WIP: Making Implicit Knowledge Explicit - A Data-Driven Approach to Improve Knowledge Transfer in a Glassblowing Beginners Class

This work-in-progress innovative practice paper presents a novel approach to 1) extract tacit knowledge from expert trainers while they perform a task demo, 2) decrease the learner's cognitive load via the use of instructional videos portraying the variables at play during a task demonstration, and 3) define quantifiable metrics of expertise by extracting features that differentiate experts from novice practitioners. Implicit or tacit knowledge is know-how that experts develop with experience and is difficult to verbalize, formalize or explicitly transfer to others. For this reason, knowledge transfer from expert to apprentice is usually slow and inefficient. Our approach seeks to support knowledge transfer using technology-enhanced approaches. Here, we focus on extracting and describing exper-tise. We do so by instrumenting experts, trainees and their tools with sensors that can help structure and formalize knowledge. Our first application of this framework is on the knowledge transfer between an expert and novice glassblower. Glassblowing is well known for its crucial expert/apprentice relation and its slow learning rate due in part to the difficulties in verbal transfer of skills. Our framework seeks to capture relevant data while an expert glassblower demonstrates basic actions in a beginners glass blowing course. Our sensors collect eye-tracking activity, verbal demo instructions, pipe accelerometry, air infusion, scene video and muscle activity (EMG), which continuously monitor the expert, their explanations, the tools, and the glass piece. We bring together all the sensed data into instructional videos to be used by novice learners as supportive training material. We present preliminary results related to metrics of expertise and future steps towards gathering similar data from novices. This will help develop AI-based models to extract data-driven differences between experts and apprentices, which can be used as further instructional material. We will also present plans to test the instructional effectiveness of the developed videos and how our approach can be used in other training settings involving tacit knowledge transfer.