Design has always been seen as an inherently human activity and hard to automate. It requires a lot of traits that are seldom attributable to machines or algorithms. Consequently, the act of designing is also hard to assess. In particular in an educational context, the assessment of progress of design tasks performed by individuals or teams is difficult, and often only the outcome of the task is assessed or graded. There is a need to better understand, and potentially quantify, design progress. Natural Language Processing (NLP) is one way of doing so. With the advancement in NLP research, some of its models are adopted into the field of design to quantify a design class performance. To quantify and visualize design progress, the NLP models are often deployed to analyze written documentation collected from the class participants at fixed time intervals through the span of a course. This paper will explore several ways of using NLP in assessing design progress, analyze its advantages and shortcomings, and present a case study to demonstrate its application. The paper concludes with some guidelines and recommendations for future development.

中文翻译：

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使用 NLP 可视化设计项目团队和个人进度：潜在语义分析与 Word2Vector 算法之间的比较

设计一直被视为一种天生的人类活动，很难自动化。它需要很多很少归因于机器或算法的特征。因此，设计行为也很难评估。特别是在教育背景下，很难评估个人或团队执行的设计任务的进度，并且通常只对任务的结果进行评估或评分。需要更好地理解并可能量化设计进度。自然语言处理 (NLP) 是这样做的一种方式。随着 NLP 研究的进步，它的一些模型被用于设计领域，以量化设计类的性能。为了量化和可视化设计进度，NLP 模型通常用于分析在课程跨度内以固定时间间隔从班级参与者收集的书面文档。本文将探讨使用 NLP 评估设计进度的几种方法，分析其优缺点，并提供案例研究来展示其应用。本文最后为未来的发展提出了一些指导方针和建议。