U.S. Department of Energy

Pacific Northwest National Laboratory

Analysis and parameter estimation for the dynamics of cognitive performance

Publish Date: 
Monday, November 30, 2015
It is useful to understand and to predict the dynamics of cognitive performance and how the timing of breaks affects this process. Prior research analyzed data from online standardized test questions, enabling the creation of a model in which a secondary resource replenishes a primary resource that determines the probability of a successful outcome. However, parameters for this model require further validation. We tested a number of techniques using data generated from the model and found an information theoretic measure, KL divergence, to be the best for parameter estimation for this model. Other techniques had difficulties dealing with noise in the system or mapping between the binary data and the continuous model. We also investigated the distribution of the primary resource given the outcome. Additional work could develop and/or refine an analysis method for verifying parameter values.
Hunter JS. 2015. Analysis and parameter estimation for the dynamics of cognitive performance. PNNL-24986, Pacific Northwest National Laboratory, Richland, WA.
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