Litcius/Paper detail

Augmenting Embodied Learning in Welding Training: The Co-Design of an XR- and tinyML-Enabled Welding System for Creative Arts and Manufacturing Training

Zhenfang Chen, Tate Johnson, Andrew Knowles, Ann Li, Semina Yi, Yumeng Zhuang, Daragh Byrne, Dina El-Zanfaly

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Abstract

Metal welding is a craft manufacturing skill that can be unusually difficult to externalize and represent to novices. Building competency requires an apprentice to iteratively practice embodied skills and sensitize themselves to a sensorially complex practice. To explore these challenges, we organized a series of co-design workshops with a youth program in welding and fabrication. Working with eight instructors and four students, we identified opportunities for mixed reality, sensing, and tinyML processes to augment welding training and practice. This resulted in an extended reality (XR) welding helmet and torch that enhances the embodied learning of welding in three key ways: biometric sensing enhances mindfulness and stress management in sensorially challenging environments; acoustic sensing focuses learner attention on non-visual cues of weld performance; and combined motion-sensing and visual XR feedback helps improve proprioceptive and embodied learning. These features are assessed and we offer design implications for augmenting novice learning of craft-practice with XR approaches.

Topics & Concepts

Embodied cognitionWeldingHuman–computer interactionComputer scienceCraftArtificial intelligenceEngineeringMechanical engineeringVisual artsArtVirtual Reality Applications and ImpactsInnovative Human-Technology InteractionCreativity in Education and Neuroscience