Reading Time: 7 minutes

Funded by the UK Foreign, Commonwealth and Development Office, the Improving Learning Through Classroom Experience (ILCE) programme focuses on investigating whether modification of the built environment (temperature, light intensity, and acoustics) can positively impact the classroom experience to improve learning. 

This blog post is about the second school visit, focused on testing the comfort survey with students, where we measured acoustics, lighting, temperature, and air quality with students in situ. We will also conduct the walk-through survey, which explores classroom conditions.  Dr. Shelina Walli, Chief Executive Officer of Aga Khan Education Services in Tanzania, and her team facilitated OpenDevEd (ODE) to conduct this pilot study at Mzizima Secondary School in the city of Dar es Salaam. The study was conducted for a period of one week with students in Form 1, typically aged from 12 to 14 years of age. You can find out more about this here

Second pilot (20–27 July 2023)

In addition to testing the devices for a longer period, the purpose of the second pilot was to:

• Run a workshop with students to present the study and answer their questions
• Conduct a comfort survey with students in Form 1 (typically students aged 12–13 years)
• Conduct a walk-through survey with school personnel to understand the classroom conditions
• Assess the time that each activity of the data collection would take in the field.

The workshop

The team held a workshop with the students and gave a presentation on the causes of climate change and how it can affect indoor classroom environment quality (IEQ), including students’ learning outcomes, wellbeing, and health. We explained the importance of the study, including how the results of the pilot could be used to implement changes and retrofits to improve classroom conditions and students’ levels of comfort.

This space was also an opportunity for students to ask questions regarding the topic and to understand more details regarding the aim and approach of the study. 

Figure 1. Presentation about climate change and the importance of indoor environment quality (IEQ) in classrooms at Mzizima Secondary School.

A comprehensive poster answering the main questions of the study was placed outside the classroom, so the school community could learn more about our project.

Figure 2. Poster placed next to the classroom

Comfort survey

Forty-three students were asked to complete an online ’comfort survey’ asking about their levels of comfort in their classrooms in terms of temperature, humidity, lighting, air quality, and noise. 

As Figure 3 below shows, 65% of students indicated that they would prefer their classroom to be cooler. It is worth mentioning that July is one of the cooler months in Dar es Salaam. The students’ answers seem to suggest that the need for cooler classrooms will only increase during the hotter months.

Figure 3. Results from comfort survey (temperature)

Another answer that caught our attention is that more than 75% of students would like the classroom to have better air circulation levels; this could be related to different things, such as the occupancy rate of the classroom, the orientation of the classroom related to airflow, reduced cross ventilation between opposing windows, etc.

Figure 4. Results from comfort survey (air)

Of 43 students, 19 reported an unpleasant smell in the classroom. Of those 19 students, 15 attributed the smell to the manure being used on the football pitch near the classroom. While this could be something that only happens occasionally, it might be necessary to consider such instances more seriously to manage such occurrences and avoid students being negatively affected.

Figure 5. Results from comfort survey (source of the odour)

Walkthrough survey

This survey consisted of different sections that aimed to cover aspects such as roof material, number of windows, wall colours, occupancy, and the frequency with which maintenance plans are implemented. While most of the questions could be answered by the OpenDevEd (ODE) team, the completion of certain sections required the collaboration of school personnel.

The results of the data collected from this survey will be analysed in a future report when we begin analysing different options for retrofits.

Environmental data

The team set up different IEQ parameter-measuring sensors in the classroom to collect data for a week. All dataloggers/sensors worked as expected with little to no interference from the students or the teaching staff. The data from the dataloggers was safely retrieved and stored in the ODE data repository. Extensive data analysis and reporting will be undertaken and shared with Aga Khan Mzizima Secondary School at a later date.

The preliminary results of our pilot study are shown below. 

Temperature

Temperatures each day vary by about 2 °C, with the coolest temperature record being 27 °C from 5 a.m. to 8 a.m. and the hottest being 29 °C from midday to 3 p.m. The increase in temperature within the classroom during midday can be attributed to a combination of factors. The heat generated by the students themselves, along with the radiant heat from sunlight during that time.

Figure 6. Temperature readings for the week of 20–27 July, using two different sensors

CO₂

As a preliminary analysis, CO₂ shows 400 ppm (parts per million) as the lowest level, and it peaks at over 1000 ppm from 8 a.m. to 9 a.m. During the school day, from 9 a.m. to 4 p.m., levels of CO₂ vary from 400 to 900 ppm. CO₂ measurements are commonly employed to gauge the sufficiency of ventilation within indoor spaces. In the context of classrooms, maintaining a CO₂ concentration below 1000 ppm is the recommended criterion for ensuring satisfactory ventilation. The utilisation of CO₂ measurements to assess ventilation adequacy stems from the fact that CO₂ is a reliable indicator of indoor air quality (IAQ) and circulation. As students exhale CO₂, its concentration within a closed space increases over time. Therefore, monitoring classroom CO₂ levels provides valuable insights into the effectiveness of ventilation systems in replenishing indoor air with fresh, oxygen-rich air from the outside.

By measuring CO₂ concentrations, it is possible to infer whether a space is experiencing sufficient air exchange and proper circulation. Elevated CO₂ levels, especially when over 1000 ppm , often indicate inadequate ventilation, suggesting that the build-up of other potential pollutants and decreased oxygen levels might also be present. Thus, CO₂ measurements offer a practical and indirect means of evaluating ventilation performance and ensuring healthier indoor environments.

Figure 7. CO₂ readings for the week of 20–27 July

PM2.5 and PM10

In the context of regulating air quality, particle size is a critical factor. Particles with a diameter of 10 microns or smaller (PM10) are considered inhalable and can pose health risks. Particularly concerning are particles with a diameter of 2.5 microns or smaller, known as fine particulate matter (PM2.5). It’s important to note that PM2.5 particles can penetrate even deeper into the respiratory system, potentially causing more severe health issues. Consequently, a portion of PM10 particles consists of PM2.5 particles.

The World Health Organization recommends that the yearly mean levels of PM2.5 should remain below 5 µg/m³ on average. Additionally, there should be no more than 3 to 4 instances per year when the 24-hour average exposure surpasses 15 µg/m³. For PM10, the annual average should be limited to 15 µg/m³, while the 24-hour average should not exceed 45 µg/m³ for more than 3 to 4 instances per year.

Figure 8. PM2.5 (µg/m³) and PM10 (µg/m³) readings for the week 20–27 July 

As can be seen from Figure 8, there were many days when the recommended values for PM2.5 and PM10 were exceeded 

Table 1. Descriptive statistic for measured PM2.5 (µg/m³)

PM 2.5

Mean	Median	Max	Min
11.32	9	50.2	2.7

Table 2. Descriptive statistic for measured PM10 (µg/m³)

PM 10

Mean	Median	Max	Min
19.16	15.2	94.8	4.5

Illuminance

The descriptive statistics for the measured light intensity during the workshop with students are shown In Table 1 above.

Table 3. Descriptive statistics for measured light intensity in the classroom (lux) during occupied hours of the workshop (~2 p.m. to ~3 p.m.) 

Mean	Median	Max	Min
36.35	35	53	10

The mean, median, maximum, and minimum light intensity values measured showed that the light intensity in the classroom was below recommended levels for classrooms, which should be around 300 lux or more. This could be related to the classroom windows being covered with curtains during classes when the teacher uses a projector. However, we noticed that the students still preferred the dark classroom even after the presentations. It’s likely that they have become accustomed to the classroom being dark, or they might be using the curtains to prevent sun glare.

Lighting is a crucial factor in creating an optimal learning environment in a classroom. It plays a significant role in shaping students’ concentration, mood, and overall wellbeing. The quality and design of classroom lighting can greatly influence students’ ability to engage in lessons, retain information, and foster a positive educational experience. 

1.5. Next steps

An in-depth analysis of the readings collected from the devices, comfort survey, and walkthrough survey will be carried out to learn more about the classroom conditions. After this, our team will provide recommendations for retrofits to improve IEQ in the classroom where the second pilot was conducted.

• Students displayed a high level of interest and asked questions in the workshop about how climate change could impact them. More activities to engage the school community on this topic might be necessary.
• Students in the schools where the study will be conducted are mostly Swahili speakers. For the fieldwork, the presentation, poster, and comfort survey will be translated into Swahili.
• The comfort survey will be printed for the fieldwork because internet connectivity and computer labs might not exist or be available in the schools selected for the larger intervention.
• OpenDevEd has built a second version of the environmental sensor that includes readings of temperature, humidity, luminance, sound, and CO₂ parameters. In the upcoming months, this second version will be tested again at Mzizima Secondary School, with and without the presence of students.

Overall, the first and second pilots enabled us to fine-tune our approach and prepare for the larger intervention programme. We are excited to see the positive impact our research could have on improving indoor environmental quality and learning conditions for students in Tanzania.

Reading Time: 6 minutes

Funded by the UK Foreign, Commonwealth and Development Office, the Improving Learning Through Classroom Experience (ILCE) programme focuses on investigating whether modification of the built environment (temperature, light intensity, and acoustics) can positively impact the classroom experience to improve learning. 

This blog post is about the first pilot, where we tested the sensors in preparation for the upcoming fieldwork. Dr Shelina Walli, Chief Executive Officer of Aga Khan Education Services in Tanzania, and her team facilitated OpenDevEd (ODE) in conducting this pilot study at Aga Khan Mzizima Secondary School in the city of Dar es Salaam for one day.

The aim was to test all the devices to be used in the study, so the presence of students was not required.

Authors: Oluyemi Toyinbo^1,2, Xuzel Villavicencio¹, and Björn Haßler¹

¹Open Development and Education Ltd (OpenDevEd, UK and Sierra Leone)

²Oulun yliopisto (University of Oulu, Finland), Teknillinentiedekunta (Faculty of Technology), Rakennus-ja yhdyskuntatekniikka (Civil Engineering)

First pilot (23 June)

The purpose of the first pilot was to:

• Conduct an initial test of the commercially available equipment
• Test the environmental sensor built by OpenDevEd
• Compare measurements and analyse the accuracy of devices
• Determine the most appropriate logging period for data for the sensors for maximum battery life and storage capacity.

Commercially available sensors

 The sensors used measured the following indoor environmental quality (IEQ) parameters:

• Temperature and humidity: 
  • Onset HOBO MX1101 with accuracy ±0.21°C from 0° to 50°C for temperature measurement and ±2% for humidity. The sensor can collect data independently of a computer system, as it operates on battery power and allows data retrieval through a mobile app. It has an extended battery life of over 3 months. Cost: £220.
  • Lascar EasyLog EL-SIE-2 with accuracy ± 0.2°C from -18⁰ to 55°C for temperature and ± 1.5% from 0-100% for humidity. The sensor can collect data independently of a computer system since it operates on battery power, and data retrieval can be accomplished through a specified manufacturer weblink (easylog.local). It has an extended battery life of over 3 months. Cost: £70.
• Lighting:
  • ATP DT-8809A Lux sensor data logger with accuracy of ±3% of reading ±0.5% full scale, below 10,000 Lux. Includes a silicon photo diode sensor and spectral response filter. This sensor can be powered by either batteries or electricity. It doesn’t have the capability for independent data logging, but it does feature independent memory, capable of storing data up to 99 times without the need for a computer system. Continuous, long-term data logging is only possible when the sensor is connected to a computer system. Data retrieval can be done through its installed computer application. Cost: £137.
• Noise: 
  • ATP ET-958 Sound level meter with accuracy of ±1.4dB (94dB @ 1 Khz). Allows measurement ranges of 30 to 80dB 50 to 100dB, 80 to 130dB, 30 to 130dB (Auto range). This sensor operates exclusively when connected to a computer system. It can be powered by batteries or electricity. Data retrieval can be done through its installed computer application. Cost: £182.
• Indoor air quality (IAQ) parameters
  • Temtop M2000 2nd generation with;
  • – CO₂ accuracy: ±50 ppm + 5% reading.
  • – PM2.5 accuracy: ±10 μg/m³(0-100 μg/m³), ±10%(>100 μg/m³)
  • – PM10 accuracy: ±15 μg/m³(0-100 μg/m³), ±15%(>100 μg/m³)- Formaldehyde accuracy: ±0.03 mg/m³(0-0.3 mg/m³), ±10%(>0.3 mg/m³)
  • The sensor operates independently and is powered by a rechargeable battery with a limited lifespan of under 7 hours when fully charged. For extended use, it must be continuously connected to an electricity source. Data retrieval can be easily done on a computer without requiring any installed applications. Cost: £170.

Assessment of the commercial sensors

We investigated commercially available sensors extensively and in great detail. The sensors listed above are the best we could find. 

Sensors for temperature and humidity are readily available at a reasonable price, with good battery life and the capability to make autonomous measurements for several months.

However, when it comes to sensors for measuring other environmental properties, either the price is high or the sensors have poor battery life (which means they will have limited autonomy). Furthermore, there are no commercially available sensors that can measure the key elements of light and sound autonomously over a period of time.

Environmental sensors built by OpenDevEd (ODE)

Inspired by available maker-type devices, such as the Pimoroni environmental range, we set about developing a ‘sensor box’ that could measure not only temperature and humidity, but also light and sound. We hoped to draw on cost-effective materials and manufacturing, ideally with a flexible approach that could be repurposed for different uses and in different settings/countries. 

The first version of our ’sensor box’ uses a Raspberry Pi Pico, with a customised power circuit and a range of sensors allowing measurement of the following environmental parameters:

• Temperature/humidity using an AHT20 sensor 
• Temperature using an MCP9808 sensor
• Luminance in Lux using LTR-559 sensor.

The sensor was also fitted with an I2S MEMS (Micro-Electro-Mechanical Systems) microphone to measure noise; this was unsuccessful due to software issues, and the next version of our sensor used a PDM (Pulse-Density Modulation) microphone instead (to be discussed in a future blogpost). The sensor is powered by two AA batteries, with an expected lifetime of up to several months, depending on frequency of measurements. In the first version of our software, the measurement interval can be set arbitrarily, typically 5, 10, or 15 minutes.  The data collected is stored on a memory card and can be easily extracted.

Even though the first version allows the measurement of a fairly limited number of  parameters, our design allows us to add additional sensors quite easily, including for sound, but also CO₂, volatile organic compounds (VOCs), and particulate matter (PM). Moreover, the sensor has provision for wireless data transmission, enabling real-time (or near-real-time) logging. These additions will be described in a future blog post. Further technical details and links are provided below, and will also be published in a report at a later date.

Observations from the first visit

After leaving all the devices running for a period of approximately 4 hours without students, the team observed that:

• Temperature and humidity show very similar results across all the devices, with a difference of 0.2 to 0.5 °C and 1%, respectively.
• Temperature and humidity do not vary significantly during the day, only by about 2–4 °C. This allows us to consider that an interval of 15 to 30 minutes will be sufficient to gather representative temperature/data for the study.
• Luminance readings between the ATP DT-8809A Lux sensor and the ODE sensor are not comparable because the latter does not include a photodiode sensor. The photodiode sensor makes the commercially available sensor more sensitive to light.
• For optimal luminance and sound readings with an ODE sensor, we will consider using three or more sensors located in strategic locations in the classroom.
• Air quality shows good levels in all its parameters, with measurements of CO₂ serving as a surrogate for ventilation adequacy, as well as measurements of PM2.5, PM10, and formaldehyde to represent volatile organic compounds (VOCs).

About our sensor

Links and further information are listed below for readers interested in the technological details of our sensors.

• The datalogger design was led by Bernhard Bablock; it was based on some of his prior designs. Details about the sensor (hardware and software) are available here: https://github.com/bablokb/pcb-pico-datalogger.
• The datalogger connects to a ‘sensor board’, mounted with a range of (mainly) I2C sensors: https://github.com/OpenDevEd/sensor-stripboard-v1 
• To keep costs down, we used a commercially available ABS box, but replaced the lid with a 3D-printed lid, that allowed mounting. The 3D print files are available here: https://github.com/OpenDevEd/case-for-pico-datalogger-rev1.00 

What’s next?

Next time, we will report on the outcome of the second school’s visit, which focused on testing comfort with students. This means we will be measuring temperature, humidity, acoustics, lighting, and air quality with students in situ. We will also conduct the walk through survey, which explores classroom conditions.

Reading Time: 3 minutes

The world is grappling with the effects of climate change, specifically global warming and biodiversity loss. Human life is greatly impacted by extreme weather events, and in Africa, warm and hot climates prevail all over the continent, with the northern part mostly arid and with high temperatures.

This blog considers the effect of climate change on school buildings and, subsequently, on learning. Implementing simple but creative solutions using design principles, local resources, and know-how can have a positive and significant impact. Read on to find out more. 

East Africa is characterised by an equatorial tropical climate which is considered moderate, with temperature and humidity levels comfortable most of the year compared to other areas with more extreme conditions. However, it is among the world’s most vulnerable regions to the impacts of climate change from a projected increase in hot days and heavy precipitation.

Continue reading “The Importance of Climate-Friendly School Buildings in Africa” →

Reading Time: 3 minutes

Nearly a third of the time in childhood and early teenage is spent in school classrooms. A school is a place to develop skills and abilities and create friendships. It is an environment for thriving social interactions that will be essential on their journey to adulthood. School should be a place where students learn, and have fun as well. School should not be a hindrance for children, because, in that space, they not only develop social, physical, and mental skills and abilities but also undergo physical changes. Therefore, no health risks should be at stake. 

Continue reading “School: A Second Home for the Children” →

Reading Time: 2 minutes

Examples of small changes in building design, or retrospective adjustments, have anecdotally been shown to improve the learning experience in the region. There is little research on improving the learning experience through infrastructural development – or how to achieve these changes in sustainable and cost-effective ways. The objective of the ILCE programme is to garner greater insight into the role of infrastructure in students’ and teachers’ experiences, moving past anecdotal case studies and providing evidence through primary data measurement.

Where is the project based?

The project is based initially in Tanzania and will take insights from similar experiences in the East Africa region.

What is the duration of the study? 

Fifteen months. From December 2022 to March 2024.

Continue reading “The “Improving Learning Through Classroom Experience” Study” →