| Title |
The benefits and caveats of using clickstream data to understand student self-regulatory behaviors: opening the black box of learning processes
|
|---|---|
| Published in |
International Journal of Educational Technology in Higher Education, April 2020
|
| DOI | 10.1186/s41239-020-00187-1 |
| Authors |
Rachel Baker, Di Xu, Jihyun Park, Renzhe Yu, Qiujie Li, Bianca Cung, Christian Fischer, Fernando Rodriguez, Mark Warschauer, Padhraic Smyth |
X Demographics
The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 31% |
| Spain | 2 | 13% |
| United Kingdom | 1 | 6% |
| South Africa | 1 | 6% |
| Germany | 1 | 6% |
| Belgium | 1 | 6% |
| Unknown | 5 | 31% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 50% |
| Members of the public | 5 | 31% |
| Science communicators (journalists, bloggers, editors) | 3 | 19% |
Mendeley readers
The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 115 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 16% |
| Lecturer | 10 | 9% |
| Researcher | 9 | 8% |
| Student > Bachelor | 8 | 7% |
| Student > Doctoral Student | 7 | 6% |
| Other | 23 | 20% |
| Unknown | 40 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 24 | 21% |
| Social Sciences | 11 | 10% |
| Psychology | 9 | 8% |
| Engineering | 4 | 3% |
| Arts and Humanities | 3 | 3% |
| Other | 16 | 14% |
| Unknown | 48 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 14 June 2022.
All research outputs
#1,886,450
of 23,862,416 outputs
Outputs from International Journal of Educational Technology in Higher Education
#138
of 393 outputs
Outputs of similar age
#47,600
of 377,290 outputs
Outputs of similar age from International Journal of Educational Technology in Higher Education
#10
of 15 outputs
Altmetric has tracked 23,862,416 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 393 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.2. This one has gotten more attention than average, scoring higher than 65% 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 377,290 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 87% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.