ADVANCING THE THEORY OF DSS DESIGN FOR USER CALIBRATION - Human-Computer Interaction and Management Information Systems: Foundations - page 54

PROBLEM NOVELTY AND THE COMPONENTS OF THE THEORY
In addition to defining the components, a design theory must consider how the components work
in a specific situation to achieve the desired goal (Walls et al., 1992). The DSS dialog design the-
ory contends that the functional usefulness of expressiveness, visibility, and inquirability charac-
teristics depend upon the novelty of the problem. This contention is supported by the literatures
that suggest a relationship between problem novelty and one's knowledge, and the role of knowl-
edge in decision making and user calibration. Recall that according to the theory of symbolic
representation in problem solving, problem novelty is based on both the degree and type of
abstraction needed to generate a solution to a problem. The type of abstraction is a reflection of
the decision maker's cognitive style, and the degree of abstraction reflects the proportion of memory-
based information contained in the decision maker's mental representation of the problem. Also
recall that as problem novelty increases, the degree (and perhaps type) of abstraction needed to
conceptualize the problem increases, as does the likelihood of miscalibration.
Problem novelty is also a characteristic of problem structure, a well-known concept in the DSS
literature (Gorry and Scott Morton, 1971; Simon, 1960). Problem structure connotes something
about the problem. Problem novelty on the other hand, as defined earlier by degree and type of
abstraction, reflects something about the decision maker(s) in relation to the problem. Because
decision-maker calibration is based on one's belief in the quality of a decision, it reflects some-
thing about the decision maker, and therefore problem novelty seems to be a more accurate
descriptor than problem structure of the nature of the role played by the problem in user calibra-
tion. However, problem novelty and problem structure are closely aligned.
Problem novelty, according to DSS dialog design theory, determines the functional usefulness
of expressiveness, visibility, and inquirability for decision making and user calibration. Problem
novelty reflects the degree (and type 1 ) of abstraction needed to develop a mental representation of
the problem. Problem novelty is not an indication of one's perception of familiarity. Usually prob-
lems that seem “familiar” are in fact the ones most susceptible to inference-based mental reason-
ing that is illusory (Kaufmann, 1980; Mahajan, 1992). If the degree of problem novelty is low, a
very high proportion of one's mental representation of the problem is based on direct memory.
Conversely, if the degree of novelty is high, a very low proportion of one's mental representation
of the problem is based on direct memory. As the degree of problem novelty increases, the pro-
portion of memory in one's mental representation of the problem decreases and the likelihood of
miscalibration increases (Juslin, 1993; Wagenaar, 1988). The relationships between the degree of
problem novelty and the functional usefulness of the different dialog symbols and actions pro-
posed by the DSS dialog design theory are illustrated in Figure 5.3.
Figure 5.3 proposes that the usefulness of expressiveness, visibility, and inquirability depend
upon the degree of problem novelty. If the degree of problem novelty is low, the functional use-
fulness of expressiveness for user calibration is high. In other words, for problems where the
user's mental symbols and methods of reasoning are naturally linguistic, a DSS dialog based on
expressiveness alone, when properly designed, may be sufficient to support effective decision
making. However, as the degree of problem novelty increases, the usefulness of the expressive-
ness dimension decreases relative to visibility and inquirability characteristics. When the novelty
of a problem requires that the decision maker employ a mental representation based on visual
imagery to solve the problem, the DSS must provide the decision maker with effective visibility
capabilities. Likewise, when the novelty of a problem requires that the user(s) employ overt
exploratory reasoning to build a mental representation of the problem, effective support requires
the DSS dialog to deliver necessary inquirability capabilities.