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⭐ Teacher-created lesson guideFour lessons that take learners on a journey from understanding what the Internet of Things is, through to exploring how IoT is used in industry and commerce, and finally coding their own sensors using Micro:Bits. Each lesson connects real-world data — including live sensor readings from the learners’ own school — to wider contexts in science, technology, numeracy and literacy.
Lesson overview
CfE experiences and outcomes
- NumeracyMNU 2-10bCarry out practical tasks and investigations involving timed events and explain which unit of time would be most appropriate to use.
- NumeracyMNU 2-20aInterpret and draw conclusions from data displayed in a variety of ways, recognising that the presentation may be misleading.
- MathsMTH 2-21aDisplay data in a clear way using a suitable scale, choosing from tables, charts, diagrams and graphs, using technology effectively.
- LiteracyENG 2-27aUse language and style in a way which engages and/or influences the reader.
- LiteracyLIT 2-02aRespond in ways appropriate to role, show that others’ contributions are valued and use these to build on thinking.
- LiteracyLIT 2-14aFind, select and sort information from a variety of sources and use this for different purposes.
- LiteracyLIT 2-25aUse notes and other types of writing to understand information and ideas, explore problems, make decisions and create new text. Acknowledge sources appropriately.
- LiteracyLIT 2-26aSelect ideas and relevant information, organise appropriately for purpose and use suitable vocabulary for audience.
- LiteracyLIT 2-29aPersuade, argue, explore issues or express an opinion using relevant supporting detail and/or evidence.
- TechnologiesTCH 2-03bUse search facilities of electronic sources to access and retrieve information, recognising the importance in learning, at home and in the workplace.
- TechnologiesTCH 2-12aExtend knowledge and understanding of engineering disciplines to create solutions.
- TechnologiesTCH 2-15aCreate, develop and evaluate computing solutions in response to a design challenge.
- Social StudiesSOC 3-08aIdentify the possible consequences of an environmental issue and make informed suggestions about ways to manage the impact (relevant when researching farming or industrial IoT applications).
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🎯 Learning intention
We are learning about the importance of data collection and analysis.
✅ Success criteria
- I can explain a definition of the Internet of Things
- I can analyse the use of connected devices
- I can discuss and share my IoT research with others
Pupils are given time to research the concept of IoT. Pose key questions to prompt exploration:
🔑 Key research questions
- What does the Internet of Things mean?
- How do you know if a device is connected to the Internet?
- Do you have any IoT devices at home?
- How can you control IoT devices?
- Are you surprised by any specific devices being part of the IoT network?
- Were you already aware that particular devices were part of IoT?
Support learners in developing their own questions about IoT — these can be explored across further IoT lessons and shared with peers.
Depending on literacy focus, learners could write notes, create a Sway or video, produce a news report, or collaborate on an online platform such as Teams, Google Classroom, Padlet or Mural.
Watch a short BBC News explanation of IoT to consolidate understanding:
At the end of the lesson, learners share their research and allow others to make notes and build understanding through peer discussion.
“IoT is omnipresent in today’s world.”
IoT IS omnipresent because:
- We have all used IoT today by…
- Towns/cities are filled with IoT — for example…
- IoT has helped me today through…
IoT is NOT omnipresent because:
- I haven’t used IoT devices today by not…
- Certain areas of the world are without an internet connection, such as…
🎯 Learning intention
We are learning about the importance of data collection and analysis.
✅ Success criteria
- I can say how data can be used to develop learning environments
- I can analyse data from my school
- I can compare data from different settings
Give pupils free time to explore the live sensor data from their own classroom and from schools in their wider area/nationally. Encourage them to find interesting data points, make inferences and be ready to share.
Guide learners to compare data sets and spot similarities and differences:
✅ Possible similarities
- Same date and time period shown
- Time starts at zero
- Similar “bell curve” shape
- Both have an X-axis and a Y-axis
📊 Possible differences
- Scale is different
- Range is different
- Relative highest/lowest Lux, CO₂, Motion, Temperature, Humidity
- Sensors are in different locations nationally and within buildings
Ask learners to choose their favourite data set, point or location and explain why it interests them. Then, task learners with deciding where they would like to place or hide sensors around their school, putting forward the best argument for their chosen location.
This thinking can lead naturally into the Secret Sensor lesson guide — hiding sensors in the school building and challenging others to guess where they are hidden using only the data.
“This data is my favourite because…”
- It shows that our teacher entered and left our classroom at this time…
- It shows the times of sunrise and sunset were…
- I can see the highest/lowest temperature today was at…
“I want to learn more about this data because…”
- I don’t know why I see X at this time/in this place
- I wonder if I can improve the humidity/Lux/CO₂ levels
“I think the sensor should be placed here because…”
- It will show if CO₂ levels are safe during indoor PE
- It will show motion for the highest number of learners in the school day
- It will help to improve our learning environment/timetable
🎯 Learning intention
We are learning about the importance of data collection and analysis.
✅ Success criteria
- I can say how data can be used to develop industry and commerce
- I can show how data analysis can be applied
- I can show how to use data to improve industry/commercial environments
Learners explore their preferred examples of Industrial and Commercial IoT (IIoT):
Dynamic Positioning
Large ocean-going vessels use IoT automation and AI to stay in an exact position without human intervention.
IoT Agriculture
Sensors attached to farm animals monitor their health, wellbeing and physical location in real time.
Food Manufacturing
Biscuit factories use IoT to ensure every biscuit meets exact quality standards — consistently, at scale.
Sport Performance
Football and rugby players wear IoT devices to monitor health, track movement and improve performance.
Smart Factories
IoT sensors throughout manufacturing control quality, reduce waste and improve energy efficiency.
Inside the Factory
BBC iPlayer series — excellent real-world examples of IoT in food production.
Once learners have grasped how IoT is used in their area of research, they should design their own industrial machine, inspired by their research, that uses IoT to support core functions.
They then create an exhibition in the classroom or wider school to present their machines and explain their IoT functions to others.
“IoT is necessary in all industries.”
IoT IS necessary because:
- It supports efficiency by…
- It develops uniformity…
- It helps the environment by reducing unnecessary emissions…
- AI is the future of industry
IoT is NOT necessary in all industries because:
- It takes jobs from humans
- AI cannot “feel” like humans can
- The ease of accessing data worldwide can be a security issue
🎯 Learning intention
We are learning about the importance of data collection and analysis.
✅ Success criteria
- I can say how data can be used to develop industry and working environments
- I can analyse data from my school
- I can compare data from different settings
Micro:Bit Step Counter projects
Learners code their own step-counter sensors using the Micro:Bit website. Two beginner step counter projects are available:
Learners familiarise themselves with the step counters. Key prompting questions:
🔑 Questions to explore
- How many steps are there between the gym hall and our classroom?
- Can you use the fewest steps to get around our classroom, and the most?
- Does everyone take the same number of steps when covering certain distances?
Once familiar with the step counters, learners use their Micro:Bits in the same locations as the school sensors (where possible). They collect a range of step counter data sets and display these graphically — bar graphs or other methods — then compare with peers.
Display and share the IoT sensor data for the same time period and support learners to investigate:
- Does my pedometer number increase in direct proportion to the Motion Detection from the sensor?
- Can this be linked to CO₂ — and if so, how?
Learners are welcome to develop their own research avenues, keeping in mind: How can I make this a fair test?
- How can I make this a fair test?
- Does my pedometer number increase in direct proportion to the Motion Detection?
- Can this be linked to CO₂ — and if so, how?
Published 15 July 2025 | Contact us | IOT@ed.ac.uk