Research Labs - [ Problem Solving and Learning Lab ]
Research in the lab focuses on two main areas. The first line of research seeks to understand how people solve complex problems especially when the problem requires the generation of novel or creative solutions. When people begin working on a difficult problem, they may reach an impasse where they fail to come up with any new ideas about how to solve the problem. Sometime later, they may have a feeling of insight when they suddenly come up with a possible solution to the problem. People often can not explain where this idea came from. Some of our findings show that the source of some new problem solving ideas is in the environment even if people are not aware that they just saw something that helped them solve a problem. We are interested in applying these kinds of findings to understand how people achieve insightful and creative solutions to difficult problems. For example, engineering design is a complex task to which we have applied our results.
The second line or research in the lab involves examining the neural correlates of employing effective learning strategies. When students study for an exam, one of the most common strategies is to reread the textbook or their class notes. Unfortunately, this learning strategy is one of the least effective. A strategy called self-explanation in which students attempt to explain the text to themselves has been shown to be much more effective. In fact, this strategy was discovered by examining what good students do naturally when they study and solve problems. Our work in this area has focused on understanding the neural correlates of these kinds of effective learning strategies. In addition, we have started to examine why some students find it difficult to self-explain while others perform well. Understanding the neural systems involved in this kind of task will help to bridge the gap between basic findings from cognitive neuroscience and our understanding of the kinds of complex learning tasks that people perform daily. The results of this work have the potential to help us design more effective computer tutoring systems that improve learning.
