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X Demographics
Mendeley readers
Chapter title |
Predicting Students’ Academic Performance and Main Behavioral Features Using Data Mining Techniques
|
---|---|
Chapter number | 21 |
Book title |
Advances in Data Science, Cyber Security and IT Applications
|
Published by |
Springer, Cham, December 2019
|
DOI | 10.1007/978-3-030-36365-9_21 |
Book ISBNs |
978-3-03-036364-2, 978-3-03-036365-9
|
Authors |
Suad Almutairi, Hadil Shaiba, Marija Bezbradica, Almutairi, Suad, Shaiba, Hadil, Bezbradica, Marija |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 54 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 7 | 13% |
Lecturer | 5 | 9% |
Student > Bachelor | 4 | 7% |
Student > Doctoral Student | 2 | 4% |
Researcher | 2 | 4% |
Other | 5 | 9% |
Unknown | 29 | 54% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 13 | 24% |
Mathematics | 4 | 7% |
Engineering | 4 | 7% |
Economics, Econometrics and Finance | 1 | 2% |
Nursing and Health Professions | 1 | 2% |
Other | 2 | 4% |
Unknown | 29 | 54% |