Application of Educational Context Data using Artificial Intelligence Methods

Myriam Peñafiel, Maria Vásquez, Diego Vásquez
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Abstract

Today the web generates a large amount of data, the same ones that come from social networks, online platforms, communities, cloud computing, etc., but one type of data has not been recognized for its relevance and that is data from Learning Management Systems like Moodle in the educational context. Considering this context, this research will apply some Artificial Intelligence methods and techniques such as the TSA methodology, Text mining, and Sentiment Analysis to assess the data about the opinion of the students, converting them into stable information structures that allow their reflection and analysis. The work carried out focuses on determining the level of user satisfaction, in this case, the students, of the virtual learning platforms. The results obtained show that applying Artificial Intelligence allows obtaining relevant information that helps to undertake improvement actions by authorities and managers in the educational context based on the opinion of the students, detecting important problems in online learning during these times of COVID-19 we are just past.
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基于人工智能方法的教育情境数据应用
今天,网络产生了大量的数据,这些数据同样来自社交网络、在线平台、社区、云计算等,但有一种数据的相关性还没有得到认可,那就是来自Moodle等学习管理系统在教育环境中的数据。考虑到这一背景,本研究将应用一些人工智能方法和技术,如TSA方法、文本挖掘和情感分析来评估学生的意见数据,并将其转换为稳定的信息结构,以便他们进行反思和分析。所开展的工作侧重于确定用户满意度的水平,在这种情况下,学生,虚拟学习平台。所获得的结果表明,应用人工智能可以获得相关信息,有助于当局和管理人员在教育背景下根据学生的意见采取改进行动,在我们刚刚过去的COVID-19时期发现在线学习中的重要问题。
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