SA-E: Sentiment Analysis for Education
Frontiers in artificial intelligence and applicationsPublished 1 January 2013Open access
Nabeela Altrabsheh, Gaber Mohamed Medhat, Mihaela Cocea
Citations98
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TL;DR
How feedback can be collected via social media such as Twitter and how using sentiment analysis on educational data can help improve teaching are discussed and the proposed system Sentiment Analysis for Education (SA-E) is introduced.
Abstract
Educational data mining (EDM) is an important research area that is used to improve education by monitoring students performance and trying to understand the students' learning. Taking feedback from students at the end of the semester, however, has the disadvantage of not benefitting the students that have already taken the course. To benefit the current students, feedback should be given in real time and addressed in real time. This would enable students and lecturers to address teaching and learning issues in the most beneficial way for the students. Analysing students' feedback using sentiment analysis techniques can identify the students' positive or negative feelings, or even more refined emotions, that students have towards the current teaching. Feedback can be collected in a variety of ways, with previous research using student response systems such as clickers, SMS and mobile phones. This paper will discuss how feedback can be collected via social media such as Twitter and how using sentiment analysis on educational data can help improve teaching. The paper also introduces our proposed system Sentiment Analysis for Education (SA-E).
Keywords
Computer Science
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