Model of cognitive dynamics predicts performance on standardized tests

Nathan O. Hodas (), Jacob Hunter (), Stephen J. Young () and Kristina Lerman ()
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Nathan O. Hodas: Pacific Northwest National Lab
Jacob Hunter: Pacific Northwest National Lab
Stephen J. Young: Pacific Northwest National Lab
Kristina Lerman: USC Information Sciences Institute

Journal of Computational Social Science, 2018, vol. 1, issue 2, No 4, 295-312

Abstract: 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.

Keywords: Cognitive depletion; Cognitive performance; Fatigue; Online testing; Modeling (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s42001-018-0025-x

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