We begin with a paradox: On the one hand, not nearly enough is known about exactly how learning takes place in the brain, although exciting new results are emerging thanks to improved brain imaging and a greater focus on neuroscience by government and universities. But this research is just beginning, and a much larger investment and effort are needed to answer even the most basic questions. On the other hand, more than enough is already known to motivate and drive educational reform for years to come. This article is a report from the front lines of both research on learning and the implementation of that research. The information should prove of use to anyone--faculty, administrators, researchers--concerned with how best to improve formal or informal teaching and learning, help people remember complex instructions, or change unhealthy habits and practices.
NSF Decides to Weigh In
Soon after the turn of this century, the National Science Foundation (NSF) decided to make the sort of major investment in the science of learning that had hitherto been reserved mostly for the traditional natural sciences, engineering, and mathematics. The funding mechanism involved cooperative agreements with newly created interdisciplinary multi-university centers, each receiving multimillion dollar annual awards for a maximum period of 10 years. The six centers eventually funded1 have matured into influential and sophisticated collaborations generating important science, some of which will be described in what follows. The author of this article was an NSF program director who helped to manage the Science of Learning Centers program.
Researchers at the Pittsburgh Science of Learning Center (PSLC) developed a useful starting point for any discussion of scientific evidence-based learning research: a definition of what should count as success in teaching and learning (LearnLab--Pittsburgh Science of Learning Center 2008). They characterize successful learning as "robust" and measure the degree of robustness according to three criteria: (1) long-term retention, (2) effective preparation for further or deeper learning and application, and (3) effective transfer of knowledge or skills to novel situations.
These criteria suggest the need for further refinement and research. For example, how long is "long-term"? The learning researcher will want to discover how much learning is retained--not just until the next test but for months or even years after the lessons are over. What schedule of practice best ensures long retention? Might the spacing of reminders or lessons determine how long the material will be usefully remembered? It turns out that it does and that the interval between practice sessions is correlated quite well with the length of retention (Cepeda et al. 2008; Pavlik and Anderson 2008). Other things being equal, longer intervals lead to longer retention, which is one reason why cramming the night before a test leads to poor long-term learning.
The assessment of learning is more than the testing of recall.
Defining robust learning in this multi-dimensional way is a reminder that learning is more than simple recall, and the assessment of learning is more than the testing of recall. At its best, education builds sophistication as well as knowledge. That is why robust learning is defined to include such sophisticated skills as the ability to build further knowledge on one's own and the capacity to transfer knowledge and skills to new domains related in increasingly complex ways to what was originally learned.
Clearing Away the Myths
It is common today to hear the call for "brain-based education," an indication that the public is both interested in and eager for more scientific information about the brain. Further, teachers and parents seem willing to translate research findings into practical steps that might enhance learning--if only they had access to accurate information and workable advice about how to adapt research results so as to enhance teaching and learning effectiveness. …