Works for Me: Personalizing Skilled Trade Worker Training via Smart Hand Tools

ABSTRACT This paper explores an approach for applying Artificial Intelligence (AI) to co‐design smart hand tools to personalize learning for future skilled trade workers in workforce training programs. The purpose of this research is to better understand the perspectives of workers in the skilled trades and to respond with co‐designed socio‐technical interventions that empower workers. The research benefits from a collaboration between The University of Texas at Austin, the City of Austin, and Austin Community College (ACC) and incorporates insights from welding instructors and students, as well as skilled trade workers and supervisors. Social science findings derived from semi‐structured interviews inform tool design implemented by an interdisciplinary research team. The participatory design approach has resulted in two prototypes: a welding simulator that uses Augmented Reality (AR) and an AI‐enabled (smart) rotary tool. This paper has implications for workforce development to address skilled worker shortages. Additionally, it contributes to ongoing research into AI and skilled trade work which is understudied compared to AI and knowledge work.

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Publication Details

Journal
Proceedings of the Association for Information Science and Technology
Published
2024-10-01
DOI
https://doi.org/10.1002/pra2.1011
Citations
2
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.82

Funders

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article

Works for Me: Personalizing Skilled Trade Worker Training via Smart Hand Tools

Sherri R. Greenberg, Tina Lassiter, Rachel New, Chelsea Collier et al.
2 citations
Proceedings of the Association for Information Science and Technology
Online Learning and Analytics
0.82
article

Works for Me: Personalizing Skilled Trade Worker Training via Smart Hand Tools

Sherri R. Greenberg, Tina Lassiter, Rachel New, Chelsea Collier, Kenneth R. Fleischmann, Raul G. Longoria, Carlos Salazar, J. Kim
article en
2 citations

Abstract

ABSTRACT This paper explores an approach for applying Artificial Intelligence (AI) to co‐design smart hand tools to personalize learning for future skilled trade workers in workforce training programs. The purpose of this research is to better understand the perspectives of workers in the skilled trades and to respond with co‐designed socio‐technical interventions that empower workers. The research benefits from a collaboration between The University of Texas at Austin, the City of Austin, and Austin Community College (ACC) and incorporates insights from welding instructors and students, as well as skilled trade workers and supervisors. Social science findings derived from semi‐structured interviews inform tool design implemented by an interdisciplinary research team. The participatory design approach has resulted in two prototypes: a welding simulator that uses Augmented Reality (AR) and an AI‐enabled (smart) rotary tool. This paper has implications for workforce development to address skilled worker shortages. Additionally, it contributes to ongoing research into AI and skilled trade work which is understudied compared to AI and knowledge work.

Proceedings of the Association for Information Science and TechnologyVol. 61(1)
Walker (United States) (US), The University of Texas at Austin (US)
University of Texas at Austin
Openalex Percentile: Top 18%
Online Learning and Analytics
0.82
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