Abstract
Designers use various design methods and tools to understand user needs, identify using process and context, and set a design direction in the design process. Generally, Human-Centered Design (HCD) process requires the process of classifying and interpreting a vast amount of raw user data into meaningful information. Designers frequently use affinity diagrams to transform the data into meaningful information. However, it is difficult to get rational insights only within the affinity diagram, since it is challenging to synthetically analyze the derived keywords. This paper presents a new method of analyzing user data called ‘dimensional themes’ matrix’. The matrix enables designers to understand the design problem structure by positioning user data on the intersections of two keyword dimensions. It provides rationales to insights by enhancing the connectivity of the keyword themes, which is difficult to capture with the original affinity diagram.
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The work was supported by the UNIST funded product development project (1.190110.01).
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Lee, D., Joo, S., Park, S., Kim, H., Kim, K. (2020). A Dimensional Themes’ Matrix for Identifying Design Problem Structure. In: Di Bucchianico, G., Shin, C., Shim, S., Fukuda, S., Montagna, G., Carvalho, C. (eds) Advances in Industrial Design. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1202. Springer, Cham. https://doi.org/10.1007/978-3-030-51194-4_50
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DOI: https://doi.org/10.1007/978-3-030-51194-4_50
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