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The utilization of data analysis techniques in predicting student performance in massive open online courses (MOOCs)

Overview of attention for article published in Research and Practice in Technology Enhanced Learning, July 2015
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
30 Dimensions

Readers on

mendeley
111 Mendeley
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Title
The utilization of data analysis techniques in predicting student performance in massive open online courses (MOOCs)
Published in
Research and Practice in Technology Enhanced Learning, July 2015
DOI 10.1186/s41039-015-0007-z
Authors

Glyn Hughes, Chelsea Dobbins

Mendeley readers

The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 3%
Finland 1 <1%
Indonesia 1 <1%
Turkey 1 <1%
Thailand 1 <1%
Unknown 104 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 30 27%
Student > Ph. D. Student 28 25%
Researcher 10 9%
Lecturer 9 8%
Student > Bachelor 6 5%
Other 16 14%
Unknown 12 11%
Readers by discipline Count As %
Computer Science 47 42%
Social Sciences 21 19%
Business, Management and Accounting 5 5%
Engineering 4 4%
Economics, Econometrics and Finance 3 3%
Other 13 12%
Unknown 18 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 13 August 2015.
All research outputs
#4,331,215
of 8,558,629 outputs
Outputs from Research and Practice in Technology Enhanced Learning
#18
of 22 outputs
Outputs of similar age
#111,670
of 233,898 outputs
Outputs of similar age from Research and Practice in Technology Enhanced Learning
#1
of 6 outputs
Altmetric has tracked 8,558,629 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22 research outputs from this source. They receive a mean Attention Score of 3.5. This one scored the same or higher as 4 of them.
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 233,898 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 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