Getting it right generally, but not precisely: learning the relation between multiple inputs and outputs

Abstract

In real-world situations, people are often faced with the complex task of deciding which of many potential variables are affecting their own or others' behavior, as well as noting which specific aspects of behavior are being affected. Although it is common for professionals who encounter such conditions to claim that they acquire accurate and specific knowledge from their experience, it is unclear that such confidence is justified. Using a managerial task, we examined participants' ability to learn how various interventions affect various aspects of their employees' performance. The results of three experiments reveal that although participants appear to avoid prescribing an intervention that has a positive effect on a primary performance measure and a negative side effect on a secondary measure, when asked directly about the impact of the intervention, they respond by reducing their judgments of its positive impact. This was true regardless of whether participants indicated clear knowledge of its negative side effect (Experiment 3) or did not (Experiments 1 and 2). Thus, participants appear to be automatically integrating across the effects on different outcome measures.

Constraint Analysis National Health Insurance

“…Factors influencing medical record completeness include knowledge, experience, competence, policies, and procedures related to claims. Knowledge derived from experience might not always yield accurate outcomes (Mathews et al, 2011). The agency's coding regulations were changed regularly, demanding coders to remain updated.…”

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“…In other words, the presence of a context that could invoke general prior knowledge could be utilized more effectively than any specialized knowledge concerning the animacy of the objective being controlled. There is good evidence to suggest that people recruit prior experiential knowledge in order to perform complex decision making and problem solving tasks (Lane, Mathews, Sallas, Prattini, & Sun, 2008;Mathews et al, 2011).…”

“…For many, the appeal of this research domain is because of its high validity, because many real world decision-making problems are dynamic and complex (e.g., Berry & Broadbent, 1984;Mathews, Tall, Lane, & Sun, 2011;Osman, 2010;Selten, Pittnauer, & Hohnisch, 2011). The contexts used in this research field range from controlling a water purification plant (Burns & Vollemeyer, 2002), an ecosystem (Vollemeyer, Burns & Holyoak, 1997), water pump (Gonzalez, 2005), sugar factory (Berry & Broadbent, 1984), military management (Mathews et al, 2011), to a patient's health (Osman & Speekenbrink, 2012). However, to the authors' knowledge, there have been no dedicated studies that have compared decision-making behavior across different contexts, in order to uncover the types of contexts that would facilitate decision-making behavior in complex dynamic systems.…”