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upon the type of knowledge they thought would be possible and useful. So for exam-
ple, common approaches based on idiographic assumptions (about the uniqueness
of individuals) and informed by phenomenology and ethnography found a diver-
sity of student ideas, whereas approaches that were informed by more normative
assumptions tended to characterise responses into modest typologies (Taber, 2007,
pp. 47-51). However, research in any field tends to have an iterative nature, so
that even if different camps begin with very different assumptions about a phe-
nomenon and plan their initial enquiries accordingly, over time we might expect a
gradual convergence as researchers take on board the “feedback” provided by their
data.
This did not happen in science education, suggesting that here the phenomenon
was complex and multifaceted, allowing different researchers to find evidence to
support very different characterisations of student thinking about science (Taber,
2009, pp. 226-256). So science teachers work with students who come to class with
ideas which are at variance with the target knowledge in the curriculum to differ-
ent degrees: and which may sometimes be labile, but sometimes inert; sometimes
fragmentary and sometimes coherent; sometimes similar to those of many other stu-
dents, but sometimes idiosyncratic; sometimes a useful intermediate conception that
can lead to target knowledge; and sometimes a substantial impediment to the desired
learning. This makes life more interesting for researchers and teachers, but clearly
such a complex picture is not helpful in informing pedagogy.
Without understanding the origins of this variety found within learners' ideas
about science, there is no reason not to suspect that much the same pattern (or per-
haps lack of apparent pattern) could be found when students are taught new concepts
in other academic areas such as history, economics, literary criticism or theory of
music.
This fascinating but challenging variety in the apparent nature of conceptions stu-
dents bring to class confuses attempts to use research into learners' ideas to inform
teaching—which is after all a key rationale for educational research. Advising teach-
ers how to respond to students' ideas depends upon being able to systematise the
research findings, so as to start to know how and when learners' ideas have cer-
tain characteristics, and so when it might be best to ignore, mould or discredit their
ideas.
Whereas eliciting and characterising students' ideas can be undertaken from
“within” education, the programme to build a systematic and inclusive model from
the disparate research findings needs to draw upon ideas from the cognitive sciences.
In particular, science educators (and their colleagues exploring teaching and learn-
ing in other subject disciplines) need to understand better the nature of the objects of
research (learners' ideas), and especially the origins and development of students'
thinking. This is not a new idea. Researchers in the field have for example recom-
mended drawing upon information processing models, either instead of focussing on
students' ideas (Johnstone, 1991), or as a means for understanding their origins and
development (Osborne & Wittrock, 1983). Despite this, much research has reported
findings in what are largely phenomenological terms, without seeking to interpret
what is reported in terms of a cognitive science framework.
