↓ Skip to main content

The influence of element type and crossed relation on the difficulty of chunk decomposition

Overview of attention for article published in Frontiers in Psychology, July 2015
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
11 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The influence of element type and crossed relation on the difficulty of chunk decomposition
Published in
Frontiers in Psychology, July 2015
DOI 10.3389/fpsyg.2015.01025
Pubmed ID
Authors

Zhonglu Zhang, Ke Yang, Christopher M. Warren, Guang Zhao, Peng Li, Yi Lei, Hong Li

Abstract

Chunk decomposition is an aspect of problem solving that involves decomposing a pattern into its component parts in order to regroup them into a new pattern. Previous work suggests that the primary source of difficulty in chunk decomposition is whether a problem's solution requires removing a part that is a meaningful perceptual pattern (termed a chunk) or not (a non-chunk). However, the role of spatial overlap (crossed relation or not) has been ignored in this line of research. Here, we dissociated the role of element type and crossed relation in chunk decomposition problems by employing a Chinese character transformation task. We replicated the finding that when the to-be-removed element is a non-chunk, the problem is more difficult to solve than when the element is a chunk. However, this result held only if the elements had no crossed relation. Relative to non-crossed relation, problems that involved removing elements that overlapped with the remaining character were more difficult to solve irrespective of the element type. We conclude that both element type and crossed relation can cause the difficulty of chunk decomposition and crossed relation plays more important role in preventing people from finding insightful ways to decompose chunk relative to element type.

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 18%
Student > Postgraduate 2 18%
Librarian 1 9%
Lecturer > Senior Lecturer 1 9%
Student > Ph. D. Student 1 9%
Other 3 27%
Unknown 1 9%
Readers by discipline Count As %
Psychology 5 45%
Engineering 2 18%
Business, Management and Accounting 1 9%
Chemistry 1 9%
Pharmacology, Toxicology and Pharmaceutical Science 1 9%
Other 0 0%
Unknown 1 9%
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 23 July 2015.
All research outputs
#18,418,919
of 22,817,213 outputs
Outputs from Frontiers in Psychology
#22,138
of 29,762 outputs
Outputs of similar age
#189,490
of 263,718 outputs
Outputs of similar age from Frontiers in Psychology
#485
of 573 outputs
Altmetric has tracked 22,817,213 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,762 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 19th percentile – i.e., 19% 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 263,718 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 573 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.