Abstract
As the interplay between cognition and emotion is involved in every learning process, student profile should be enhanced with information regarding his/her affective state. Sentiment analysis could serve this end, through the analysis of student behavioral traces in teaching-learning environments. The purpose of the present study is to review the status of research on the field of sentiment analysis in the educational domain; exploring different ways in which sentiment analysis has been applied in the educational domain, and analyze the different techniques that researchers have adopted in developing sentiment analysis systems on educational datasets. Five different task types that sentiment analysis has served within the domain were identified, namely: (i) instruction evaluation, (ii) institutional decision/policy making, (iii) intelligent information/learning systems enhancement, (iv) assignment evaluation and feedback improvement, and (v) new research insights. From a technical perspective, a brief explanation of the different sentiment analysis techniques along with representative examples are presented. The character of this work may address the needs of a diverse group of stakeholders, including educators, social sciences researchers as well as researchers, in natural language processing in education.
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