Digital Transformation in Education: How to use behavioral frameworks to improve edtech for digital educators
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A 4-fold increase in edtech investment
As the pandemic shifted education out of physical classrooms into their virtual counterparts, investment in education technologies - or edtech - has grown exponentially. $8.2 billion was invested in 2021, an increase of nearly 4x from $2.2 billion in 2020.1
The emergence of digital education has not only made learning more accessible at scale, but created new possibilities for delivery. Seven out of 10 teachers surveyed responded that using digital education technologies in the classroom enables them to do “more than ever before”.2 And they’ve only had a taste of what’s to come.
Personalized learning can increase academic success, as long as we make the leap
Of the many innovative potentials for edtech on the horizon, perhaps the most promising is personalized learning. Edtech enables a flexible model for personalized learning by continuously evaluating performance and providing real-time feedback to deliver the right material, in the right way, at the right time.
Personalization also offers students more autonomy to determine their own learning path, allowing them to decide for themselves what they learn and how to learn it. Students thrive when they have this autonomy - a study of 5539 students found that personalized learning resulted in a significant 3 percentile increase in math scores.3
However, the adoption of personalized edtech is still lacking. Sixty percent of American teachers never or rarely use digital technologies to allow students to learn at their own pace.4 If edtech developers want their products to be adopted at scale, they need to target teachers.
They can start with personalized teaching interventions.
Behavioral Science, Democratized
We make 35,000 decisions each day, often in environments that aren’t conducive to making sound choices.
At TDL, we work with organizations in the public and private sectors—from new startups, to governments, to established players like the Gates Foundation—to debias decision-making and create better outcomes for everyone.
Overcoming the implementation gap by providing teachers with clear direction
Personalization offers a bold vision of what education could be. Imagine a classroom where students can progress at their own pace, engage with content that interests them, and receive personalized instruction to overcome learning obstacles. Personalization can also have an enormous impact on marginalized students who fall through the cracks–and if done correctly, can motivate them to complete school and push socioeconomic boundaries.
The barriers to personalized digital learning
But a 2018 report from CRPE, funded by the Bill and Melinda Gates Foundation, found that teachers were not provided with strategies and support to implement personalized learning in their classrooms.5 Being left to their own devices, teachers often had to sacrifice more rigorous teaching approaches for experimenting with alternative classroom structures and teaching standards. The inconsistencies in personalized teaching due to unclear guidelines was a source of frustration for both teachers and students alike–and as a result, personalized learning was often not developed beyond initial pilot studies.
This is a clear lesson for edtech developers: in order to increase the effectiveness and widespread adoption of their products, they need to equip educators with clear strategies for supporting students in a personalized manner.
To do so, edtech design can incorporate behavioral frameworks that map barriers to educational outcomes and design customized teaching strategies that address them.
Designing behaviorally-aligned edtech
Incorporating behavioral insights into educational technologies enhances learning outcomes – and in fact many digital learning products already do. Adaptive edtech tailors the pace and difficulty of learning material to keep students in their zone of proximal development. Edtech can also implement spaced-learning strategies to improve the retention of key concepts and competencies.
But when it comes to applying behavioral science frameworks to provide educators with clear guidelines for how to deliver personalized instruction, edtech is still lacking. So, how can behavioral science inform customized teaching interventions?
Applying the COM-B framework to design personalized teaching interventions
The COM-B model offers a flexible framework for designing behavioral interventions. It posits that there are three main drivers for any behavior:
- Capability: the physical and psychological ability to execute a behavior
- Opportunity: the environmental and social factors that enable a behavior
- Motivation: the internal drive to execute a behavior
Since any behavior depends on each of these factors, achieving a desired educational outcome involves identifying which of these three factors is lacking and then implementing an intervention that addresses it.
Applied to an educational setting, the COM-B model works backwards from a learning outcome that’s not being met, like poor student engagement or learning progress, and specifies how to overcome the barrier that’s been identified.
By monitoring the progress of students and identifying patterns in their habits and decision-making, edtech provides detailed insight into what challenges a student is facing. Behavioral science then identifies which teaching intervention would be most effective, and can provide educators with customized recommendations for how to support a student’s needs.
This can include detailed suggestions for what intervention to apply and how to cater it to a student’s learning style, interests, and behavioral traits. After implementing a teaching strategy, the teacher and student are provided with immediate feedback to evaluate the success of an intervention. This enables an iterative process for giving students customized support, that provides educators with greater clarity and confidence in their teaching methods.
In practice: Micro-journeys can help refine teaching strategies
What does applied, behaviorally-aligned edtech look like?
Imagine a digital technology that breaks down learning objectives into ‘micro-journeys’ that give teachers a birds-eye view of how their students are progressing. These micro-journeys provide a timeline of how a student has progressed in a subject area, identifying where they were challenged and where they needed support.
At each of these touch points, the educator is notified that the student needed help and a teaching intervention was implemented based on a personalized recommendation from the digital technology. The effectiveness of this intervention would then be evaluated by monitoring the student’s subsequent progress.
And don’t forget the framework!
By keeping a historical record of different teaching methods and whether they were successful, educators gain valuable perspective for how they can best support their students. Over time, teachers can build up an intuition for how to deal with different types of students and the unique challenges they face.
Applying behavioral frameworks to edtech helps remove the guesswork from personalized learning. But to make these products even more effective, developers need to ensure that their solutions integrate research from learning sciences and feedback from their primary users: teachers and students.
Using behavioral science frameworks to encourage teacher uptake
The rise of personalized learning technologies is giving education a much-needed makeover. To unlock the full potential of personalization, edtech developers can apply the COM-B framework for designing customizing teaching interventions that cater to the needs and preferences of students. By leveraging evidence-based teaching strategies that incorporate user feedback, educational technologies have an opportunity to empower both teachers and students alike.
The Decision Lab is a research-oriented consultancy that uses behavioral science to advance social good. We work with industry leaders in edtech like the Gates Foundation to help students and educators thrive in the future of learning. If you'd like to help us deliver top-tier education to students everywhere, contact us.
- Wan, T. (2022, March 8). US Edtech's roaring twenties begins with $8.2 billion invested in 2021. Medium. Retrieved May 5, 2022, from https://medium.com/reach-capital/us-edtechs-roaring-twenties-begins-with-8-2-billion-invested-in-2021-99f01a662280
- Public Broadcasting Service. (n.d.). PBS survey finds teachers are embracing digital resources to propel student learning. PBS. Retrieved May 5, 2022, from https://www.pbs.org/about/about-pbs/blogs/news/pbs-survey-finds-teachers-are-embracing-digital-resources-to-propel-student-learning/
- Pane, John F., Elizabeth D. Steiner, Matthew D. Baird, Laura S. Hamilton, and Joseph D. Pane. (2017). How Does Personalized Learning Affect Student Achievement?. Santa Monica, CA: RAND Corporation https://www.rand.org/pubs/research_briefs/RB9994.html.
- Klein, A. (2021, January 15). Data: Here's what educators think about personalized learning. Education Week. Retrieved May 5, 2022, from https://www.edweek.org/leadership/data-heres-what-educators-think-about-personalized-learning/2019/11
- Gross, Betheny, and DeArmond, Michael. (2018). Personalized Learning at a Crossroads: Early Lessons from the Next Generation Systems Initiative and the Regional Funds for Breakthrough Schools Initiative. CRPE. https://crpe.org/wp-content/uploads/crpe-personalized-learning-at-crossroads.pdf
About the Authors
Ryan is currently pursing his PhD in neuroscience at McGill University, focusing on the molecular and cellular mechanisms of neural plasticity in the developing brain. His main interest is in applying behavioural frameworks to guide interventions that enhance mental health and wellbeing. A staunch advocate for data-driven solutions, he seeks to leverage data science and machine learning tools to improve behavioural outcomes in digital health and finance. He has also participated in McGill-affiliated science outreach campaigns, giving presentations on neuroscience topics for high school students and answering publicly-sourced neuroscience questions. In his spare time, Ryan can be found enjoying a good book, playing various sports like hockey, volleyball and tennis, or simply getting lost in nature.
Jayden has a particular interest in studying how public policy can be used as a tool to help individuals and organizations make decisions to protect the environment. She has previously worked in the domain of environmental policy at the Ontario Ministry of the Environment. She is a founding director of the environmental non-profit Climatable, which focuses on engaging Canadians in climate change action. Jayden received her bachelor’s degree from McGill University in environment and political science.