Approaches for Measuring Learning in a Digital World
Our Expanding Evidence report calls for smart change by presenting educators, policymakers, and funders with an expanded view of evidence approaches and sources of data that can help them with decision-making about learning resources.
Download the Expanding Evidence report [PDF, 1.2MB]
Change happens big in technology and it happens fast. And when public money is being spent and students’ futures are at stake, it is crucial that changes also happen smart. Our new report, Expanding Evidence Approaches for Learning in a Digital World, calls for smart change by presenting educators, policymakers, and funders with an expanded view of evidence approaches and sources of data that can help them with decision-making about learning resources.
The report discusses the promise of sophisticated digital learning systems for collecting and analyzing very large amounts of fine-grained data (“big data”) as users interact with the systems. It proposes that this data can be used by developers and researchers to improve these learning systems and strive to discover more about how people learn. It discusses the potential of developing more sophisticated ways of measuring what learners know and adaptive systems that can personalize learners’ experiences.
Additionally, the report describes an iterative R&D process, with rapid design cycles and built-in feedback loops—one familiar in industry but less so in education (however, the report provides numerous examples of applications in education). An iterative R&D process enables early-stage innovations to be rapidly deployed, widely adopted, and—through continuous improvement processes—refined and enhanced over time. This means that data collection and analysis can occur continuously and that users are integral to the improvement process.The report encourages learning technology developers, researchers, and educators to collaborate with and learn from one another as a means of accelerating progress and ensuring innovation in education.