M. Bustos-López, N. Cruz-Ramírez, A. Guerra-Hernández, L. N. Sánchez-Morales, and G. Alor-Hernández. New Perspectives on Enterprise Decision-Making Applying Artificial Intelligence, volume 966 of Studies in Computational Intelligence, chapter Emotion Detection from Text in Learning Environments: A Review, pages 483–508. Springer, Cham, Switzerland, 2021. | SpringerLink
Abstract. Knowing student emotions allows teachers to efﬁciently adapt or redirect educational resources, activities, learning environments, and learning procedures within a particular educational community, where age, learning styles, and skills are already challenging factors. This book chapter introduces a literature review of text-based emotion detection in learning environments. We analyze the main APIs and tools available today for emotion detection and discuss their key characteristics. Also, we introduce a case study to detect the positive and negative polarity of two educational resources to identify the accuracy of the results obtained from ﬁve selected APIs. Finally, we discuss our conclusions and suggestions for future work.