Trends in Digital Personalized Learning
Landscape review | Taking stock of personalized learning solutions in low and middle-income countries
Digital Personalized Learning — tech solutions and products that tailor learning to individuals and their specific learning needs — hold great promise in improving learning outcomes and closing gaps for students who have fallen behind.
But for all that promise, there is a dearth of information on digital Personalized Learning products being used in the developing world. When it comes to their effectiveness, their design, their implementation, and their scalability, we know even less.
This landscape review analyzes Personalized Learning products 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 have multiple products, while there is weak market penetration in others.
Why is this important? Because local innovation is critical, and so is including countries with similar challenges and learning gaps.
- 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.
- 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.
- There are 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.