The significance of prescriptive decision theory for instructional design expert systems

Abstract

Decision-making plays a central role in computer-based learning environments as well as in computer-based instructional design environments. Therefore, it is also an explicit function of expert systems which are software products aimed at modeling the reasoning and decision-making of experts by explaining and making available human expert knowledge concerning performance of the particular task of instructional planning. This chapter will report the background and scope of the “prescriptive decision theory” (PDT) for expert systems in instructional design environments aimed at providing appropriate learning environments. In comparison with descriptive or normative decision theories, PDT involves interactive procedures aimed at revealing the preference structure of the decision-maker. Interactive procedures of decision-making are characterized by an interaction between subjective phases where the decision-maker has to offer local statements about his preference structure, and objective phases of calculation where the computer investigates alternative propositions based on available data. Exemplifying this procedure, a multiple-attribute-utility-test (MAUT) will be described of choosing media in the context of instructional design. With the help of this method it is possible to evaluate alternatives by taking into account the relative importance of individual goals and outcomes for the decision-maker, whereby each phase of the evaluation process is fully explicated. The significance of PDT and MAUT also will be discussed with regard to other relevant parts in the instruction design environments.