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801.
How do managers expect the proficiency of users and the power of the computers to determine overall performance? Five different models are proposed: (a) a matching model in which optimal performance is achieved when the power of the system is judged to be compatible with the proficiency of the user, (b) an averaging model in which expected performance is the average of the values of user proficiency and system power, (c) a multiplying model in which performance is the product of the values of user proficiency and system power, (d) a human/computer ratio model in which performance is determined by the ratio of system power over total effort, and (e) a computer/human ratio model in which performance is determined by the ratio of user proficiency over total effort. The applicability of these models was assessed by having managers and students of management predict performance in human/computer systems from information about the user's proficiency with computers and the power of the system. Participants rated 16 combinations of user proficiency and system power from a 4 × 4 factorial design. The pattern of ratings indicated that 51 per cent used a multiplying model and 25 percent used an averaging model; whereas, only 6 percent used the matching model and 4 percent used a ratio model. The remaining 14 percent did not follow any model clearly. Implications of these results were discussed for the design of the human/ computer interface, training and selection of users, and the cost-benefit tradeoffs for investment in user training versus equipment acquisition.  相似文献   
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Efforts to improve the implementation of evidence-based treatments (EBT) have recently made important strides. One such example is understanding the vital role that weekly consultation plays as therapists learn to deliver an EBT. Because mechanism-based research can further support EBT implementation, the present study sought to examine the potential relationship between therapist self-efficacy in relation to treatment fidelity and outcomes.We examined therapist self-efficacy ratings from 80 therapists working with 188 patients. These data were collected as part of a randomized controlled implementation trial testing cognitive processing therapy (CPT). Across post-workshop training conditions, we ran multilevel models to assess (1) changes in therapist self-efficacy, (2) therapist self-efficacy in relation to treatment fidelity, and (3) therapist-self-efficacy in relation to patient PTSD symptom outcomes.We found that therapist self-efficacy significantly improved over the course of 6 months of CPT training. Baseline therapist self-efficacy was differentially associated with client outcomes based on post-workshop training condition. Specifically, therapists with low self-efficacy that did not receive post-workshop consultation tended to have poorer outcomes than therapists with low self-efficacy that received consultation. In the present sample, therapist self-efficacy was not related to treatment fidelity.As this was the first study to examine therapist self-efficacy in the implementation of an evidence-based treatment, our findings suggest that self-efficacy may be an important implementation factor in treatment outcomes and worthy of ongoing research.  相似文献   
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Perception and production of language often have a problem-solving component to them, and this has not been much studied. The present article describes an exploratory approach to some aspects of production which required college students to reorder sentential anagrams. The main finding was that the number of words to be ordered was the greatest influence on performance, whereas little if any influence was exerted by the grammatical variables studied. Although the problem-solving process does not model all language use, it may model the more creative aspect, in which people try to make nonstandard statements. In contrast to a common current view that sentences are holistic, well-formed linguistic objects in mind, the present work emphasizes the developmental and interactive aspect of language production.This work was supported by Grant A7655 from the National, Research Council of Canada and by Leave Fellowship W 760 174 from Canada Council.  相似文献   
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A Bayesian network (BN) is a graphical model of uncertainty that is especially well suited to legal arguments. It enables us to visualize and model dependencies between different hypotheses and pieces of evidence and to calculate the revised probability beliefs about all uncertain factors when any piece of new evidence is presented. Although BNs have been widely discussed and recently used in the context of legal arguments, there is no systematic, repeatable method for modeling legal arguments as BNs. Hence, where BNs have been used in the legal context, they are presented as completed pieces of work, with no insights into the reasoning and working that must have gone into their construction. This means the process of building BNs for legal arguments is ad hoc, with little possibility for learning and process improvement. This article directly addresses this problem by describing a method for building useful legal arguments in a consistent and repeatable way. The method complements and extends recent work by Hepler, Dawid, and Leucari (2007) on object‐oriented BNs for complex legal arguments and is based on the recognition that such arguments can be built up from a small number of basic causal structures (referred to as idioms). We present a number of examples that demonstrate the practicality and usefulness of the method.  相似文献   
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