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Eye Movements and Cognitive Strategy in a Fluid Intelligence Test: Item Type Analysis

Overview of attention for article published in Frontiers in Psychology, March 2018
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Title
Eye Movements and Cognitive Strategy in a Fluid Intelligence Test: Item Type Analysis
Published in
Frontiers in Psychology, March 2018
DOI 10.3389/fpsyg.2018.00380
Pubmed ID
Authors

Paulo G. Laurence, Tatiana P. Mecca, Alexandre Serpa, Romain Martin, Elizeu C. Macedo

Abstract

Eye movements help to infer the cognitive strategy that a person uses in fluid intelligence tests. However, intelligence tests demand different relations/rules tokens to be solved, such as rule direction, which is the continuation, variation or overlay of geometric figures in the matrix of the intelligence test. The aim of this study was to understand whether eye movements could predict the outcome of an intelligence test and in the rule item groups. Furthermore, we sought to identify which measure is best for predicting intelligence test scores and to understand if the rule item groups use the same strategy. Accordingly, 34 adults completed a computerized intelligence test with an eye-tracking device. The toggling rate, that is, the number of toggles on each test item equalized by the item latency explained 45% of the variance of the test scores and a significant amount of the rule tokens item groups. The regression analyses also indicated toggling rate as the best measure for predicting the score and that all the rule tokens seem to respect the same strategy. No correlation or difference were found between baseline pupil size and fluid intelligence. Wiener Matrizen-Test 2 was demonstrated to be a good instrument for the purpose of this study. Finally, the implications of these findings for an understanding of cognition are discussed.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 15%
Student > Bachelor 6 13%
Student > Master 5 10%
Student > Ph. D. Student 5 10%
Student > Doctoral Student 3 6%
Other 4 8%
Unknown 18 38%
Readers by discipline Count As %
Psychology 20 42%
Neuroscience 3 6%
Computer Science 1 2%
Arts and Humanities 1 2%
Social Sciences 1 2%
Other 1 2%
Unknown 21 44%
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 21 March 2018.
All research outputs
#15,494,712
of 23,026,672 outputs
Outputs from Frontiers in Psychology
#18,969
of 30,283 outputs
Outputs of similar age
#212,230
of 332,397 outputs
Outputs of similar age from Frontiers in Psychology
#440
of 582 outputs
Altmetric has tracked 23,026,672 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 30,283 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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We're also able to compare this research output to 582 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.