Research in Engineering Education Symposium 2011 - rees2009

Universidad Politécnica de Madrid (UPM) Página 492 de 957
Networks of p-prims
diSessa & Sherin (1998) propose a very different model of conceptual change. They
propose the phenomenological primitive (p-prim) as the fundamental building block of
knowledge. Students construct p-prims from their basic experiences and observations of
the world. These p-prims are organized by conceptual networks where students establish
loose connections between the p-prims. Through experiences that cultivate appropriate pprims
and build connections, students can move towards understanding phenomena in a
more scientific manner.
Each of these models represent slightly different understandings of concepts, with
different degrees of relevancy to K-12 engineering that will be explored later in this paper.
How stable are the conceptual understandings?
A critical difference between theories of conceptual change is their assumptions about the
coherence and stability of students’ understanding. As mentioned earlier, Vosniadou
(2003) believes that students’ conceptions are theory-like, relatively coherent, and change
fairly slowly over time. Although not explicitly addressed, schema and script theory
suggest relatively stable understanding built from experiences as well.
diSessa (2008) makes a strong argument against both coherence and stability in
understanding. He primarily argues against parsimony, in other words trying to
oversimplify or ignore pieces of data in the name of creating an elegant theory. Assuming
stability results in losing complexity and depth and nuance of understanding. When
assuming a stable model, especially that multiple students share the same incorrect stable
model, one loses awareness of how individuals construct understanding of a given
phenomenon, and what concepts the individual learner may be struggling with. Assuming
a stable model may also suggest that student models have the same level of validity as
normative scientific models, that they are well reasoned in their development and
generative when applied to new situations. This needs to be counterbalanced with a
respect for students’ models and ideas. diSessa also argues that there is no way to measure
stability or coherence of a student’s model, so when researchers describe this they are in
fact imposing their own views or biases towards their own theories of conceptual change
on the student. Assuming that students possess a stable, incorrect understanding that
needs to be replaced with a normative, scientific understanding may make it more difficult
to discover and work with the student’s fundamental pieces of knowledge or p-prims.
Rather than trying to restructure a stable theory through revolutionary or evolutionary
conceptual change, instruction should focus on developing the p-prims necessary to build
the scientific model and the meta-cognitive awareness to appreciate and verify the validity
of the scientific model. Assuming a stable, individual model ignores the social aspect of
knowledge and understanding, and presumes an individual independent of both social and
experiential context. Finally, assuming than an individual’s theories are stable and
“science-like” in their nature may also incorrectly lead to the assumption that these
theories change in manner consistent with Kuhn’s (1996) description of scientific
Proceedings of Research in Engineering Education Symposium 2011
Madrid, 4 th - 7 th October 2011