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Model of cognitive dynamics predicts performance on standardized tests

Abstract

In the modern knowledge economy, success demands sustained focus and high cognitive performance. Research suggests that human cognition is linked to a finite resource, and upon its depletion, cognitive functions such as self-control and decision-making may decline. While fatigue, among other factors, affects human activity, how cognitive performance evolves during extended periods of focus remains poorly understood. By analyzing performance of a large cohort answering practice standardized test questions online, we show that accuracy and learning decline as the test session progresses and recover following prolonged breaks. To explain these findings, we hypothesize that answering questions consumes some finite cognitive resources on which performance depends, but these resources recover during breaks between test questions. We propose a dynamic mechanism of the consumption and recovery of these resources and show that it explains empirical findings and predicts performance better than alternative hypotheses. While further controlled experiments are needed to identify the physiological origin of these phenomena, our work highlights the potential of empirical analysis of large-scale human behavior data to explore cognitive behavior.

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Acknowledgements

This work was supported, in part, by AFOSR (contract FA9550-10-1-0569), by DARPA (contract W911NF-12-1-0034), by ARO (contract W911NF-15-1-0142), and IARPA (contract 2017-17042800005). The research described in this paper is also part of the Analysis In Motion Initiative at Pacific Northwest National Laboratory. It was conducted under the Laboratory Directed Research and Development Program at PNNL, a multiprogram national laboratory operated by Battelle for the US Department of Energy.

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Correspondence to Kristina Lerman.

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Hodas, N.O., Hunter, J., Young, S.J. et al. Model of cognitive dynamics predicts performance on standardized tests. J Comput Soc Sc 1, 295–312 (2018). https://doi.org/10.1007/s42001-018-0025-x

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  • DOI: https://doi.org/10.1007/s42001-018-0025-x

Keywords

  • Cognitive depletion
  • Cognitive performance
  • Fatigue
  • Online testing
  • Modeling