The Minnesota Adaptive Instructional System research program investigates variables and conditions that improve learning through adaptive instructional strategies. The macro- level component of the system includes a learner model, knowledge base, and expert tutor model. At the micro-level there are nine variables which form the possible…

Examines the functional characteristics of intelligent computer assisted instruction (ICAI) and discusses the requirements of a multidisciplinary cooperative effort of its development. A typical ICAI model is presented and intelligent features of ICAI systems are described, including modeling the student's learning process, qualitative decision…

Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

Reviews the structure of intelligent computer assisted instruction (ICAI) systems, gives some examples of such systems, and discusses their relative strengths and weaknesses. Four references are listed. (MBR)

Presents a knowledge representation model that was designed for instructional decision making. Topics discussed include classification models for instructional design; artificial intelligence; semantic networks; natural language; and data models, including network and hierarchical models. An example is given of knowledge analysis for a secondary…