Research in Engineering Education Symposium 2011 - rees2009

Universidad Politécnica de Madrid (UPM) Página 121 de 957
To address this issue, we observe and analyze the solutions of two experts, each with
expertise in a different domain, as they complete the project. Neither expert has direct
experience with the type of process upon which the Virtual CVD Project is based. One's
expertise aligns with an FPM approach and the other's with an SED approach. In this way,
our study is reductionist; we have selected individuals to intentionally investigate these
two possible solution approaches and compare the similarities and differences.
This work is part of a larger investigation which seeks to answer the following research
questions:
1. What characterizes the two different approaches (SED and FPM) these experts
take as they complete the Virtual CVD process development project? Which
components of their solutions are similar and which are different?
2. What approach leads to a higher quality solution? Are both methods suited for this
project, or is either method preferred? Why?
3. Based on these observations, what conjectures can we make about engineering
curriculum design, instruction, and feedback?
Expertise and Transfer
A clear goal of education is to help students move towards expertise. Following this goal,
many studies across a wide range of domains have sought to characterize expertise (Chi,
1989; Cross, 2004). It has been found that experts possess well connected and rich
knowledge structures regarding topics within their field of expertise. These knowledge
structures, often referred to as schemata, facilitate a rich understanding of the problem
and rapid recall of relevant “chunks” of information during the solution process
(Bransford, 2000). When studying solutions to engineering design projects, it has also
been found that experts tend to spend more time problem scoping than novices do (Atman
et al., 2007). However, once experts choose a solution concept, they often stick with the
concept throughout the solution process, whether it is good or bad (Ullman et al., 1988).
In the field of engineering where new technologies emerge daily, graduates need the
ability to apply familiar domain content in new situations. This application of core
knowledge to solve novel real world problems requires transfer. In order to understand
transfer in this context, a new branch of expert studies has emerged, and has been
classified by Hatano and Iganaki (1986) as ‘adaptive expertise.’ Adaptive expertise
contrasts with ‘routine expertise’ in that it is flexible and may be applied to increase
learning and performance in a wide range of new situations. Recently, efforts have been
reported in the engineering education literature discussing how to increase adaptive
expertise in students (McKenna et al., 2006) using pedagogies such as “challenge-based
instruction, brainstorming in groups to generate ideas, receiving input from multiple
experts in the field, and formative assessment integrated into powerful computer
simulations” (Pandy, 2004, p. 9).
Our expert study is informed by this literature. We hypothesize that the experts will both:
(i) execute their solution path in a sophisticated and effective manner, and (ii) rigidly
adhere to a path that aligns with their foundational domain knowledge. By contrasting the
Proceedings of Research in Engineering Education Symposium 2011
Madrid, 4 th - 7 th October 2011