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Chess knowledge predicts chess memory even after controlling for chess experience: Evidence for the role of high-level processes

Overview of attention for article published in Memory & Cognition, November 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet
twitter
5 X users
facebook
1 Facebook page
wikipedia
2 Wikipedia pages
video
1 YouTube creator

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
53 Mendeley
Title
Chess knowledge predicts chess memory even after controlling for chess experience: Evidence for the role of high-level processes
Published in
Memory & Cognition, November 2017
DOI 10.3758/s13421-017-0768-2
Pubmed ID
Authors

David M. Lane, Yu-Hsuan A. Chang

Abstract

The expertise effect in memory for chess positions is one of the most robust effects in cognitive psychology. One explanation of this effect is that chess recall is based on the recognition of familiar patterns and that experts have learned more and larger patterns. Template theory and its instantiation as a computational model are based on this explanation. An alternative explanation is that the expertise effect is due, in part, to stronger players having better and more conceptual knowledge, with this knowledge facilitating memory performance. Our literature review supports the latter view. In our experiment, a sample of 79 chess players were given a test of memory for chess positions, a test of declarative chess knowledge, a test of fluid intelligence, and a questionnaire concerning the amount of time they had played nontournament chess and the amount of time they had studied chess. We determined the numbers of tournament games the players had played from chess databases. Chess knowledge correlated .67 with chess memory and accounted for 16% of the variance after controlling for chess experience. Fluid intelligence accounted for an additional 13% of the variance. These results support the conclusion that both high-level conceptual processing and low-level recognition of familiar patterns play important roles in memory for chess positions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 9%
Student > Master 5 9%
Professor 4 8%
Student > Bachelor 4 8%
Other 2 4%
Other 10 19%
Unknown 23 43%
Readers by discipline Count As %
Psychology 12 23%
Engineering 2 4%
Agricultural and Biological Sciences 2 4%
Nursing and Health Professions 1 2%
Business, Management and Accounting 1 2%
Other 11 21%
Unknown 24 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 11 May 2023.
All research outputs
#2,120,737
of 25,211,948 outputs
Outputs from Memory & Cognition
#146
of 1,644 outputs
Outputs of similar age
#40,944
of 336,235 outputs
Outputs of similar age from Memory & Cognition
#1
of 9 outputs
Altmetric has tracked 25,211,948 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,644 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,235 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them