Temporal analytics with discourse analysis: tracing ideas and impact on communal discourse

Proceedings of the Seventh International Learning Analytics & Knowledge Conference Pub Date : 2017-03-13 DOI:10.1145/3027385.3027386

Vwen Yen Lee, S. Tan

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引用次数: 15

Abstract

This paper presents a study of temporal analytics and discourse analysis of an online discussion, through investigation of a group of 13 in-service teachers and 2 instructors. A discussion forum consisting of 281 posts on an online collaborative learning environment was investigated. A text-mining tool was used to discover keywords from the discourse, and through social network analysis based on these keywords, a significant presence of relevant and promising ideas within discourse was revealed. However, uncovering the key ideas alone is insufficient to clearly explain students' level of understanding regarding the discussed topics. A more thorough analysis was thus performed by using temporal analytics with step-wise discourse analysis to trace the ideas and determine their impact on communal discourse. The results indicated that most ideas within the discourse could be traced to the origin of a set of improvable ideas, which impacted and also increased the community's level of interest in sharing and discussing ideas through discourse.

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话语分析的时间分析:对公共话语的思想追踪及其影响

本文通过对13名在职教师和2名讲师的调查，对在线讨论的时间分析和话语分析进行了研究。在一个在线协作学习环境中，一个由281个帖子组成的论坛被调查。使用文本挖掘工具从话语中发现关键词，并通过基于这些关键词的社会网络分析，揭示了话语中存在的大量相关和有希望的想法。然而，仅仅揭示关键思想不足以清楚地解释学生对所讨论主题的理解程度。因此，通过使用时间分析和逐步话语分析来追踪这些想法并确定它们对公共话语的影响，进行了更彻底的分析。结果表明，话语中的大多数想法都可以追溯到一组可改进的想法的起源，这影响并增加了社区通过话语分享和讨论想法的兴趣水平。

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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Proceedings of the Seventh International Learning Analytics & Knowledge Conference

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