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Mendeley readers
Chapter title |
Predicting Student Performance from Multiple Data Sources
|
---|---|
Chapter number | 90 |
Book title |
Artificial Intelligence in Education
|
Published in |
Lecture notes in computer science, June 2015
|
DOI | 10.1007/978-3-319-19773-9_90 |
Book ISBNs |
978-3-31-919772-2, 978-3-31-919773-9
|
Authors |
Irena Koprinska, Joshua Stretton, Kalina Yacef |
Editors |
Cristina Conati, Neil Heffernan, Antonija Mitrovic, M. Felisa Verdejo |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 31 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 26% |
Student > Master | 6 | 19% |
Other | 3 | 10% |
Professor > Associate Professor | 2 | 6% |
Professor | 2 | 6% |
Other | 5 | 16% |
Unknown | 5 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 10 | 32% |
Engineering | 3 | 10% |
Business, Management and Accounting | 2 | 6% |
Social Sciences | 2 | 6% |
Economics, Econometrics and Finance | 2 | 6% |
Other | 4 | 13% |
Unknown | 8 | 26% |