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.