NaturalLanguageProcesing4All: - A Constructionist NLP tool for Scaffolding Students’ Exploration of Text
NaturalLanguageProcesing4All: - A Constructionist NLP tool for Scaffolding Students’ Exploration of Text
复制标题
NaturalLanguageProcesing4All： - 用于支撑学生探索文本的建构主义 NLP 工具
DOI：
--
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
A. Hjorth
中科院分区：
文献类型：
--
作者：
A. Hjorth
本文介绍了一个试点研究的自然语言处理4All（NLP 4All），一个构造主义，低门槛，XAI学习工具，旨在将自然语言处理方法带入高中课堂。具体来说，NLP 4All旨在让非程序员通过分类活动探索不同的文本语料库。我与一位高中社会研究老师一起开发了一个为期2周（6小时）的学习单元，重点分析政党的推文，探索他们的政策观点和沟通风格之间的差异和相似之处。在分析中，我发现文本分类显示出作为一种学习活动的未开发的承诺;学生能够利用他们的先验知识对推文进行分类;使用NLP 4All对推文进行协作分类导致了富有成效的课堂讨论;虽然学生们能够建立良好的机器学习模型来对推文进行分类，但他们的理论往往集中在识别一方，而不是区分各方。最后，我讨论了其他教育环境，其中NLP和ML可以为儿童提供生产力，以及未来可能值得探索的设计功能。
This paper presents a pilot study of NaturalLanguageProcessing4All (NLP4All), a Constructionist, low-threshold, XAI learning tool designed to bring Natural Language Processing methods into high school classrooms. Specifically, NLP4All is designed to let non-programmers explore different corpora of text through classification activities. Together with a high school Social Studies teacher, I developed a 2-week (6-hour) learning unit focusing on analyzing tweets from political parties to explore the differences and similarities between their policy views and communication styles. In the analysis, I find that text classification shows unexplored promise as a learning activity; that students were able to draw on their prior knowledge to classify tweets; that using NLP4All to collaboratively classify tweets led to productive classroom discussions; and that while students were able to build good machine learning models for classifying tweets, their rationales often focused on identifying one party, rather than distinguishing between parties. Finally, I discuss other educational contexts where NLP and ML can be productive for children, and future design features that may be worth exploring.