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Mendeley readers
Chapter title |
Student’s Performance Prediction Using Data Mining Technique Depending on Overall Academic Status and Environmental Attributes
|
---|---|
Chapter number | 66 |
Book title |
International Conference on Innovative Computing and Communications
|
Published by |
Springer, Singapore, July 2020
|
DOI | 10.1007/978-981-15-5148-2_66 |
Book ISBNs |
978-9-81-155147-5, 978-9-81-155148-2
|
Authors |
Syeda Farjana Shetu, Mohd Saifuzzaman, Nazmun Nessa Moon, Sharmin Sultana, Ridwanullah Yousuf, Shetu, Syeda Farjana, Saifuzzaman, Mohd, Moon, Nazmun Nessa, Sultana, Sharmin, Yousuf, Ridwanullah |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 38 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Lecturer | 6 | 16% |
Student > Bachelor | 4 | 11% |
Student > Master | 2 | 5% |
Student > Postgraduate | 2 | 5% |
Student > Ph. D. Student | 2 | 5% |
Other | 5 | 13% |
Unknown | 17 | 45% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 10 | 26% |
Engineering | 5 | 13% |
Arts and Humanities | 2 | 5% |
Social Sciences | 2 | 5% |
Business, Management and Accounting | 1 | 3% |
Other | 1 | 3% |
Unknown | 17 | 45% |