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Examining the Roles of Reasoning and Working Memory in Predicting Casual Game Performance across Extended Gameplay

Overview of attention for article published in Frontiers in Psychology, March 2017
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Title
Examining the Roles of Reasoning and Working Memory in Predicting Casual Game Performance across Extended Gameplay
Published in
Frontiers in Psychology, March 2017
DOI 10.3389/fpsyg.2017.00203
Pubmed ID
Authors

Michael B. Kranz, Pauline L. Baniqued, Michelle W. Voss, Hyunkyu Lee, Arthur F. Kramer

Abstract

The variety and availability of casual video games presents an exciting opportunity for applications such as cognitive training. Casual games have been associated with fluid abilities such as working memory (WM) and reasoning, but the importance of these cognitive constructs in predicting performance may change across extended gameplay and vary with game structure. The current investigation examined the relationship between cognitive abilities and casual game performance over time by analyzing first and final session performance over 4-5 weeks of game play. We focused on two groups of subjects who played different types of casual games previously shown to relate to WM and reasoning when played for a single session: (1) puzzle-based games played adaptively across sessions and (2) speeded switching games played non-adaptively across sessions. Reasoning uniquely predicted first session casual game scores for both groups and accounted for much of the relationship with WM. Furthermore, over time, WM became uniquely important for predicting casual game performance for the puzzle-based adaptive games but not for the speeded switching non-adaptive games. These results extend the burgeoning literature on cognitive abilities involved in video games by showing differential relationships of fluid abilities across different game types and extended play. More broadly, the current study illustrates the usefulness of using multiple cognitive measures in predicting performance, and provides potential directions for game-based cognitive training research.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 15%
Student > Master 8 15%
Researcher 6 12%
Student > Bachelor 6 12%
Student > Doctoral Student 5 10%
Other 10 19%
Unknown 9 17%
Readers by discipline Count As %
Psychology 21 40%
Neuroscience 7 13%
Computer Science 4 8%
Medicine and Dentistry 3 6%
Engineering 2 4%
Other 5 10%
Unknown 10 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 February 2017.
All research outputs
#20,400,885
of 22,950,943 outputs
Outputs from Frontiers in Psychology
#24,292
of 30,094 outputs
Outputs of similar age
#268,283
of 307,962 outputs
Outputs of similar age from Frontiers in Psychology
#476
of 536 outputs
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We're also able to compare this research output to 536 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.