Ml. Commons et al., HIERARCHICAL COMPLEXITY OF TASKS SHOWS THE EXISTENCE OF DEVELOPMENTALSTAGES, Developmental review (Print), 18(3), 1998, pp. 237-278
The major purpose of this paper is to introduce the notion of the orde
r of hierarchical complexity of tasks. Order of hierarchical complexit
y is a way of conceptualizing information in terms of the power requir
ed to complete a task or solve a problem. It is orthogonal to the noti
on of information coded as bits in traditional information theory. Bec
ause every task (whether experimental or everyday) that individuals en
gage in has an order of hierarchical complexity associated with it, th
is notion of hierarchical complexity has broad implications both withi
n developmental psychology and beyond it in such fields as information
science. Within developmental psychology, traditional stage theory ha
s been criticized for not showing that stages exist as anything more t
han ad hoc descriptions of sequential changes in human behavior (Kohlb
erg & Armon, 1984; Gibbs, 1977, 1979; Broughton, 1984). To address thi
s issue, Commons and Richards (1984a,b) argued that a successful devel
opmental theory should address two conceptually different issues: (1)
the hierarchical complexity of the task to be solved and (2) the psych
ology, sociology, and anthropology of such task performance and how th
at performance develops. The notion of the hierarchical complexity of
tasks, introduced here, formalizes the key notions implicit in most st
age theories, presenting them as axioms and theorems. The hierarchical
complexity of tasks has itself been grounded in mathematical models (
Coombs, Dawes, & Tversky, 1970) and information science (Lindsay & Nor
man, 1977). The resultant definition of stage is that it is the highes
t order of hierarchical complexity on which there is successful task p
erformance. In addition to providing an analytic solution to the issue
of what are developmental stages, the theory of hierarchical complexi
ty presented here allows for the possibility within science of scaling
the complexity in a form more akin to intelligence, (C) 1998 Academic
Press.