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  1.  10
    Using Video Game Telemetry Data to Research Motor Chunking, Action Latencies, and Complex Cognitive‐Motor Skill Learning.Joseph J. Thompson, C. M. McColeman, Ekaterina R. Stepanova & Mark R. Blair - 2017 - Topics in Cognitive Science 9 (2):467-484.
    Many theories of complex cognitive-motor skill learning are built on the notion that basic cognitive processes group actions into easy-to-perform sequences. The present work examines predictions derived from laboratory-based studies of motor chunking and motor preparation using data collected from the real-time strategy video game StarCraft 2. We examined 996,163 action sequences in the telemetry data of 3,317 players across seven levels of skill. As predicted, the latency to the first action is delayed relative to the other actions in the (...)
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  2.  76
    Grapheme-Color Synaesthesia Benefits Rule-Based Category Learning.Marcus R. Watson, Mark R. Blair, Pavel Kozik, Kathleen A. Akins & James T. Enns - 2012 - Consciousness and Cognition 21 (3):1533-1540.
    Researchers have long suspected that grapheme-color synaesthesia is useful, but research on its utility has so far focused primarily on episodic memory and perceptual discrimination. Here we ask whether it can be harnessed during rule-based Category learning. Participants learned through trial and error to classify grapheme pairs that were organized into categories on the basis of their associated synaesthetic colors. The performance of synaesthetes was similar to non-synaesthetes viewing graphemes that were physically colored in the same way. Specifically, synaesthetes learned (...)
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  3.  19
    Errors, Efficiency, and the Interplay Between Attention and Category Learning.Mark R. Blair, Marcus R. Watson & Kimberly M. Meier - 2009 - Cognition 112 (2):330-336.
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  4.  18
    Waiting and Weighting: Information Sampling is a Balance Between Efficiency and Error-Reduction.Kimberly M. Meier & Mark R. Blair - 2013 - Cognition 126 (2):319-325.
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  5. The Impact of Category Type and Working Memory Span on Attentional Learning in Categorization.Mark R. Blair, Lihan Chen, Kimberly M. Meier, Michael J. Wood, Marcus R. Watson & Ulric Wong - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.