Adaptive Expertise and its Manifestation in CAD Modeling: A Comparison of Practitioners and Students

Abstract

The state of Computer-Aided Design (CAD) education is often decried for focusing too much on the low-level skills required to do specific tasks; this often comes at the expense of promoting the strategic knowledge associated with expertise. The environment that today’s students will encounter in the workplace will require them to adapt to new challenges in innovative ways. Namely, they will need to become adaptive experts. To better inform CAD education, this work examines how practicing engineers adapt to a new environment and compares this behavior to that of students. To establish the “baseline” adaptive expertise among the sample population, an Adaptive Expertise Survey (AES) instrument was administered to both the practicing engineers and the college students. The practicing engineers in this work are asked to model a component in a CAD program that they are not familiar with. The students are asked to model either a stylized component or an artifact that they have brought from home and to which they have some attachment. In both cases, pre and post interviews inquire how the participants approach their tasks and overcome any challenges. Recordings of the interviews are transcribed and analyzed using open and axial coding. Selective coding is used to align responses with the dimensions of adaptive expertise. This coding provides the manifestation of adaptive expertise in the exercise. Statistical analyses are used to compare participants’ interview responses to their AES scores. Practitioners’ and students’ manifestations of adaptive expertise are compared. Manifestations of adaptive expertise are also compared to demographic data.