Predicting Students’ Emotions Using Machine Learning Techniques

Author:

Altrabsheh Nabeela,Cocea Mihaela,Fallahkhair Sanaz

Publisher

Springer International Publishing

Reference7 articles.

1. Danisman, T., Alpkocak, A.: Feeler: Emotion classification of text using vector space model. Convention Communication, Interaction and Social Intelligence 1, 53–59 (2008)

2. D’Mello, S., Jackson, T., Craig, S., Morgan, B., Chipman, P., White, H., Person, N., Kort, B., el Kaliouby, R., Picard, R., et al.: Autotutor detects and responds to learners affective and cognitive states. In: Workshop on Emotional and Cognitive Issues at the International Conference on Intelligent Tutoring Systems (2008)

3. Hanczar, B., Hua, J., Sima, C., Weinstein, J., Bittner, M., Dougherty, E.R.: Small-sample precision of roc-related estimates. Bioinformatics 26(6), 822–830 (2010)

4. Kaur, J., Saini, J.R.: Emotion detection and sentiment analysis in text corpus: a differential study with informal and formal writing styles. International Journal of Computer Applications 101(9), 1–9 (2014)

5. Kort, B., Reilly, R., Picard, R.W.: An affective model of interplay between emotions and learning: Reengineering educational pedagogy-building a learning companion. In: Advanced Learning Technologies, pp. 43–436. IEEE Computer Society (2001)

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