Students' real-time feedback has numerous advantages in education, however, analysing feedback while teaching is both stressful and time consuming. To address this problem, we propose to analyse feedback automatically using sentiment analysis. Sentiment analysis is domain dependent and although it has been applied to the educational domain before, it has not been previously used for real-time feedback. To find the best model for automatic analysis we look at four aspects: preprocessing, features, machine learning techniques and the use of the neutral class. We found that the highest result for the four aspects is Support Vector Machines (SVM) with the highest level of preprocessing, unigrams and no neutral class, which gave a 95 percent accuracy.
|Title of host publication||IEEE 26th international conference on tools with artificial intelligence|
|Place of Publication||Limassol, Cyprus|
|Number of pages||5|
|Publication status||Published - 31 Dec 2014|
|Event||IEEE 26th international conference on tools with artificial intelligence - Limassol, Cyprus, 10-12 Nov. 2014|
Duration: 31 Dec 2014 → …
|Conference||IEEE 26th international conference on tools with artificial intelligence|
|Period||31/12/14 → …|
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- Sentiment Analysis
- Educational Data Mining
- Feature Selection
- Real-time Feedback
Altrabsheh, N., Cocea, M., & Fallahkhair, S. (2014). Sentiment analysis: towards a tool for analysing real-time students feedback. In IEEE 26th international conference on tools with artificial intelligence (pp. 419-423). IEEE. https://doi.org/10.1109/ICTAI.2014.70