As we approach the next millenium most humans are facing
serious concerns about being overtaken, even consumed, by the very
technologies meant to make their lives easier. Educational
Technologists (and many others in related fields) have been given the
task of designing learning systems which can take advantage of new
technologies and apply them to traditional learning paradigms. Such
systems today can not be developed within the constraints of
traditional Ò...group-based, time-based,
teacher-as-primary-source-of-instruction model of educationÓ (Reiser
& Salisbury, 1995). Our hope is to develop learning systems which
can utilize second order artificial intelligence capable of
automating its decision making processes to adapt to the needs of the
learner and be ÔcognisantÕ of all the implications and nuances of
that ÔstyleÕ or model presented to the learner and be maleable
internally (self-correcting) and externally (by the learner) in order
to engender a rich world schema in which learners can emerse
themselves. The system will then make ongoing adjustments as it
interacts with each new learner. We are therefore faced with the
challenge of developing learning systems which take on human
characteristics, combining cognisance and mechanical immediacy in its
serving the needs of the learner. Such a
MetacognitiveCybernetic (MC)
model seems to be utopian and the stuff of science fiction, yet there
are a number of research projects which are moving in this direction
and elements of such models are appearing in embryonic form today
that bode well for the future. In this paper I hope to describe some
of these projects and technologies, how they are changing the way
humans and technologies are converging to deliver new learning
experiences and perhaps how such developments are portending the
creation of new learning theories born from the seeds of this
technological (r)evolution.
Pick a different paper