| Title |
The performance of some machine learning approaches and a rich context model in student answer prediction
|
|---|---|
| Published in |
Research and Practice in Technology Enhanced Learning, April 2021
|
| DOI | 10.1186/s41039-021-00159-7 |
| Authors |
Alisa Lincke, Marc Jansen, Marcelo Milrad, Elias Berge |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 25% |
| Australia | 1 | 25% |
| Belgium | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 84 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Lecturer | 7 | 8% |
| Student > Postgraduate | 5 | 6% |
| Other | 5 | 6% |
| Student > Ph. D. Student | 4 | 5% |
| Student > Master | 4 | 5% |
| Other | 10 | 12% |
| Unknown | 49 | 58% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 20% |
| Business, Management and Accounting | 4 | 5% |
| Unspecified | 3 | 4% |
| Arts and Humanities | 3 | 4% |
| Social Sciences | 3 | 4% |
| Other | 3 | 4% |
| Unknown | 51 | 61% |