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Training the equidistant principle of number line spacing

Overview of attention for article published in Cognitive Processing, April 2016
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Title
Training the equidistant principle of number line spacing
Published in
Cognitive Processing, April 2016
DOI 10.1007/s10339-016-0763-8
Pubmed ID
Authors

Tanja Dackermann, Ursula Fischer, Stefan Huber, Hans-Christoph Nuerk, Korbinian Moeller

Abstract

The characteristics of effective numerical trainings are still under scientific debate. Given the importance of number line estimation due to the strong relation between task performance and arithmetic abilities, the current study aimed at training one important number line characteristic: the equidistant spacing of adjacent numbers. Following an embodied training approach, second-graders were trained using a randomized crossover design to divide a presented line into different numbers of equal segments by walking the line with equally spaced steps. Performance was recorded, and feedback as to the correct equidistant spacing was provided using the Kinect sensor system. Training effects were compared to a control training with no involvement of task-specific whole-body movements. Results indicated more pronounced specific training effects after the embodied training. Moreover, transfer effects to number line estimation and arithmetic performance were partially observed. In particular, differential training effects for bounded versus unbounded number line estimation corroborate the assumption that not only bodily experiences but also the need for a flexible adaption of the perspective on the training material might influence training success. Hence, more pronounced training effects of the embodied training might stem from different cognitive processes involved.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Germany 1 1%
Unknown 79 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 27%
Student > Master 12 15%
Researcher 8 10%
Student > Doctoral Student 7 9%
Student > Bachelor 6 7%
Other 10 12%
Unknown 16 20%
Readers by discipline Count As %
Psychology 36 44%
Sports and Recreations 4 5%
Nursing and Health Professions 3 4%
Arts and Humanities 3 4%
Mathematics 2 2%
Other 7 9%
Unknown 26 32%
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 25 April 2016.
All research outputs
#15,369,653
of 22,865,319 outputs
Outputs from Cognitive Processing
#188
of 337 outputs
Outputs of similar age
#180,508
of 300,871 outputs
Outputs of similar age from Cognitive Processing
#5
of 7 outputs
Altmetric has tracked 22,865,319 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 337 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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 300,871 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.