Can Personalized Learning end the world’s education crisis?
Sustainable Development Goals: 3, 4, 9, 16
- SDG 3 - Good Health and Well-Being
- SDG 4 - Quality Education
- SDG 9 - Industry, Innovation and Infrastructure
- SDG 16 - Peace, Justice and Strong Institutions
Featured project | A landscape analysis of tech-enabled personalized learning solutions in developing country contexts.
Learning is in crisis, and it’s been made worse by the pandemic. If there is any silver lining here, it is the growing willingness of students and teachers to experiment with new approaches to learning – whether to overcome the physical constraint of school closures, or to find ways to catch-up when kids have fallen behind on their curriculum. Innovation in education is hardly new, but the pandemic has offered up a vast experiment in testing different forms. Among the most interesting of these is digital Personalized Learning. But what is “digital Personalized Learning”? As the name suggests, we are talking about tech solutions and products that tailor learning to suit not an entire classroom or a school, but instead to adapt to individuals and their specific learning needs. Many, although not all, harness rapidly advancing technologies and that’s helped fuel an expansion of the products on offer over the past decade. And while evidence is still emerging, these products hold great promise in improving learning outcomes and closing gaps for students who have fallen behind. For all that promise, there is a dearth of systematic information on digital Personalized Learning products being used in the developing world. And when it comes to their effectiveness, their design, their implementation, and their scalability, we know even less. That’s why we decided to take a look for ourselves: we kicked off with more than 1,000 products before narrowing our study down to a shortlist of 40, which we analyzed to identify broad trends, features and gaps.
Here are five key takeaways:
- The market for homegrown digital Personalized Learning products in the developing world is growing, with local innovators leading the way, but it is also uneven: some countries – including India, China, Brazil, Kenya, Nigeria and South Africa – have multiple products competing, while market penetration is weak in francophone central and west Africa, small island developing states, and some low-income countries. Why is this important? Because local innovation is critical, and so is including countries with similar challenges and learning gaps.
- We discovered that most solutions deployed artificial intelligence to dynamically adapt learning paths to individual students. They also demanded levels of hardware and connectivity that can be tough to find in the developing world, and sometimes even registering and logging-on threw up challenges. Why is this important? While AI is a useful emerging tool, more research is necessary to understand the effectiveness, accuracy, and bias of different algorithmic approaches.
- Students who are already disadvantaged remain underserved by many digital Personalized Learning solutions, including learners with disabilities, out-of-school children, ethnic minorities, and displaced children. Why is this important? Not only are these learners highly disadvantaged to begin with, but these are the very gaps digital Personalized Learning could help address.
- We discovered that most digital Personalized Learning products conduct some kind of evaluation, but the results are often not publicly available and comparing them can be difficult. Why is this important? If the impact of digital Personalized Learning products is not robustly measured, available and comparable, decisions about what to buy, where to invest, and what (and how) to scale will be difficult to make.
- We also found some concerning gaps in data privacy and protection policies. Why is this important? While data is needed to inform learning adaptation, more attention needs to be paid to safeguarding it. Because when it comes to data governance, children are more vulnerable than adults and their data must be treated differently to ensure their privacy and protection.
Don’t think it’s all bad news! We were happy to see the products we studied offering homegrown solutions and innovations, features to engage teachers and to see them being used flexibly across different educational settings – whether that’s in class, after school or at home). But we need to see more. More equitable access, more careful evaluation of features and implementation, better support for educators, parents and school leaders in facilitating children’s learning journeys, more government involvement, and more attention paid to impact measurement, data privacy and protection. Because for years educators have advocated the transformative potential of digital Personalized Learning. With some work, we can finally realize this potential and take a great leap towards ending our learning crisis.