6 Programming Lesson Activities for GCSE Students
Written by: Robert Hampton
Reviewed by: James Woodhouse
Published
Last updated
Contents
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
Identify the problem: The program crashes if b=0 when dividing
Modify the code to handle the division by zero
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:
What is inefficient about this approach? (String concatenation in a loop is slow.)
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:
Why is this approach more efficient?
What happens if the input contains spaces or mixed cases (e.g., “A man a plan a canal Panama”)?
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
Identify unnecessary operations (e.g., using range(len(numbers)) instead of for number in numbers).
Rewrite it for better readability and performance.
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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