Classroom Climate-change — Positive ways to enhancing classroom learning with real-world data and student-ownership.

If I told you we could improve cognition in classrooms by 101%, you’d want to know how, yes?

Left > Enviroment sensors . Middle > Smart lights to control visuals . Right > Student-dictated furniture

A range of research projects into how factors like student-ownership, classroom visuals, and environmental conditions can be optimised have been conducted over the last few years, led in particular in Education by the Learnometer.com project from Professor Stephen Heppell. These projects have now reached the point where the evidence for harm being caused to students in sub-optimal classrooms is ready to contribute to an industry-changing transformation in how learners are supported to achieve.

One of the most well known of these research projects in regards to physical environment was published in 2015 by Harvard researchers with the detailed title of ‘Cognitive Function Scores with Carbon Dioxide, Ventilation, and Volatile Organic Compound (VOC) Exposures in Office Workers’ (1). The general findings of this paper were that cognitive functions were 61% higher in rooms with low concentrations of VOC’s (such as formaldehyde), and 101% higher in those that also had ventilation to reduce CO2 (carbon dioxide) levels.

Other research has confirmed similar impacts. A 2010 University of Technology Sydney study (2) found that improved air quality resulted in a 10–14% improvement in spelling and mathematics results. A Yale School of Public Health study (3) conducted 2010–2014 with 20,000 people in China showed that some children lose the equivalent of a whole year of progress across their school lives due to high levels of urban air pollution.

In addition to air quality, enhancing other environmental conditions has also been shown to positively enhance classrooms. A 2015 study by Salford University (4) demonstrated that good lighting significantly influences reading, vocabulary and Science test scores. In regards to temperature, the USA-based National Bureau of Economic Research (5) found that “math performance declines linearly above 21C (70F), with the effect statistically significant beyond 26C (79F)”. Lead researcher Joshua Graff Zivin of the University of California concluded that “if you move from roughly 70F to roughly 87 ½ F, a child’s mathematics score decreases by 1.6 percentile points … when you see a test score change of this magnitude, it’s pretty notable.”

These factors of air quality, light levels and temperature, as well as the levels of visual complexity and student-ownership, have been visualised together in a 2018 article from Edutopia (6) in terms of what percentage of academic performance they represent. The conclusion was that together they are responsible for 49% of all academic progress attributed to classroom design.

Qualifying classroom environmental data and what constitutes optimal learning conditions has been the pioneering goal of the Learnometer project (7) begun by Professor Stephen Heppell, who has worked with a team of experts since 2015 to develop a classroom environmental sensor unit as a result. The resulting units have been operated in schools world-wide, further adding to the data about how classrooms can be enhanced. Prof Heppell has also collated information on what conditions are optimal for learning as part of the Learnometer.com site at http://rubble.heppell.net/learnometer/remedy.html, and is preparing an enhanced Learnometer device for 2019 .

In Australia, Learnometer units have been trialled most recently at a Lutheran College in Brisbane by educator, ICT Coach and founder of FutureWe.org Jonathan Nalder. The Brisbane trial, while at an early stage, has already shown that many classrooms could be enhanced by regular data collection and analysis to optimise learning conditions, most notably around air quality even in air-conditioned rooms. Not only is this an issue for students, but for the teachers who also can benefit from knowledge about air quality, light levels and temperature.

Based on this potential, as well as the contribution that visuals and student-ownership can have, Jonathan Nalder is working to bring the benefits of such a learning enhancement project to more schools in his part of the world. This involves processing the research so far as well as learnings from IOT (Internet of things) professionals and a ‘future readiness’ program called ‘First Kids on Mars’ (where it stands in for spaceship and Mars-base sensors).

Specifically Jonathan is passionate about the student-ownership component and helping schools to realise how improving environment and visual complexity in a classroom can also improve student ownership of learning via inquiry and problem solving approaches.

Beyond this, Jonathan’s 18 years in Education make him keenly aware of the process that often happens with any new technology in schools — where the demands of teaching, crowded curriculum and ongoing training sees many teachers can get stuck at the substitution level (as mapped to the SAMR model) with new technologies. This level sees these used to replace previous tools or methods without taking advantage of the ways that they may also allow learning to be redefined with collaboration and content creation.

As the potential to inform, optimise and then transform learning is so great, Jonathan and a team of Australian educators are looking to support schools in this journey in a way that compliments what research and the Learnometer project’s inspiring work has revealed by developing a complimentary three stage solution: 
Step 1 is a Classroom-level, student-led project clathat bundles basic environmental sensors with a flexible inquiry-based unit developed to be classroom-proof, with room for students as experts and problem-solvers, and the ability to match it to curriculum. 
Step 2 is a School-level solution where 4–10 environmental multi-sensors are paired with staff training, and student experts to support it. This step plans to draw on future releases of devices from the Learnometer project.
Step 3 is a combination of both that also includes ongoing support, use of official net-gen Learnometer units, updates and links to solutions for participating classrooms, schools and partners.

The goal of all these steps is empower students and schools with how data can be used to enhance learning conditions, for all of the tangible reasons found in the research cited above. Doing so also presents the opportunity to link curriculum with skills collated in the Future Readiness Framework (FutureWe.org/framework), a collation of best practice that sets out five big picture ‘literacies’ which can enable students to adapt no matter what their future in a more digital and automated era brings. Specifically the ‘Thinking and Planning’ literacy covers critical thinking and problem-solving skills, both of which can be boosted for students who participate in the project-based steps Jonathan is developing.

To find out more or collaborate on a program for your school or organisation, please email Jonathan via contact@futurewe.org, and don’t forget to follow the original Learnometer twitter account https://twitter.com/learnometer as well.

References:

  1. https://ehp.niehs.nih.gov/doi/10.1289/ehp.1510037
  2. http://www.wolvertonenvironmental.com/Plants-Classroom.pdf
  3. https://www.theguardian.com/environment/2018/aug/27/air-pollution-causes-huge-reduction-in-intelligence-study-reveals
  4. http://www.salford.ac.uk/cleverclassrooms/1503-Salford-Uni-Report-DIGITAL.pdf
  5. http://www.nber.org/papers/w21157
  6. https://www.edutopia.org/article/flexible-classrooms-research-scarce-promising
  7. http://learnometer.com