@article{Gray2016,
title = {Plateaus, Dips, and Leaps: Where to Look for Inventions and Discoveries during Skilled Performance},
author = {Wayne D. Gray and John K. Lindstedt},
doi = {10.1111/cogs.12412},
year = {2016},
date = {2016-10-18},
journal = {Cognitive Science},
abstract = {120 years ago the emergent field of experimental psychology became embroiled in debates as to whether plateaus in performance are real (or not) and if so whether they were due to periods in which league-stepping methods originally defined by Bryan & Harter, 1897, 1899, as a hierarchy of habits that enabled experts to step leagues while novices were ``bustling over furlongs or inches'') were being acquired (or not). 20 years ago both the human-computer interaction (HCI) and cognitive science (CogSci) communities were seized with concerns over performance plateaus (i.e., extended periods of stable suboptimal performance) from experts. For HCI this was viewed as a systems problem and referred to as the Paradox of the Active User. CogSci diagnosed this as a training problem and embraced Deliberate Practice. We review this history and clarify the distinction between performance plateaus and asymptotes, suggesting that the former may be remediated by Deliberate Practice whereas the latter cannot. We then present a modest revision to the concept of Deliberate Practice which focuses on methods (i.e., patterns of cognitive, perceptual, and motor activities) that produce league-stepping jumps in performance and which questions whether all hard practice should be considered Deliberate Practice.},
keywords = {BreakOut, changepoint detection, digit span, dips, expertise, extreme expertise, leaps, performance, plateaus, Space Fortress},
pubstate = {published},
tppubtype = {article}
}
120 years ago the emergent field of experimental psychology became embroiled in debates as to whether plateaus in performance are real (or not) and if so whether they were due to periods in which league-stepping methods originally defined by Bryan & Harter, 1897, 1899, as a hierarchy of habits that enabled experts to step leagues while novices were ``bustling over furlongs or inches'') were being acquired (or not). 20 years ago both the human-computer interaction (HCI) and cognitive science (CogSci) communities were seized with concerns over performance plateaus (i.e., extended periods of stable suboptimal performance) from experts. For HCI this was viewed as a systems problem and referred to as the Paradox of the Active User. CogSci diagnosed this as a training problem and embraced Deliberate Practice. We review this history and clarify the distinction between performance plateaus and asymptotes, suggesting that the former may be remediated by Deliberate Practice whereas the latter cannot. We then present a modest revision to the concept of Deliberate Practice which focuses on methods (i.e., patterns of cognitive, perceptual, and motor activities) that produce league-stepping jumps in performance and which questions whether all hard practice should be considered Deliberate Practice.
@conference{marc16csc,
title = {Where Should Researchers Look for Strategy Discoveries during the Acquisition of Complex Task Performance? The Case of Space Fortress},
author = {Destefano, Marc and Gray, Wayne D.},
editor = {Papafragou, A. and Grodner, D. and Mirman, D. and Trueswell, J. C.},
url = {http://cogworks.cogsci.rpi.edu/marc16csc-2/},
year = {2016},
date = {2016-08-05},
booktitle = {Proceedings of the 38th Annual Conference of the Cognitive Science Society},
publisher = {Cognitive Science Society},
address = {Austin, TX},
abstract = {In complex task domains, such as games, students may exceed their teachers. Such tasks afford diverse means to tradeoff one type of performance for another, combining task elements in novel ways to yield method variations and strategy discoveries that, if mastered, might produce large or small leaps in performance. For the researcher interested in the development of extreme expertise in the wild, the problem posed by such tasks is ``where to look'' to capture the explorations, trials, errors, and successes that eventually lead to the invention of superior performance. In this paper, we present several successful discoveries of methods for superior performance. For these discoveries we used Symbolic Aggregate Approximation as our method of identifying changepoints within score progressions in the venerable game of Space Fortress. By decomposing performance at these changepoints, we find previously unknown strategies that even the designers of the task had not anticipated.},
keywords = {changepoint analysis, dips, expertise, leaps, method invention, performance, plateaus, SAX, skill acquisition, Space Fortress, strategy discovery},
pubstate = {published},
tppubtype = {conference}
}
In complex task domains, such as games, students may exceed their teachers. Such tasks afford diverse means to tradeoff one type of performance for another, combining task elements in novel ways to yield method variations and strategy discoveries that, if mastered, might produce large or small leaps in performance. For the researcher interested in the development of extreme expertise in the wild, the problem posed by such tasks is ``where to look'' to capture the explorations, trials, errors, and successes that eventually lead to the invention of superior performance. In this paper, we present several successful discoveries of methods for superior performance. For these discoveries we used Symbolic Aggregate Approximation as our method of identifying changepoints within score progressions in the venerable game of Space Fortress. By decomposing performance at these changepoints, we find previously unknown strategies that even the designers of the task had not anticipated.
