Opinion Mining for Modeling User Experience of Online Education: Sentiment Analysis and Keywords Extraction of Student Reviews

A. Moskvina, M. Kirina, Anastasia Gavrilyuk
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引用次数: 0

Abstract

The paper discusses the possibilities of applying modern natural language processing technologies of opinion mining to investigate and improve the user experience of online-courses students. We analyzed 27 000 student reviews of projects within the Python programming language course. First, we applied keyword extraction algorithms as a way of semantic compression to receive a generalized picture of what users' main impressions are. Then we performed sentiment analysis to understand the feelings of students towards the learning process. The used methodology proved to be effective for analyzing user experience and allowed to find out some discrepancies between information in project descriptions and what users' reflection on the project. Two instruments of SA were applied to receive data on users' feelings in general.
面向在线教育用户体验建模的意见挖掘:学生评论的情感分析与关键词提取
本文探讨了应用现代自然语言处理技术的意见挖掘来调查和改善在线课程学生的用户体验的可能性。我们分析了27000名学生对Python编程语言课程项目的评论。首先,我们应用关键字提取算法作为语义压缩的一种方式,以获得用户主要印象的广义图像。然后我们进行情绪分析,了解学生对学习过程的感受。所使用的方法被证明是有效的分析用户体验,并允许发现项目描述信息与用户对项目的反映之间的一些差异。使用两种SA工具来接收用户总体感受的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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