Research in Engineering Education Symposium 2011 - rees2009

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revolutions, and cognitive conflict will successfully lead students to the scientific theory or
understanding of a given phenomena.
How do people react to anomalous data?
Anomalous data is data that does not conform to a student’s present understanding of a
particular phenomenon (Chinn & Brewer, 1993). Educators often assume that presenting
a student with anomalous data will result in cognitive conflict that will lead him or her to
reject or modify their naïve understanding of a particular phenomenon in favour of an
understanding that is more closely aligned with accepted scientific explanations (Posner,
Brewer, Strike & Herzog, 1982). However, this is often not the case. An excellent example
is students attempting to transition from understanding the Earth as flat to understanding
that it is a sphere (Vosniadou, 2003): Students find it difficult to reconcile their classroom
instruction which states that the Earth is a sphere with their own experiences which
suggest that the Earth is flat. Instead of rejecting the flat earth model, they instead wind up
with a dual Earth model where there is one Earth that is a sphere and travels through the
solar system, and a different flat Earth that they actually live on. Understandings built on
personal experience do not change readily when students are exposed to anomalous data.
Chinn & Brewer (1993) developed a theoretical framework to explain the wide variety of
ways that students respond to anomalous data. They identified seven different
psychological responses that students may have regarding their naïve theory (call it
Theory A) in response to anomalous data that supports a scientific theory (Theory B).
Students may simply ignore the anomalous data, and forget about or ignore the data. They
may also reject the data, which is similar to ignoring the data except that they can provide
a reason for rejecting the data. These reasons could include assuming that there was a
methodological error in generating the data, believing that the anomalous data are a fluke
due to random variation in the data, or believing that the data are fraudulent. Students
may also exclude the data from the domain of Theory A, believing that their theory is not
supposed to explain the anomalous data. They may also hold the data in abeyance,
acknowledging its validity but believing that their theory will be able to explain the
anomalous data in the future. Students can also reinterpret the data so that it fits better
with Theory A. Finally, the students actually engage in conceptual change and make
peripheral changes to Theory A (weak conceptual change), or accept the data and change
Theory A, possibly so that it more closely resembles Theory B (strong conceptual change).
Students’ responses to anomalous data vary due to a variety of factors (Chinn & Brewer,
1993). Several characteristics of students’ prior knowledge have a strong effect on their
responses to anomalous data. This includes the entrenchment of their current
understanding based on the amount of experience they have with the phenomenon in
question. The students’ ontological beliefs about the fundamental categories and
properties of the world can be particularly difficult to change because they can support
understanding across domains. Their epistemological beliefs about what constitutes
knowledge and sound theories can also affect their responses to anomalous data. The
students’ background knowledge and familiarity with mathematical, scientific, or other
concepts related to the theory in question can also affect how they react to anomalous
Proceedings of Research in Engineering Education Symposium 2011
Madrid, 4 th - 7 th October 2011