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Tacit Knowing - WoodCraft
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Reflection on (Externalized) Action
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Reflection on (Externalized) Action
How can we trace tacit knowledge in woodcraft? Unlike technical expertise, tacit knowledge cannot be easily communicated or registered. But is is a key element in craft practices, such as woodworking. This project aims to detect varying performances through material-based sensing, look for possible patterns, and apply them in an instructional interface.
Tacit knowledge is the kind of knowledge that one gains through embodied processes. This knowledge is produced through embodied doing as one encounters materials, tools, objects. “Tacit knowing is the way in which we are aware of neural processes in terms of perceived objects,” argues Polanyi. Unlike explicit and external knowledge, it cannot be easily abstracted or communicated because it is rooted in this embodied relation. Tacit knowledge remains central to design since Schön established in the 80s: “Design knowledge is knowing-in-action, revealed in and by actual designing. It is mainly tacit.”
In material practices, such as crafting or tangible interaction, tacit knowledge has always been important as these practices unfold only in the encounter of practitioner, tool, and material. The challenge is, that this kind of knowledge is not easy to detect and teach.
How can we detect different levels of tacit knowledge and use these data for tangible media aimed at craft instruction?
The project combines three overlapping concepts: 1) a material turn to practice, 2) emphasize the constitutional role of tools, and 3) focus on relationality across data. It connects to existing debates on more-than-human design in HCI and adds a practical sensing technique that emphasizes the relations, agencies, and activities between partners over a distinction of individual actors.
This project first aims to detect differences between woodworking experts and amateurs with the help of a sensor set up that follows more-than-human design. It combines hybrid craft and material-based design to build sensors and interfaces. In order to focus on a specific practice, it limits itself to an intuitive but highly specialized craft practice: using a wood plane.
Four basic design criteria informed the necessary sensing set up: • Sense the material: detect data from the material at hand (examples: heat, movement, form or color changes) • Sense the body: detect data from the human body and how it changes during the encounter (examples: muscle activation, posture, gestures) • Sense the tool: detect tool performance (examples: speed, direction, alterations) • Keep data relational: support data comparison across all participants (examples: use a shared timeline, reliable sensing speed, frequency, and data transmission)
Based on the gathered data, we aim to design and implement a teaching tool for woodworking that informs amateurs about possible corrections during the embodied practices itself.
Tacit knowledge has received increasing interest in craft and hybrid craft research. Practitioners and researchers have traditionally used photos, videos and journals to document the tacit and experiential knowledge at work in the craft process. Such documentation enables the recording and surfacing of the embodied sensory experience to the conscious level, so practitioners could conduct reflection-in-action or reflection-on-action activities. We have conducted some related work on this for pottery [link]. Adding to these approaches, we target a more sensor-based approach for woodworking. Sensing technologies, including computer vision and affordable sensors in tangible design, can trace tacit knowledge through varying performances in a more quantifiable. They can capture details and nuances that are not necessarily visual/visible in a video or image.
To examine the effect of the EMG visualization, we generated the following hypotheses:
Hypothesis 1: The EMG data will lead to a perception change: potters are going to shift more of their attention from objects to actions.
Hypothesis 2: The EMG visualization will emphasize embodiment and lead to more reflections covering qualitative aspects of the action.
Hypothesis 3: The EMG visualization will promote more engaging reflection experience.
In sum, it indicated that the added visualization of participants’ EMG data affected the reflections. The EMG visualization appeared to be useful in promoting more reflections on the actions (Hypothesis 1) and the quality of the actions (Hypothesis 2). The provision of the EMG data also promoted more activities such as feeling and thinking that were beyond the throwing itself, as indicated by the participants, in the reflection sessions, which suggests that participants were more engaged in the reflection (Hypothesis 3).
Yilin Elaine Liu
Ph.D. student in Industrial Design, M.S. student in HCI - Digital Media
Michael Nitsche
Professor in Digital Media
Jialuo Yang
M.S. in Digital Media
