The Systemic Representation of Knowledge for Truly Individualized Computer Assisted Instruction
Abstract
Current computer assisted instruction software (CAl) utilizes
advances in interactive technology and artificial intelligence to achieve
individualized instruction. Because it has adopted authoring techniques
from traditional educational media, however, it presents a finite,
hierarchical representation of knowledge which is incapable of addressing
the unique and varying needs of each student. Recent research in cognitive
psychology suggests an alternate, systemic representation of knowledge.
Rather than the rigidly linear, content dependent architecture currently
used, systems theory presents multiple complex and infinitely variable
arrangements whose essential characteristics stem from the inter-relations
between individual entities. Traditional representations of knowledge as
presented in current CAl software are incongruous with the naturally
occurring cognitive structures revealed by psychological research. In
order that CAl may achieve its goal of providing truly individualized
instruction, new authoring practices following a systemic representation of
knowledge must be developed. Integrated with the software technology
currently utilized by CAl, such techniques would address the shortcomings
of the hierarchical model of knowledge and present both content and
structure in accordance with the individual student's needs.