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This lesson guide focuses specifically on CO₂ and its effect on learners’ ability to concentrate and learn. Using real sensor data and the PPDAC enquiry cycle, learners investigate CO₂ patterns in their own classroom, identify pinch points during the school day, and explore evidence-based interventions — including the introduction of plants — to improve their learning environment.
Lesson overview
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For the PowerPoint version of the presentation, email IOT@ed.ac.uk.
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🎯 Learning intention
We are learning how environmental factors, such as CO₂, can affect children’s learning.
✅ Success criteria
- We can find evidence that shows how environmental factors affect learning
- We can share and present our findings
- We can work well in groups
The class (working in groups) conducts internet research to discover how environmental factors such as CO₂ can affect learning. Useful links to support this activity:
- Let’s Talk Science — Is there too much CO₂ in your classroom?
- Learnometer — environmental variables and learning
- EnergyAir — how classroom temperature affects learning
- heppell.net/byop — Bring Your Own Plant
- Harvard study: elevated CO₂ levels and human cognition
CO₂ reference guide — parts per million (ppm)
Learners share and present their findings to the class.
🎯 Learning intention
We are learning how sensors can record environmental data.
✅ Success criteria
- I can describe types of environmental data recorded by a sensor
- I can say why data about the environment is helpful
- I can analyse environmental data about a classroom
Recap on Activity 1 — looking at how environmental conditions like CO₂ can affect learning.
Learners are introduced to using sensors to monitor indoor environments such as classrooms, offices and homes.
Learners consider the purpose of monitoring environmental conditions such as CO₂ levels. Possible considerations include:
- Health and wellbeing
- Safety
- Productivity
- Comfort
- Being eco-friendly
Learners are presented with data from the classroom at Cladach Primary School, measuring CO₂ levels throughout the school day.
In groups, learners discuss and analyse the Cladach Primary data. They should identify trends and develop hypotheses to explain why changes occurred. For example:
- CO₂ levels increase from 9am due to pupils and teachers breathing and speaking. Levels fall at lunchtime when pupils are outside, then increase again during the afternoon.
- CO₂ falls significantly between 2–3pm. This suggests the teacher opened windows, or the class was elsewhere doing PE.
- CO₂ follows a similar pattern on different days — this helps establish what is ‘normal’ for the classroom.
🎯 Learning intention
We are learning how to plan and carry out an investigation into our classroom environment using the PPDAC model.
✅ Success criteria
- I can identify the problem to be investigated
- I can plan an investigation
- I can describe how our sensor will provide us with data
- I can work well in groups
The main purpose of this investigation is for learners to determine whether CO₂ levels in their classroom could be affecting their learning. Learners will use the PPDAC model:
Present the PPDAC process to the class as applied to this investigation:
- Problem: We want to know if CO₂ could be affecting our learning.
- Plan: We will plan how we will gather data on CO₂.
- Data: We will gather data about CO₂ in our classroom.
- Analysis: We will analyse the data to understand if CO₂ could be affecting our learning.
- Conclusion: We will conclude our investigation.
Learners discuss the problem of CO₂ in the classroom, prompted by the teacher.
Learners learn about the Elsys ERS Smart Building Sensor in their classroom. They learn how the sensor operates, captures data and uploads it to the University of Edinburgh’s cloud-based systems. They also learn how to access their classroom data through the dashboard.
Learners discuss where the sensor should be located in the classroom. The sensor measures CO₂ in its immediate vicinity — placing it on the teacher’s desk or pupil desks will likely capture elevated levels that may not reflect the ambient CO₂ in the room. This distinction should be discussed with learners.
At the outset, learners establish the normal pattern of CO₂ for their classroom — how it varies throughout the day and week — to create a baseline for comparison.
Data from the sensor is collected over a time period agreed during group discussion.
🎯 Learning intention
We are learning how to analyse sensor data about our classroom.
✅ Success criteria
- I can identify changes to classroom CO₂ data
- I can suggest possible reasons for changing data during the school day
For 3 or more weeks, learners analyse the data from the sensor dashboard and discuss changes to CO₂ levels.
Learners explore how CO₂ changes during the school day and week:
- At what times of day are CO₂ levels highest/lowest?
- What might be the cause of these changes?
At the end of the data collection period, split the class into groups. Each group presents their findings to the class. Discussion prompts:
- What have we learned from our analysis of the data?
- Agree on possible explanations for changes during the day and week
- Describe how changes to our classroom environment might affect our learning
🎯 Learning intentions
We can conclude our investigation. We are looking to improve our learning environment. We will create a presentation to share with the class.
✅ Success criteria
- I can describe the problem we investigated
- I can describe how we planned the investigation
- I can describe the role of data in our investigation
- I can describe how we analysed the data
- I can describe the main conclusions of our investigation
- I can suggest ways of improving our classroom environment
Learners reflect on what they have learned about the impact of CO₂ on their learning.
Note for teachers: Every classroom will have heightened CO₂ levels at some point during the day and week. Based on learners’ findings from Activity 4, the focus is now on finding ways to reduce CO₂ overall, or on mitigating measures at the pinch points identified in the data.
Learners discuss what they could do in groups or as a whole class to improve their learning environment:
- Opening windows and/or doors to reduce CO₂
- Introducing plants to the classroom (see Activity 6 extension for full details)
Learners create a presentation about their investigation and share it with the class, using the PPDAC structure:
Each group may present the entirety of the investigation, or each group may present only one PPDAC stage. The Data Education in Schools team can also link you with other classes doing the same investigation for online collaboration.
🎯 Learning intentions
We can implement suitable interventions to improve air quality. We see the changes in CO₂ data from the sensors. We can suggest further interventions.
✅ Success criteria
- I can summarise the interventions I put in place and the effects I would expect
- I can conclude the sensor data analysis once interventions are in place
- I can suggest further ways of improving our classroom environment
Over the following weeks, learners regularly analyse sensor data to see if their interventions have achieved optimal CO₂ levels.
Learners summarise their findings and draw conclusions from the full investigation.
🎯 Learning intention
We are investigating the effect of plants on air quality and CO₂ levels in our classroom.
✅ Success criteria
- I can explain why plants can help reduce CO₂
- I can plan an investigation into the effect of plants on CO₂ levels
- I can analyse data to see the impact of plants over time
Introducing plants is the most active way for children to improve their learning environment. Evidence from countless studies confirms that the right plants reduce CO₂ and increase oxygen in closed spaces. Schools that have introduced plants have noticed a measurable difference in air quality.
Key points from Stephen Heppell’s BYOP research:
- Higher than normal CO₂ directly damages cognitive performance — the threshold for harm is lower than was first thought
- Target CO₂: keep below 1,000 ppm throughout the school day
- Plants should ideally be in white pots — white reflects light to help photosynthesis, and prompts the question “Why white?” — a valuable metacognitive discussion
- A white background behind plants helps too
- Moist air above 40% humidity helps the body fight infections — plants with moist soil help raise humidity
- Measure CO₂ at 3 points during the day, before and after plants are added, to visualise the difference
- Research which plants are best for reducing CO₂ — spider plants are particularly effective. The NASA Mars Mission has produced a top list of air-purifying plants.
- Each learner brings their own plant to school with their name on the pot. They are responsible for looking after it and monitoring moisture levels.
- Introduce plants gradually so learners can monitor and analyse incremental changes to CO₂ levels.
- Take CO₂ readings at 3 points during the day — before and after plants are added — for a graphing and data visualisation task.
- Discuss ways of raising funds to purchase a plant wall or additional plants (1 per learner is ideal).
- Learners may decide to grow their own plants from seed.
- Some schools may explore hydroponics or BBC Micro:bit controlled watering systems — the Data Education in Schools team can point you in the right direction.
- Contact other schools doing similar research to compare findings — email IOT@ed.ac.uk for details.
- Discuss why environmental data matters in offices, factories and homes.
- Review all data from the investigation — analyse, compare and summarise.
- Use online visualisation tools such as Flourish Studio to produce graphical representations of the data.
- Write a blog or newspaper article about the research for a local newspaper or school magazine.
Published 15 July 2025 | Contact us | IOT@ed.ac.uk