Coping with the complexities of multiple-solution problems: a case study

Smith, Philip J.; Galdes, D.; Fraser, Jane; Miller, Thomas E.; Smith, Jack W.; Svirbely, John R.; Blazina, Janice; Kennedy, Melanie S.; Rudmann, Sally V.; Thomas, Donna L.

doi:10.1016/s0020-7373(05)80086-0

Cited by 22 publications

(11 citation statements)

References 5 publications

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“…4,5 Workload has been shown to contribute to decision making and errors in other studies in the medical field. 6 Fatigue is a major factor in performance decrements and cognitive decline.…”

Section: Variables Selectedmentioning

confidence: 99%

Supervision of Students May Protect Academic Physicians from Cognitive Bias: A Study of Decision Making and Multiple Treatment Alternatives in Medicine

Roswarski

Murray

2006

Med Decis Making

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“…4,5 Workload has been shown to contribute to decision making and errors in other studies in the medical field. 6 Fatigue is a major factor in performance decrements and cognitive decline.…”

Section: Variables Selectedmentioning

confidence: 99%

Supervision of Students May Protect Academic Physicians from Cognitive Bias: A Study of Decision Making and Multiple Treatment Alternatives in Medicine

Roswarski

Murray

2006

Med Decis Making

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“…We have conducted a series of empirical studies aimed at understanding how to engineer computer systems to successfully aid students in learning how to solve complex problems (Smith, Galdes, Fraser, et al, 1991;Smith, Miller, Fraser, et al, 1991). The studies presented here provide data regarding the teaching effectiveness of an expert-system-based tutor, the Transfusion Medicine Tutor (TMT), when used by medical technology students to learn an important problem-solving task, the identification of alloantibodies in a patient's blood for the purpose of finding compatible blood for transfbsion.…”

Section: Introductionmentioning

confidence: 99%

The Transfusion Medicine Tutor: A Model for the Design and Use of Expert Systems for Teaching

Obradovich

1996

Proceedings of the Human Factors and Ergonomics Society Annual

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There is a long research history addressing the design of knowledgebased systems for tutoring. There exists, however, very little rigorous empirical data describing the impact o f such systems on users. This paper presents the results of two studies that were conducted to investigate the effectiveness of an expert system for teaching medical technology students a complex abduction task, the identification of alloanbbodies in a patient's blood. The first study, involving 30 students, showed that those students who used the system with all intelligent tutoring fimctions turned on and with instructor assistance available went fiom 0% correct on a pre-test case to 80% -93% correct on post-tests (p < 0.001). Students in a control group, using a passive version of the system with the tutoring functions turned off, went from 7% correct on a pre-test case to 2!7% correct on post-tests (non significant; p > 0.05). The results of the second study found that 36 students who used the system with all intelligent tutoring functions enabled but without instructor assistance went fiom 19% correct on a pre-test to 83% -86% correct on the post-tests (p < 0.001). In order to better understand the roles of the computer and the teacher in these studies, computer logs and videos collected for each student were analyzed and coded for certain key behaviors.

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“…In preparation for designing a computer system to support blood bankers in identifying antibodies, background studies were performed to learn what characteristics of the task make the problem-solving difficult (Miller et al, 1993;Smith et al, 1991a;Smith et al, 1991b). It was found that antibody identification can be characterized as an abductive reasoning task, where one must reason to the best explanation of the data.…”

Section: Introductionmentioning

confidence: 99%

Factors Influencing the Cooperative Problem-Solving of People and Computers

Guerlain

1993

Proceedings of the Human Factors and Ergonomics Society Annual

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It was the goal of this research to study the influence of different computer system designs on cooperative problem-solving performance. In particular, given that a computer has some knowledge about a domain, how should such knowledge be shared with the practitioner such that overall performance is improved? It was hypothesized that multiple factors contribute to performance changes, and that such factors may interact. In order to test these ideas, a formal, empirical study was conducted comparing the effectiveness of a critiquing system vs. a partially automated system when performing a medical diagnosis task. Thirty-two certified practitioners used one of the two systems to solve five test cases. The results showed that the design of the system interacted with the case characteristics and the competence level of the practitioners such that overall performance was slightly better with the partially automated system on cases where the computer's knowledge was competent (5.6% vs. 11.9% misdiagnosis rate) but on a case where the computer's knowledge was incompetent, the partially automated system induced more errors (76% vs. 43% misdiagnosis rate, p < .05). Details of the interactions causing this tradeoff in performance are discussed so that future designers may take what was learned from this study and apply it to their work.

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Coping with the complexities of multiple-solution problems: a case study

Cited by 22 publications

References 5 publications

Supervision of Students May Protect Academic Physicians from Cognitive Bias: A Study of Decision Making and Multiple Treatment Alternatives in Medicine

Supervision of Students May Protect Academic Physicians from Cognitive Bias: A Study of Decision Making and Multiple Treatment Alternatives in Medicine

The Transfusion Medicine Tutor: A Model for the Design and Use of Expert Systems for Teaching

Factors Influencing the Cooperative Problem-Solving of People and Computers

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