Sentiment Analysis on Student Online Learning Experiences

Cheow, Yih Kit (2022) Sentiment Analysis on Student Online Learning Experiences. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

The online learning is introduced to education by the high improvement and implementation in web and technology. However, the pros and cons of online learning still remain unknown as there are various of statement to discuss the topic relevant to it. Therefore, it is important to find out whether online learning will affect the satisfaction of the student on the study experiences by obtaining the students feedback and opinions and determine the factors that can affect the satisfaction of the student on the online learning experiences. The best solution to solve this problem is performing the sentiment analysis that acts as an opinion mining technique with the usage of natural language programming, text analysis and emotion detection. As mentioning the text analysis, the confession page that contains in the social media is selected as the data collection channel by focusing on the English language texts. The text obtained is then used as sentiment process to find out the opinions of the students through the sentiment result and emotion classification. The research project will develop through the form of analysis and development part. The analysis part performs the process starting from data understanding until the construction of the model for sentiment analysis whereas the development part performs the sentiment analyser by getting the user interaction through the web application. In conclusion, this research aims to determine the student online learning experiences through sentiment analysis to provide useful information and reference to the educational institute.