Technological advances and organizational changes in the modern workplace have created an unprecedented and continuous demand for training. Simultaneously, the technology for delivering training has advanced rapidly, so that traditional classroom approaches are being replaced by distance learning. In distributed learning and training, which are now prevalent in industry, academia, and the government, students can be separated by both time and space. The increased use of such technology raises the question of how best to implement it for optimal results. In ""Toward a Science of Distributed Learning"", the contributors step up to the challenge by presenting theoretically-driven research that at the same time considers the characteristics and needs of learners. Drawing on findings from the cognitive and organizational sciences, they tackle such questions as the difference between distributed and collocated learning and performance, the effect of learner control in automated training, and the power of narrative in debriefing at a distance. This volume provides rich data and avenues for future research side-by-side with practical applications for today's fast-changing organizations.
