Name
Abstract | ||
|---|---|---|
This article describes experiments with a tool, called CourseObservatory, that applies sentiment analysis to comments made by students during course surveys. The main objective is to provide course coordinators and teachers with relevant information about the courses students take based on their qualitative feedbacks. The experiments use a dataset that contains comments in Portuguese found in questionnaires filled out by students from mid-2005 to the first semester of 2018, with a total of nearly 170,000 comments, after a cleaning process that removes blank comments. The experiments show that comments made by students are influenced by the final status achieved (approved or failed), among other facts. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICALT.2019.00053 | 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT) |
Keywords | Field | DocType |
Sentiment Analysis,Educational Data Mining,Data Visualisation | Data visualization,Sentiment analysis,Computer science,Portuguese,Knowledge management,Blank,Mathematics education,Educational data mining | Conference |
Volume | ISSN | ISBN |
2161-377X | 2161-3761 | 978-1-7281-3486-4 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haydee Jimenez | 1 | 1 | 0.70 |
| Marco Antonio Casanova | 2 | 0 | 0.34 |
| Bernardo Pereira Nunes | 3 | 185 | 30.96 |
| Anna Carolina Finamore | 4 | 0 | 0.34 |