Research in Engineering Education Symposium 2011 - rees2009

Universidad Politécnica de Madrid (UPM) Página 88 de 957
Theoretical Framework
We frame our study using the adaptive expertise model. According to Schwartz, Bransford,
and Sears (2005), an adaptive expert is someone who not only has deep subject matter
knowledge, but also can recognize when this knowledge applies in a novel setting. Our
study analyzes adaptive expertise as it applies to how one flexibly uses knowledge of
modeling. Modeling know-how falls under the banner of “computational adaptive
expertise” or CADEX, which concentrates on the development of analytical and
computational knowledge (McKenna, Linsenmeier, & Glucksberg, 2008). Many
engineering courses teach these topics without explicitly acknowledging how analytical
techniques serve as representations of a physical phenomenon. This approach omits an
important step in the development of a robust fluency.
Modeling Literature Review
Given the pervasiveness of modeling in engineering, our current paper explores students’
conceptions connected to the use of modeling. The teaching and learning of modeling is
easily complicated by semantics in that the term “model” can be a noun, verb, or adjective.
Maki & Thompson (2006) note that the term modeling has different meanings depending
on the context. In everyday use, modeling references a display version or miniaturization
of something. This use of the term corresponds in engineering to physical models intended
for experimentation, display, and emulation purposes. Engineers also use the term model
to describe theoretical, logical, and mathematical representations which represent
behaviors (Starfield et al., 1994). The everyday use of the term is often not consistent with
the nuanced technical meaning.
A goal for teaching modeling is therefore to guide students in the discovery of the intended
uses, appropriate applications, and embedded assumptions of models. Modeling in
engineering is a process not just a product. As Lesh & Doerr (2003) describe, modeling is a
cyclic activity consisting of real world descriptions, prediction manipulation, and
verification. Modeling as a process provides students with an understanding of how to
create purposeful and meaningful representations.
Perkins (1986) cautions that the term model does not include everything. Models are
intrinsically ambiguous, and often additional information is necessary to make sense of
any model. Models are typically taught using the general method of highlighting features
with words or labels. This can lead to a compound effect of using one type of model (e.g.
words and symbols) to explicate or highlight aspects of another model (e.g. sketches and
diagrams). As educators we take for granted that students understand that we are
teaching different types of modeling that are appropriate for different types of analysis
and decision-making. The explicit reasons for modeling fade in the background such that
they become invisible causing students to often lose sight of or not even notice that they
are engaging in the process of modeling, and for what purpose.
In engineering education, research on embedded modeling interventions has come by way
of modeleliciting activities (MEAs) (Deifes-Dux, Moore, Zawojewski, Imbrie, & Follman,
Proceedings of Research in Engineering Education Symposium 2011
Madrid, 4 th - 7 th October 2011