Discourse Comprehension and Metacomprehension
This line of research 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. This line of inquiry has led us to examine metacomprehension, the assessment of one’s own comprehension. 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.
*Wong A.Y., Moss J., Schunn C.D. (in press). Tracking reading strategy utilization through pupillometry. Australasian Journal of Educational Psychology.
Moss, J., Schunn, C. D., (2015). Comprehension through explanation as the interaction of the brain’s coherence and cognitive control networks. Frontiers in Human Neuroscience, 9(562). PDF
Moss, J., Schunn, C. D., Schneider, W., & McNamara, D. S. (2013). The nature of mind wandering during reading varies with the cognitive control demands of the reading strategy. Brain Research, 1539, 48-60. PDF
Moss, J., Schunn, C. D., Schneider, W., McNamara, D. S. (2011). An fMRI study of zoning out during strategic reading comprehension. Proceedings of the Thirty-third Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. PDF
Moss, J., Schunn, C., Schnider, W., McNamara, D., VanLehn, K. (2010). An fMRI Study of Strategic Reading Comprehension. Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society. Portland, OR. PDF
This 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.
Cranford, E. A., Moss, J. (2012). Is insight always the same? A protocol analysis of insight in compound remote associate problems. The Journal of Problem Solving, 4(1), Article 7. PDF
Cranford, E. A., Moss, J. (2011). Is insight always the same? An fMRI study of insight. Proceedings of the Thirty-third Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. PDF
Moss, J., Kotovsky, K., Cagan, J. (2010). The effect of incidental hints when problems are suspended before, during, or after an impasse. Journal of Experimental Psychology: Learning, Memory, and Cognition. PDF
Tseng, I., Moss, J., Cagan, J., & Kotovsky, K. (2008). The role of timing and analogical similarity in the stimulation of idea generation in design, Design Studies, 203-221. PDF
Moss, J., Kotovsky, K., & Cagan, J. (2007). The influence of open goals on the acquisition of problem relevant information. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(5), 876-891. PDF
Moss, J., Cagan, J., & Kotovsky, K. (2004). Learning from design experience in an agent-based design system. Research in Engineering Design, 15(2), 77-92. PDF
Individual Differences in Skill Acquisition
Multitasking is the ability to interleave tasks that vary in duration and the demands placed on cognitive resources. The Abstract Decision Making (ADM) task correlates with performance in real-world multitasking environments (Joslyn & Hunt, 1998). This study uses the ADM to measure multitasking ability. Our hypothesis is that use of consistent and effective task strategies partially explain individual differences in multitasking ability. This was investigated using behavioral and fMRI measures. The behavioral results show a correlation between strategy consistency and individual differences in ADM performance and support the strategy hypothesis. The fMRI results suggest that executive control areas of the brain are involved in task performance, but that activation in these areas alone does not explain differences in ADM performance. However, activation in other areas, including temporo-parietal regions, is correlated with individual differences in performance.
*Jones, W. E., Moss, J. (2015). Interruption-recovery training transfers to novel tasks. Proceedings of the Thirty-seventh Annual Conference of the Cognitive Science Society (pp. 1027-1032), Austin, TX: Cognitive Science Society. PDF
*Bai, H., *Jones, W. E., Moss, J., & Doane, S. M. (2014). Relating individual differences in cognitive ability to multitasking performance: Interruption recovery and task difficulty. Learning and Individual Differences. PDF