Using Video Game Telemetry Data to Research Motor Chunking, Action Latencies, and Complex Cognitive‐Motor Skill Learning

Thompson, Joseph J.; McColeman, Caitlyn; Stepanova, Ekaterina R.; Blair, Mark R.

doi:10.1111/tops.12254

Cited by 31 publications

(42 citation statements)

References 42 publications

(70 reference statements)

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“…This focus on well‐practiced sequences of keystrokes is echoed and deepened in the Thompson et al. () paper.…”

Section: Introduction To the Papers Of This Topicmentioning

confidence: 93%

“…For web‐based or cellphone‐based games, it may be possible to obtain a complete record of skill acquistion by mining Big Data sources. Big Data: Many of the most popular games are web‐based or cellphone‐based with the side effect that much or all of the interactions, decisions, and keystrokes made during the game are available in datafiles on the internet. Hence, researchers can obtain Big Data (Griffiths, ) and/or naturally occurring datasets (NODS, see Goldstone & Lupyan, ), which contain hundreds of thousands or millions of records (e.g., Huang, Yan, Cheung, Nagapan, & Zimmermann, ; Sangster, Mendonca, & Gray, ; Stafford & Haasnoot, ; Thompson, McColeman, Stepanova, & Blair, ). Joint Action and Teams: It seems fair to say that, outside of studies of language, the cognitive revolution has not greatly influenced the study of people in cooperative or competitive settings. In recent years, Joint Action (e.g., Knoblich, Butterfill, & Sebanz, ; Sebanz & Knoblich, ) has emerged primarily as the study of interactions between two humans.…”

Section: Introductionmentioning

confidence: 99%

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Game‐XP: Action Games as Experimental Paradigms for Cognitive Science

Gray

2017

Topics in Cognitive Science

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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.

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“…This focus on well‐practiced sequences of keystrokes is echoed and deepened in the Thompson et al. () paper.…”

Section: Introduction To the Papers Of This Topicmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Game‐XP: Action Games as Experimental Paradigms for Cognitive Science

Gray

2017

Topics in Cognitive Science

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“…Playing a demanding RTS game like SC2 requires the engagement of a wide range of cognitive and motor functions (42,57,58). However, the degree to which each of these functions is engaged is not likely to be equally engaged across all stages of SC2's learning.…”

Section: Abbreviations: Sc2 -Starcraft IImentioning

confidence: 99%

Lenticular nucleus volume predicts performance in real-time strategy game - cross-sectional and training approach using voxel-based morphometry

Kowalczyk

Skorko

Dobrowolski

et al. 2020

Preprint

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It is unclear why some people learn faster than others. We performed two independent studies in which we investigated the neural basis of real-time strategy (RTS) gaming and neural predictors of RTS games skill-acquisition. In the first (cross-sectional) study we found that experts in the RTS game StarCraft II (SC2) had a larger lenticular nucleus volume than non-RTS players. We followed a cross validation procedure where we used the volume of regions identified in the first study to predict the quality of learning a new, complex skill (SC2) in a sample of individuals who were naïve to RTS games (second training study). Our findings provide new insights into how the volume of lenticular nucleus, which is associated with motor as well as cognitive functions, can be utilized to predict successful skill-learning, and be applied to a much broader context than just video games, e.g. contributing to optimizing cognitive training interventions.

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“…Four of the eight papers (Huang, Yan, Cheung, Nagappan, & Zimmermann, ; Stafford & Haasnoot, ; Thompson, McColeman, Stepanova, & Blair, ; van der Maas & Nyamsuren, ) used video‐game archival data. The analysis of large databases for studying cognition, which was not anticipated by Newell, magnifies some of the problems he identified (in particular, the peril of averaging across strategies and tasks), but also provides means to address them (e.g., using sophisticated statistical and data‐mining techniques for identifying strategies).…”

Section: Newell's Twenty‐question Paper and The Contributions Of Thismentioning

confidence: 99%

Allen Newell's Program of Research: The Video‐Game Test

Gobet

2017

Topics in Cognitive Science

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Newell (1973) argued that progress in psychology was slow because research focused on experiments trying to answer binary questions, such as serial versus parallel processing. In addition, not enough attention was paid to the strategies used by participants, and there was a lack of theories implemented as computer models offering sufficient precision for being tested rigorously. He proposed a three-headed research program: to develop computational models able to carry out the task they aimed to explain; to study one complex task in detail, such as chess; and to build computational models that can account for multiple tasks. This article assesses the extent to which the papers in this issue advance Newell's program. While half of the papers devote much attention to strategies, several papers still average across them, a capital sin according to Newell. The three courses of action he proposed were not popular in these papers: Only two papers used computational models, with no model being both able to carry out the task and to account for human data; there was no systematic analysis of a specific video game; and no paper proposed a computational model accounting for human data in several tasks. It is concluded that, while they use sophisticated methods of analysis and discuss interesting results, overall these papers contribute only little to Newell's program of research. In this respect, they reflect the current state of psychology and cognitive science. This is a shame, as Newell's ideas might help address the current crisis of lack of replication and fraud in psychology.

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Using Video Game Telemetry Data to Research Motor Chunking, Action Latencies, and Complex Cognitive‐Motor Skill Learning

Cited by 31 publications

References 42 publications

Game‐XP: Action Games as Experimental Paradigms for Cognitive Science

Game‐XP: Action Games as Experimental Paradigms for Cognitive Science

Lenticular nucleus volume predicts performance in real-time strategy game - cross-sectional and training approach using voxel-based morphometry

Allen Newell's Program of Research: The Video‐Game Test

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