Harnani Mat Zin, N. Mustapha, M. A. Azmi Murad, Nurfadhlina Mohd Sharef
{"title":"Towards a Framework on Sentiment Analysis of Educational Domain for Improving the Teaching and Learning Services","authors":"Harnani Mat Zin, N. Mustapha, M. A. Azmi Murad, Nurfadhlina Mohd Sharef","doi":"10.37134/jictie.vol4.1.2017","DOIUrl":null,"url":null,"abstract":"Analyzing students’ feedback and their expressed emotions toward any subjects could help lecturers to understand their students’ learning behaviour. Several platforms are used by students to express their feelings such as through social networking sites, blogs, discussion forums and the university survey systems. However, the feedbacks typically contain thousands of sentences and are from various sources which makes analyzing them a cumbersome and tedious work. In this regard, sentiment analysis (SA) has been proposed to automate the process of mining user feedback into valuable information. This paper discusses the principles of SA, its potential benefits, and its application in the educational field based on the synthesis of previous studies. We suggest that SA can help lecturers to easily understand the needs and problems of their students. In particular, a framework and a performance evaluation method were proposed to help guide the implementation of the SA in the education domain.","PeriodicalId":301836,"journal":{"name":"Journal of ICT In Education","volume":"202 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of ICT In Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37134/jictie.vol4.1.2017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Analyzing students’ feedback and their expressed emotions toward any subjects could help lecturers to understand their students’ learning behaviour. Several platforms are used by students to express their feelings such as through social networking sites, blogs, discussion forums and the university survey systems. However, the feedbacks typically contain thousands of sentences and are from various sources which makes analyzing them a cumbersome and tedious work. In this regard, sentiment analysis (SA) has been proposed to automate the process of mining user feedback into valuable information. This paper discusses the principles of SA, its potential benefits, and its application in the educational field based on the synthesis of previous studies. We suggest that SA can help lecturers to easily understand the needs and problems of their students. In particular, a framework and a performance evaluation method were proposed to help guide the implementation of the SA in the education domain.