基于大数据分析方法的教育计划研究——基于聊天GPT的学习任务数据反馈研究

Bo-ho Seo
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引用次数: 0

摘要

本研究探讨透过学习任务数据的分析与可视化,探索与实化可应用于实际课堂的教学方法。在教育中,大数据分析技术已经被用于分析课堂外的环境,本研究找到了一种将该方法应用于线下课堂的方法。特别是,如果通过主题建模、情感分析、网络分析等方法对学习者的作业进行处理,然后将其可视化并给予反馈,将有助于课堂的互动性。此外,本研究的重点是收集和预处理学习者的作业数据,以便这些知识可以在与计算机科学无关的课堂环境中使用。这是基于大数据分析方法的普及和Chat GPT等人工智能技术的发展。通过这种方式,教师可以在课堂环境中轻松地使用计算机科学技术。本研究以学习任务数据的分析与可视化为具体实例。如果使用这种讨论,即使在数据分析不普遍化的教育环境中,教师也可以以更自动化的方式处理和处理学习数据。这是打开计算机科学和其他学科之间融合可能性的一个例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on Education Plans Using Big Data Analysis Methods: Focusing on the Feedback of Learning Task Data Using Chat GPT
This study discusses exploring and materializing educational methods that can be used in actual classes with the analysis and visualization of learning task data. In education, big data analysis technology has been used for analyzing the environment outside class, and this study finds a way to utilize this method in an offline classroom. In particular, it was expected that if learners' assignments were processed through topic modeling, sentiment analysis, and network analysis methods and then visualized and given feedback, it would be helpful for interactive classes. In addition, this study focuses on collecting and pre-processing the learner's assignment data so this knowledge can be utilized in a class environment unrelated to computer science. This is based on the spread of big data analysis methods and the development of artificial intelligence technologies such as Chat GPT. Through this, instructors can use computer science technology easily in their class environment. This study presents the analysis and visualization of learning task data as a specific example. If this discussion is used, it will be possible for instructors to process and process learning data in a more automated way, even in educational environments where data analysis is not generalized. This is an example of opening the possibility of convergence between computer science and other disciplines.
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