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Introducing StatHand: A Cross-Platform Mobile Application to Support Students’ Statistical Decision Making

Overview of attention for article published in Frontiers in Psychology, February 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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Title
Introducing StatHand: A Cross-Platform Mobile Application to Support Students’ Statistical Decision Making
Published in
Frontiers in Psychology, February 2016
DOI 10.3389/fpsyg.2016.00288
Pubmed ID
Authors

Peter J. Allen, Lynne D. Roberts, Frank D. Baughman, Natalie J. Loxton, Dirk Van Rooy, Adam J. Rock, James Finlay

Abstract

Although essential to professional competence in psychology, quantitative research methods are a known area of weakness for many undergraduate psychology students. Students find selecting appropriate statistical tests and procedures for different types of research questions, hypotheses and data types particularly challenging, and these skills are not often practiced in class. Decision trees (a type of graphic organizer) are known to facilitate this decision making process, but extant trees have a number of limitations. Furthermore, emerging research suggests that mobile technologies offer many possibilities for facilitating learning. It is within this context that we have developed StatHand, a free cross-platform application designed to support students' statistical decision making. Developed with the support of the Australian Government Office for Learning and Teaching, StatHand guides users through a series of simple, annotated questions to help them identify a statistical test or procedure appropriate to their circumstances. It further offers the guidance necessary to run these tests and procedures, then interpret and report their results. In this Technology Report we will overview the rationale behind StatHand, before describing the feature set of the application. We will then provide guidelines for integrating StatHand into the research methods curriculum, before concluding by outlining our road map for the ongoing development and evaluation of StatHand.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Netherlands 1 3%
France 1 3%
Norway 1 3%
Unknown 36 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 23%
Researcher 5 13%
Lecturer 4 10%
Professor > Associate Professor 4 10%
Student > Bachelor 3 8%
Other 11 28%
Unknown 4 10%
Readers by discipline Count As %
Psychology 13 33%
Computer Science 4 10%
Linguistics 3 8%
Social Sciences 2 5%
Nursing and Health Professions 1 3%
Other 8 20%
Unknown 9 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 03 May 2017.
All research outputs
#4,070,438
of 22,852,911 outputs
Outputs from Frontiers in Psychology
#6,849
of 29,874 outputs
Outputs of similar age
#62,877
of 297,592 outputs
Outputs of similar age from Frontiers in Psychology
#136
of 456 outputs
Altmetric has tracked 22,852,911 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 29,874 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has done well, scoring higher than 77% 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 297,592 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 78% of its contemporaries.
We're also able to compare this research output to 456 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.