did you find?

  • How can you systematically debug a program?

Why is this technique effective?

Debugging code is a vital step in software development and mirrors a real-world approach to writing programs. Students who work with broken code learn to identify common errors and understand what causes them.

For the student, they get:

  • A better problem-solving mindset

  • Improved code comprehension

  • To build persistence and resilience skills

This technique will help students with GCSE exam-style questions related to error identification and correction, trace table practice, and applying computational thinking. For example, Question 3 asks, “Complete the trace table to test the program.”. By practising this method, students develop the ability to follow code execution step by step and this improves their ability to track variable values and predict outputs.

Intermediate Activities: Building Confidence

These activities encourage students to apply their knowledge and think critically.

3. Code Modification Challenge

Objective: Reinforce understanding of how small changes affect program behaviour.

How to do it:

  • Provide a working program and ask students to modify it to meet new requirements.

  • Examples include changing a for-loop to a while-loop or modifying an if-else condition.

  • Discuss how modifications impact efficiency and readability.

Example: Editing a basic calculator program to handle division by zero.

def calculator(a, b, operation):

    if operation == "add":

        return a + b

    elif operation == "subtract":

        return a - b

    elif operation == "multiply":

        return a * b

    elif operation == "divide":

        return a / b  # Issue: Doesn't handle division by zero

    else:

        return "Invalid operation"

print(calculator(10, 5, "add"))       # Expected: 15

print(calculator(10, 0, "divide"))    # Error: Division by zero!

Student task: modify the code

  1. Identify the problem: The program crashes if b=0 when dividing

  2. Modify the code to handle the division by zero

  3. Test to ensure it works correctly

def calculator(a, b, operation):

    if operation == "add":

        return a + b

    elif operation == "subtract":

        return a - b

    elif operation == "multiply":

        return a * b

    elif operation == "divide":

        if b == 0:

            return "Error: Cannot divide by zero"

        return a / b

    else:

        return "Invalid operation"

print(calculator(10, 5, "add"))       # Output: 15

print(calculator(10, 0, "divide"))    # Output: Error: Cannot divide by zero

Reflection Questions:

  • What changes improved the program’s efficiency?

  • How can small modifications introduce new bugs?

Why is this technique effective?

Modifying and optimising code is just as important as writing new code. Rather than starting from scratch, it means students analyse existing programs, identify potential issues, and make targeted improvements.

For students, they get:

  • To learn programming flexibility

  • Improved code comprehension

  • Code efficiency & readability awareness

This technique will help students with exam-style questions that test students on the efficiency of their modifications, requiring them to identify improvements. For example, Question 6, asks “Refine the program to be more efficient.”. By practising this method, students develop the skills to confidently approach this type of question, improving their ability to adapt, debug, and optimise code effectively.   

4. Pair Programming

Objective: Develop teamwork and problem-solving skills.

How to do it:

  • Pair up students as "drivers" (writes code) and "navigators" (reviews and suggests improvements).

  • Swap roles regularly.

  • Encourage clear verbal explanations and teamwork.

Example: Working together to implement a simple guessing game in Python.

Reflection Questions:

  • How did communication impact your coding experience?

  • What challenges did you face while working in pairs?

Why is this technique effective?

Encouraging students to verbalise their thought processes, leads to a deeper understanding of programming concepts. By switching roles, students develop both technical skills (coding & debugging) and soft skills (communication & teamwork).

For students, they get:

  • Exposure to different coding styles

  • Improved confidence

  • Enhanced communication skills

Many exams require students to describe what a program does or explain a coding solution in words. Pair programming helps students develop this skill by regularly discussing their code. For example, Question 1, asks “Explain why each correction is necessary.”. This technique helps refine their communication, problem-solving, and debugging skills.

Advanced Activities: Thinking Like a Programmer

This is for students who are ready for more complex problem-solving and creativity.

5. Algorithm Design Race

Objective: Strengthen algorithmic thinking under time constraints.

How to do it:

  • Give students a problem (e.g., sorting a list, finding the largest number).

  • Set a time limit to design the most efficient algorithm before coding it.

  • Compare different approaches and discuss efficiency.

Example: Write an efficient algorithm to check if a given word or phrase is a palindrome (reads the same forward and backwards).

def is_palindrome(word):

    reversed_word = ""

    for char in reversed(word):

        reversed_word += char

    return word == reversed_word

print(is_palindrome("racecar"))  # Expected: True

print(is_palindrome("hello"))    # Expected: False

Ask students:

  1. What is inefficient about this approach? (String concatenation in a loop is slow.)

  2. How can we make it faster?

def is_palindrome(word):

    return word == word[::-1]

print(is_palindrome("racecar"))  # Expected: True

print(is_palindrome("hello"))    # Expected: False


Discussion points:

  1. Why is this approach more efficient?

  2. What happens if the input contains spaces or mixed cases (e.g., “A man a plan a canal Panama”)?

  3. How would you modify it to handle phrases?

Reflection Questions:

  • What was the most challenging part of designing your algorithm?

  • How does efficiency differ between solutions?

Why is this technique effective?

By working under time constraints, students learn to quickly devise and refine solutions, balancing efficiency, correctness, and clarity. The competitive element keeps engagement high, while discussions afterwards reinforce key programming concepts like algorithm complexity and optimisation.

For the student, they get:

  • Improved problem-solving speed

  • Code optimisation skills

  • Stronger algorithmic thinking skills

Many exams require students to write an algorithm to solve a given problem efficiently. This activity provides practice in designing, structuring, and refining solutions. For example, Question 1a, asks “Create a function…”. By practising this method, students develop development speed, efficiency, and critical thinking skills, helping them get comfortable with solving problems under strict time limits.

6. Improving Code Efficiency and Readability

Objective: Teach students to improve code quality without changing functionality.

How to do it:

  • Provide a working but inefficient program.

  • Ask students to rewrite it for better readability and performance.

  • Discuss why writing clean code matters.

Example: Improving an inefficient loop structure to find the largest number in a list.

def find_largest(numbers):

    largest = numbers[0]

    for i in range(len(numbers)):

        if numbers[i] > largest:

            largest = numbers[i]

    return largest

print(find_largest([3, 7, 2, 9, 5]))  # Expected: 9


Student task: Improve the efficiency

  1. Identify unnecessary operations (e.g., using range(len(numbers)) instead of for number in numbers).

  2. Rewrite it for better readability and performance.

  3. Ensure the function still works correctly.

def find_largest(numbers):

    largest = numbers[0]

    for number in numbers:

        if number > largest:

            largest = number

    return largest

print(find_largest([3, 7, 2, 9, 5]))  # Output: 9

Reflection Questions:

  • What made your improved code better?

  • How does readability impact debugging?

Why is this technique effective?

Many beginner programmers focus on making their code work but overlook efficiency and readability, which are essential for maintainable, scalable programs. This technique encourages students to think critically about code optimisation, best practices, and debugging, which are important both in exams and in real-world programming.

For students, they get:

  • Improved readability & maintainability

  • Introduction to algorithm optimisation

  • Critical thinking and refactoring skills

Many questions ask students to write complex programs that demonstrate a variety of programming skills, a skill honed through this activity. For example, Question 16, asks “Write an algorithm that…”. By practising code efficiency and readability improvements, students develop skills in optimisation, clarity, and debugging, all of which directly support their success in exam-style programming questions.

Conclusion

Teachers can make programming engaging and practical for GCSE students by incorporating these hands-on activities into lessons. These activities reinforce key concepts, develop problem-solving skills, and prepare students for real-world coding challenges.

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Robert Hampton

Author: Robert Hampton

Expertise: Computer Science Content Creator

Rob has over 16 years' experience teaching Computer Science and ICT at KS3 & GCSE levels. Rob has demonstrated strong leadership as Head of Department since 2012 and previously supported teacher development as a Specialist Leader of Education, empowering departments to excel in Computer Science. Beyond his tech expertise, Robert embraces the virtual world as an avid gamer, conquering digital battlefields when he's not coding.

James Woodhouse

Author: James Woodhouse

Expertise: Computer Science

James graduated from the University of Sunderland with a degree in ICT and Computing education. He has over 14 years of experience both teaching and leading in Computer Science, specialising in teaching GCSE and A-level. James has held various leadership roles, including Head of Computer Science and coordinator positions for Key Stage 3 and Key Stage 4. James has a keen interest in networking security and technologies aimed at preventing security breaches.

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