Motivation, Emotion, and Cognition : Integrative Perspectives On Intellectual Functioning and Development

(Rick Simeone) #1

(Speelman, 1998). It is not trivial to note that Kasparov characterized his
match with Deep Junior as “intuition versus the brute force of calculation”
(Sieberg, 2003, p. 1).^2


Integration of Neurobiological, Psychological-Behavioral
(Functional), and Phenomenological Levels of Analysis:
Emergentism, Reductionism, and Interactionism


As discussed earlier, integrative efforts can be seen as operating with three
distinct epistemological stances or levels of analysis: neurobiological, psycho-
logical-behavioral, and phenomenological. Unifying these approaches would
mean forging a marriage between the sciences of the biological and “the sci-
ences of the subjective” (Bruner, 1996, p. 12), with the sciences of func-
tional behavior in-between. No wonder why some would question whether
such a marriage is a possible, or even desirable, one (Kendler, 1987; Shweder,
2001). However, the dream of putting it all together, of forging the unity or
consilience of the natural and human sciences, is very much alive and well
(e.g., Damasio et al., 2001). According to Sternberg and Grigorenko (2001), a
unified psychology is possible if we (a) focus on psychological phenomena
rather than compartmentalizing psychology into isolated components, and
(b) use convergent operations rather than insulated single research para-
digms. Dweck’s (1999; Dweck et al., chap. 2) work provides a good example.
Dweck’s theory (1999) has a distinct interpretive component: people’s im-
plicit theories of intelligence, which belongs in the sciences of the subjective.
However, her theory is also grounded in empirical work searching for causal
patterns of motivation, emotion, cognition, and observable behaviors, a be-
havioral-functional level integration. Also, the social-cognitive approach she
adopts does not prevent her from exploring measurable physiological differ-
ences of individuals with different goal orientations in addition to behavioral
analyses (see Dweck et al., chap. 2). Thus, the use of multimethods and con-
vergent operations, and the flexible shift of epistemological stances (from a
more or less positivist stance to an interpretive stance) have enhanced our un-
derstanding of the phenomenon in question.


424 DAI


2 2 Of course, whether human expert intuition is the result of computation at the unconscious
level, analogous to that of artificial neural networks (ANNs), is an empirical question. Our
hunch is that the human capability of pattern recognition and analogical mental modeling en-
ables such a quick insight without going through the lengthy, inefficient, rule-based iteration of a
computer program such as Deep Blue (see Klein, 1998). It is possible that more embodied cogni-
tive modeling such as dynamic systems approaches (Port & Gelder, 1995) may better approxi-
mate the underlying mechanisms of human intuition and perception. On the other hand, one
should also be open to the possibility that some mental processes and events are fundamentally
noncomputational (see Edelman, 1989).

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