Exploiting sentiment analysis to track emotions in students' learning diaries

Abstract

Learning diaries are instruments through which students can reflect on their learning experience. Students' sentiments, emotions, opinions and attitudes are embedded in their learning diaries as part of the process of understanding their progress during the course and the self-awareness of their goals. Learning diaries are also a very informative feedback source for instructors regarding the students' emotional well-being. However the number of diaries created during a course can become a daunting task to be manually analyzed with care, particularly when the class is large. To tackle this problem, in this paper we present a functional system for analyzing and visualizing student emotions expressed in learning diaries. The system allows instructors to automatically extract emotions and the changes in these emotions throughout students' learning experience as expressed in their diaries. The emotions extracted by the system are based on Plutchik's eight emotion categories, and they are shown over the time period that the diaries were written. The potential impact and usefulness of our system are highlighted during our experiments with promising results for improving the communication between instructors and students and enhancing the learning experience.

Sentiment Analysis: Towards a Tool for Analysing Real-Time Students Feedback

“…Sentiment analysis in the educational domain has mainly been focused on e-learning [3], [4], with little research done on classroom feedback [5]. Although e-learning and classroom education may seem similar, they differ in the types of interactions between the students and the lecturers and in the fact that the lecturer should respond to the students' feedback in real-time.…”

An Exploratory Analysis of a Hybrid OSS Company's Forum in Search of Sales Leads

“…Over the past years, a large number of SA programs have been developed to discover the sentiment content of texts in various genres including movie reviews [15], student diaries [16], education forums [17], [18], and developer platforms. For example, in Parastou et al [19], they extracted the sentiment from user and developer mailing lists of two of the most successful and mature projects of the Apache software foundation.…”

Using Learning Analytics to Visualise Computer Science Teamwork

“…Sentiment analysis has primarily been used within the domains of business and social sciences and very limited research has investigated its use within education contexts. Some of the work that has been done in education has been to explore sentiment expressed by students in diaries [16]. The researchers extended sentiment analysis work to also extract and identify expressions that aligned with eight fundamental emotions of anger, trust, surprise, sadness, joy, fear, disgust and anticipation.…”

“…The evolution of emotions [16] is also extracted and visualized, both as an overall positive/negative sentiment graph and through the identification of individual, commonly expressed emotions. Figure 3 illustrates the visualisation of emotions Figure 4).…”