Title |
Automatic distractor generation for multiple-choice English vocabulary questions
|
---|---|
Published in |
Research and Practice in Technology Enhanced Learning, October 2018
|
DOI | 10.1186/s41039-018-0082-z |
Pubmed ID | |
Authors |
Yuni Susanti, Takenobu Tokunaga, Hitoshi Nishikawa, Hiroyuki Obari |
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 % |
---|---|---|
Australia | 1 | 25% |
Unknown | 3 | 75% |
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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 48 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 8 | 17% |
Student > Bachelor | 5 | 10% |
Researcher | 3 | 6% |
Student > Ph. D. Student | 3 | 6% |
Student > Doctoral Student | 2 | 4% |
Other | 5 | 10% |
Unknown | 22 | 46% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 13 | 27% |
Linguistics | 5 | 10% |
Social Sciences | 3 | 6% |
Arts and Humanities | 1 | 2% |
Physics and Astronomy | 1 | 2% |
Other | 1 | 2% |
Unknown | 24 | 50% |