Computing · Year 6

Active learning ideas

Introduction to Autonomous Systems

Active learning helps students grasp abstract ideas like autonomy by making them tangible. When Year 6 students build and test simple robots, they see firsthand how sensors and code replace human direction, turning abstract concepts into observable behaviour.

• National Curriculum Attainment Targets
• KS2: Computing - Programming and Algorithms
• KS2: Computing - Computational Thinking

• 25–45 min
• Pairs → Whole Class
• 4 activities

Activity 01

• Socratic Seminar
• 30 min · Pairs

Robot Comparison: Remote vs Autonomous

Provide pairs with remote-controlled toys and simple programmable robots like micro:bits. First, students control the toys manually through mazes. Then, they code the robots to navigate autonomously using sensors. Discuss differences in control and decision points.

Explain what makes a system 'autonomous' compared to a remote-controlled system.

Facilitation Tip

During Robot Comparison, have students physically stand where the robot would, acting out both roles to feel the difference in control.

What to look for

Provide students with a scenario, for example: 'A robot is moving forward and a wall appears directly in front of it.' Ask them to write one 'if-then' statement that describes what the robot should do and name the sensor it might use to detect the wall.

• Analyze
• Evaluate
• Create
• Social Awareness
• Relationship Skills

Activity 02

• Socratic Seminar
• 45 min · Small Groups

Decision Tree Mapping: Human vs Robot

In small groups, draw decision trees for crossing a road: one for humans, one for robots. Program a robot to follow a similar tree with light or distance sensors. Test in class obstacle course and refine based on failures.

Compare the decision-making process of a human to a simple autonomous robot.

Facilitation Tip

For Decision Tree Mapping, provide printed human and robot decision trees side by side so students can trace both paths with highlighters.

What to look for

Pose the question: 'Imagine a self-driving car encounters an unexpected situation, like a pedestrian suddenly stepping into the road. How is its decision-making process different from a human driver's?' Encourage students to discuss the role of programming versus human intuition and experience.

• Analyze
• Evaluate
• Create
• Social Awareness
• Relationship Skills

Activity 03

• Socratic Seminar
• 35 min · Small Groups

Prediction Challenges: Everyday Scenarios

Whole class brainstorms autonomous systems in homes or roads. Groups predict outcomes in scenarios like a robot vacuum in a cluttered room. Test predictions with available robots, then vote on most accurate forecasts.

Predict the benefits and challenges of autonomous systems in everyday life.

Facilitation Tip

In Prediction Challenges, ask students to volunteer as 'sensors' who shout out changes in a scenario while others adjust their predictions in real time.

What to look for

Show students a simple flowchart for a robot navigating a path with an obstacle. Ask them to trace the path the robot would take, explaining each decision point based on the 'if-then' rules provided in the flowchart.

• Analyze
• Evaluate
• Create
• Social Awareness
• Relationship Skills

Activity 04

• Socratic Seminar
• 25 min · Individual

Algorithm Design: Simple Patrol Bot

Individuals design an algorithm for a robot to patrol a square path autonomously. Code it using block-based tools, test on floor mats, and share successes or tweaks with the class.

Explain what makes a system 'autonomous' compared to a remote-controlled system.

Facilitation Tip

When designing the Algorithm for a Patrol Bot, insist students write commands in plain English first before translating them into code.

What to look for

Provide students with a scenario, for example: 'A robot is moving forward and a wall appears directly in front of it.' Ask them to write one 'if-then' statement that describes what the robot should do and name the sensor it might use to detect the wall.

• Analyze
• Evaluate
• Create
• Social Awareness
• Relationship Skills

A few notes on teaching this unit

Teachers should start with concrete comparisons before introducing abstract concepts. Hands-on building and testing reveal the limits of simple algorithms, which students naturally question and refine. Avoid rushing to theory—instead, let surprises from live tests drive deeper discussion. Research shows that when students debug their own robots, they internalise computational thinking more deeply than through demonstration alone.

Students will confidently explain the difference between remote-controlled and autonomous systems. They will use if-then logic to program a basic robot and justify their sensor choices. Misconceptions about human-like decision-making will be replaced with clear understanding of rule-based responses.

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Watch Out for These Misconceptions

• During Robot Comparison, students may say that the autonomous robot is 'smart enough to figure things out on its own'.

  Use the two robots side by side. Have students physically block the autonomous robot and ask, 'Why did it stop?' Direct them to notice the obstacle sensor and the programmed rule, not intelligence.

• During Decision Tree Mapping, students may claim that autonomous robots make decisions 'just like people' when faced with choices.

  Have students compare their hand-drawn human decision tree with the robot’s flowchart. Ask them to point to where feelings or past experiences appear on the robot’s tree—then highlight their absence.

• During Prediction Challenges, students may assume that an autonomous system can handle any situation it encounters.

  After testing a scenario where the robot fails, ask students to revise the if-then logic in small groups. Focus their attention on the limits of sensor data and the need for human-designed rules.

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Methods used in this brief

• Socratic Seminar