Examining Adaptive Expertise: A Novel Comparison of Student and Practicing Engineer CAD Modeling Performance Conference Paper uri icon

abstract

  • Copyright © 2015 by ASME. Computer-aided design (CAD) tools are critical in the current fast-paced digital product commercialization environment. As firms move towards a model based enterprise, it becomes more important for engineers to develop the skills necessary to efficiently and effectively model components in CAD. The status of CAD education and training has often been decried as focusing too much on declarative knowledge, namely how to do specific procedures in a specific software program. This is opposed to the strategic knowledge or expertise that is adaptable to other CAD programs. To better inform CAD education and modeling procedures, an understanding of how experts model and model in novel situations is presented. Specifically, and novel to this work, the adaptive nature of these practicing professional's CAD expertise is examined and compared to that of relatively novice students. The methods comprise a combination of screen capture data, model attributes, and the results of interviews to assess adaptive expertise. Practicing engineers are found to spend a smaller percentage of their modeling time engaged in actual modeling procedures (doing time). Significant differences related to model attributes include: practicing engineers being less likely to use pattern features, more likely to have incorrect feature terminations, and more likely to use more complex features (as measured by feature density). Results show practicing engineers as less likely to highlight strategies related to adaptive expertise prior to the modeling activity. Post interview results show practicing engineers with more manifestations of adaptive expertise. These results are in agreement with previous literature examining both general and CAD modeling expertise.

author list (cited authors)

  • Johnson, M. D., Ozturk, E., Yalvac, B., Valverde, L., Peng, X., & Liu, K. e.

citation count

  • 0

publication date

  • November 2015