Abstract
Design as a process has mostly been studied from a qualitative perspective. This paper aims to contribute to a better quantitative and qualitative understanding of the design process. To do that, we introduce the Design Progress Dashboard (DPD) framework, a set of Natural Language Processing (NLP) assisted tools using the Word2Vec and t-SNE models to organically and quantifiably capture and visualise the design progress of a typical design class. We describe the methods used to gather data and perform analyses of student designers' mental thought processes through a periodic written assignment throughout the design class by converting text information into numerical data. Towards this end, we present a case study to dive into one of the design teams from the design class and propose a clear explanation on the usefulness of the research framework, its limitations and the potential future work.