| Title |
Text analytics approach to extract course improvement suggestions from students’ feedback
|
|---|---|
| Published in |
Research and Practice in Technology Enhanced Learning, June 2018
|
| DOI | 10.1186/s41039-018-0073-0 |
| Pubmed ID | |
| Authors |
Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 17% |
| Australia | 1 | 17% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 82 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 9 | 11% |
| Researcher | 8 | 10% |
| Student > Ph. D. Student | 7 | 9% |
| Lecturer | 7 | 9% |
| Student > Master | 6 | 7% |
| Other | 16 | 20% |
| Unknown | 29 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 27 | 33% |
| Engineering | 6 | 7% |
| Arts and Humanities | 3 | 4% |
| Social Sciences | 3 | 4% |
| Linguistics | 2 | 2% |
| Other | 8 | 10% |
| Unknown | 33 | 40% |