@article{gray17csj-pdl,
title = {Plateaus, Dips, and Leaps: Where to Look for Inventions and Discoveries during Skilled Performance},
author = {Wayne D. Gray and John K. Lindstedt},
url = {http://homepages.rpi.edu/~grayw/pubs/papers/2017/gray17csj-pdl.pdf},
doi = {10.1111/cogs.12412},
year = {2017},
date = {2017-10-18},
journal = {Cognitive Science},
volume = {41},
number = {7},
pages = {1838-1870},
abstract = {The framework of plateaus, dips, and leaps shines light on periods when individuals may be inventing new methods of skilled performance. We begin with a review of the role performance plateaus have played in (a) experimental psychology, (b) human--computer interaction, and (c) cognitive science. We then reanalyze two classic studies of individual performance to show plateaus and dips which resulted in performance leaps. For a third study, we show how the statistical methods of Changepoint Analysis plus a few simple heuristics may direct our focus to periods of performance change for individuals. For the researcher, dips become the marker of exploration where performance suffers as new methods are invented and tested. Leaps mark the implementation of a successful new method and an incremental jump above the path plotted by smooth and steady log--log performance increments. The methods developed during these dips and leaps are the key to surpassing one's teachers and acquiring extreme expertise.},
keywords = {BreakOut, changepoint detection, digit span, dips, expertise, extreme expertise, leaps, performance, plateaus, Space Fortress},
pubstate = {published},
tppubtype = {article}
}
The framework of plateaus, dips, and leaps shines light on periods when individuals may be inventing new methods of skilled performance. We begin with a review of the role performance plateaus have played in (a) experimental psychology, (b) human--computer interaction, and (c) cognitive science. We then reanalyze two classic studies of individual performance to show plateaus and dips which resulted in performance leaps. For a third study, we show how the statistical methods of Changepoint Analysis plus a few simple heuristics may direct our focus to periods of performance change for individuals. For the researcher, dips become the marker of exploration where performance suffers as new methods are invented and tested. Leaps mark the implementation of a successful new method and an incremental jump above the path plotted by smooth and steady log--log performance increments. The methods developed during these dips and leaps are the key to surpassing one's teachers and acquiring extreme expertise.
@article{gray17topiCS.gxp,
title = {Game-XP: Action Games as Experimental Paradigms for Cognitive Science},
author = {Gray, Wayne D.},
url = {http://homepages.rpi.edu/~grayw/pubs/papers/2017/gray17topics.gxp.pdf},
doi = {10.1111/tops.12260},
year = {2017},
date = {2017-04-15},
journal = {Topics in Cognitive Science},
volume = {9},
number = {2},
pages = {289--307},
abstract = {Why games? How could anyone consider action games an experimental paradigm for Cognitive Science? In 1973, as one of three strategies he proposed for advancing Cognitive Science, Allen Newell exhorted us to ``accept a single complex task and do all of it.'' More specifically, he told us that rather than taking an ``experimental psychology as usual approach,'' we should ``focus on a series of experimental and theoretical studies around a single complex task'' so as to demonstrate that our theories of human cognition were powerful enough to explain ``a genuine slab of human behavior'' with the studies fitting into a detailed theoretical picture. Action games represent the type of experimental paradigm that Newell was advocating and the current state of programming expertise and laboratory equipment, along with the emergence of Big Data and naturally occurring datasets, provide the technologies and data needed to realize his vision. Action games enable us to escape from our field's regrettable focus on novice performance to develop theories that account for the full range of expertise through a twin focus on expertise sampling (across individuals) and longitudinal studies (within individuals) of simple and complex tasks.},
keywords = {Action games, Chess, cognitive skill acquisition, Cohort analysis, Computer games, Expertise sampling, extreme expertise, Halo, Longitudinal studies, Skilled performance, Space Fortress, StarCraft, Tetris, Verbal protocol analysis, Video games},
pubstate = {published},
tppubtype = {article}
}
Why games? How could anyone consider action games an experimental paradigm for Cognitive Science? In 1973, as one of three strategies he proposed for advancing Cognitive Science, Allen Newell exhorted us to ``accept a single complex task and do all of it.'' More specifically, he told us that rather than taking an ``experimental psychology as usual approach,'' we should ``focus on a series of experimental and theoretical studies around a single complex task'' so as to demonstrate that our theories of human cognition were powerful enough to explain ``a genuine slab of human behavior'' with the studies fitting into a detailed theoretical picture. Action games represent the type of experimental paradigm that Newell was advocating and the current state of programming expertise and laboratory equipment, along with the emergence of Big Data and naturally occurring datasets, provide the technologies and data needed to realize his vision. Action games enable us to escape from our field's regrettable focus on novice performance to develop theories that account for the full range of expertise through a twin focus on expertise sampling (across individuals) and longitudinal studies (within individuals) of simple and complex tasks.
