Written by: Amy Lightfoot, Director Insight and Innovation, English Programmes
For several years, the British Council has been offering webinars, courses, lesson plans and other resources to help teachers develop their understanding of climate change, and to integrate a focus on sustainability into their classrooms. However, like all organisations, we are also concerned about our own institutional carbon footprint, and keen to explore how we can reduce this not only for our day-to-day activities but also within the context of our programme and project delivery on the ground.
We are conscious that the nature of project delivery comes with its own environmental impact, including through the development of resources and transporting resources and people – such as teacher educators – within and between countries around the world. Post-Covid, we have increased the amount of project delivery that is done remotely, usually online, and we are interested in the effects this shift in modality is having not only on the impact on teachers’ learning outcomes, but also in relation to our environmental impact.
In April 2024 we commissioned a brilliant research team at Jigsaw to explore the relative environmental impact of online versus face-to-face models of delivery of education-focused projects. Recognising that much of the literature to date focuses on measuring the carbon footprint of activity taking place in higher income contexts, we wanted to focus on delivery in low and middle-income countries with the understanding that there were likely to be different factors affecting the measurement.
Together with Jigsaw, we decided to use the Secondary Teachers English Language Improvement Rwanda (STELIR) project as a case study to test the measurement approach. STELIR is a large-scale three-year teacher development project delivered by the British Council under a partnership with Mastercard Foundation, expected to reach over 8000 pre-service and in-service teachers by its conclusion in 2025. The programme is designed to improve teachers’ knowledge and skills for more successful English language teaching and uses a blended model of delivery: perfect for comparing the relative environmental impact of online versus face-to-face training.
STELIR involves a combination of online courses (60-90 hours), intensive face-to-face courses (30-60 hours) and six months of school-based peer-supported continuing professional development. One of the first tasks for the research team was listing the relevant data points including the number of participants involved at each stage, transportation requirements, goods and services purchased (including technology to facilitate the online courses), premises and their energy usage and details of accommodation and meals. With this data collected, the team moved on to identifying the most appropriate calculation tools and working out the emissions from each phase of the programme. This was no easy task, as the team found a distinct lack of information about emission factors that has been calculated for Rwanda specifically, or for low- and middle-income countries more broadly. In some cases, estimates were required to fill gaps where detailed information was not available.
The resulting calculations have caused much debate and discussion internally among our team and with those who have since engaged with the developed framework, tools and report on our findings. Our expectation going into the project was that we would be likely to see a greater carbon footprint for the face-to-face elements of the programme. This held true – until we calculated in the fact that a large number of devices (tablets, chargers and earphones) were procured to enable the online delivery phase. The emissions involved in the manufacturing of these and then transportation into Rwanda skewed the picture considerably, with the result that the online component ended up with a higher carbon footprint than the face-to-face element.
In countries where teachers have their own devices and there is no requirement to purchase these, online delivery is very likely to be – as expected – a more environmentally friendly approach. But it is important to highlight the impact of using technology where it is built into projects in places where new devices are required. There are clear implications for us to ensure that we systematically reuse devices and reduce the need for procurement of new ones, to make this type of project delivery more sustainable. It is worth noting too, that as the data storage requirements of more sophisticated technologies like AI increase, the environmental impact of applications and software will only increase.
Finally, we recognise the importance of learning outcomes as a critical factor for drawing conclusions about the relative effectiveness, efficiency and sustainability of differing models of delivery. This is an area we are looking to explore further, and we’d be keen to hear from partners who have a mutual interest.
You can find a summary of the research findings here along with links to the full report and the framework and tools which are available open access for others to use by clicking here.