In today's highly competitive market with economic, environmental, and social challenges, it is imperative that engineers are educated to adapt to the new challenges. Engineering education could play a critical role to improve engineering students' self-regulated and adaptive skills that are important for their future engineering productivity and innovation. To survive and thrive in the fast-changing workplace, today's students will need to become adaptive experts. However, current engineering education practices tend to focus too much on the low-level skills required to do specific and routine tasks rather than fostering self-regulated and adaptive skills required for innovation. Experts are defined in two distinctive characteristics: adaptive experts versus routine experts. Adaptive experts acquire the content knowledge parallel to routine experts in the field; in addition, they have the ability to effectively and innovatively utilize and extend that knowledge. In this dissertation, to determine the "baseline" adaptive expertise among the sample population, an adaptive expertise survey (AES) instrument is administered to both the practicing engineers and the students. The instrument contains questions defining four dimensions of adaptive expertise: multiple perspectives, metacognitive self-assessment, goals and beliefs, and epistemology. Participants' demographics and engineering experience were recorded and cross-tabulated with their adaptive expertise characteristics captured in the study. In addition this study explored engineering students' and practicing engineers' adaptive expertise (AE) characteristics as they used a CAD tool. The practicing engineers were asked to model a component in a CAD program that they were not familiar with. The students were asked to model a stylized familiar component that they brought from home. In both cases, pre and post interviews were conducted to explore how the participants approached their tasks and overcame any challenges. Effects of the contextualized activity on students' AE characteristics were investigated. In general, results indicated that as students gain more experience through years their overall AE characteristics were developed. In addition, the studies signified that multiple perspectives, goals and beliefs, and metacognitive skills are good indicators of developing AE and educators should consider promoting those skills in engineering education.
In today's highly competitive market with economic, environmental, and social challenges, it is imperative that engineers are educated to adapt to the new challenges. Engineering education could play a critical role to improve engineering students' self-regulated and adaptive skills that are important for their future engineering productivity and innovation. To survive and thrive in the fast-changing workplace, today's students will need to become adaptive experts. However, current engineering education practices tend to focus too much on the low-level skills required to do specific and routine tasks rather than fostering self-regulated and adaptive skills required for innovation.
Experts are defined in two distinctive characteristics: adaptive experts versus routine experts. Adaptive experts acquire the content knowledge parallel to routine experts in the field; in addition, they have the ability to effectively and innovatively utilize and extend that knowledge. In this dissertation, to determine the "baseline" adaptive expertise among the sample population, an adaptive expertise survey (AES) instrument is administered to both the practicing engineers and the students. The instrument contains questions defining four dimensions of adaptive expertise: multiple perspectives, metacognitive self-assessment, goals and beliefs, and epistemology. Participants' demographics and engineering experience were recorded and cross-tabulated with their adaptive expertise characteristics captured in the study. In addition this study explored engineering students' and practicing engineers' adaptive expertise (AE) characteristics as they used a CAD tool. The practicing engineers were asked to model a component in a CAD program that they were not familiar with. The students were asked to model a stylized familiar component that they brought from home.
In both cases, pre and post interviews were conducted to explore how the participants approached their tasks and overcame any challenges. Effects of the contextualized activity on students' AE characteristics were investigated. In general, results indicated that as students gain more experience through years their overall AE characteristics were developed. In addition, the studies signified that multiple perspectives, goals and beliefs, and metacognitive skills are good indicators of developing AE and educators should consider promoting those skills in engineering education.
