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Educational Psychology—Limitations and Possibilities

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PICTURE THIS<br />

Figure 105.1<br />

Dualisms of Cartesian–Newtonian–Baconian epistemology<br />

Dualisms of Cartesian-Newtonian-Baconian Epistemology<br />

Constants<br />

Space & Time<br />

Cause & Effect<br />

Separations<br />

Mind Matter<br />

Knower Known<br />

<strong>Educational</strong> Psychology on the Move 917<br />

The language of metaphor is often useful in describing paradigmatic change, <strong>and</strong> ordinarily I<br />

would use a metaphor to describe the difference between a CNB epistemology <strong>and</strong> a post-CNB<br />

model. None is forthcoming, however. Remembering the pedagogical lessons of my youth, when<br />

words won’t work, I turn to pictures. I sketch several representations of a CNB epistemology<br />

of ed psych, the first (Figure 105.1) showing Sir Isaac Newton’s constant dualisms of space <strong>and</strong><br />

time, <strong>and</strong> cause <strong>and</strong> effect, <strong>and</strong> Réné Descartes’ separate dualisms of mind <strong>and</strong> matter, knower<br />

<strong>and</strong> known. The constant dualism of space <strong>and</strong> time represents the assignment of universality<br />

to many of the findings of traditional ed psych; if it’s true here <strong>and</strong> now, it’s true everywhere<br />

<strong>and</strong> always. Context doesn’t matter. The results of Piaget’s study of a small group of boys in a<br />

Swiss school, for example, were universalized to apply to all children, everywhere. All learning<br />

is assumed to fit within the hierarchical confines of Bloom’s taxonomy. The Cartesian constant<br />

dualism of cause <strong>and</strong> effect refers to the attribution of causality, that a particular cause will always<br />

have the same effect. Again, context is not a consideration in this paradigm, nor is interpretation.<br />

This dualism has as its most prominent example the “mind as computer” model. Human minds<br />

are conceptualized as computers that always work in a predictable way; the same input always<br />

results in the same output, without fail (Bruner, 1996). Predictability is an important requirement<br />

of research findings, because predictability makes possible the assignment of universality. Neither<br />

intuition nor imagination is acknowledged because each introduces too great a variable into the

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