Improvement of skills for solving‐ ill‐defined problems

Klein, Gary; Weitzenfeld, Julian

doi:10.1080/00461527809529193

Cited by 32 publications

(9 citation statements)

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“…Sometimes, a decision maker will retrieve and use an analogy without thinking about it, and at other times there will be a deliberate search for an analogue, and a careful mapping of the analogue onto the situation. Klein and Weitzenfeld (1978) have described the importance of analogical reasoning for diagnosing a problem, and there have been a number of key research projects 27 to clarify different aspects of analogical reasoning. Recently, analogical inference has become relevant to system designers because of the interest in Case-Based Reasoning, a computational approach to expert systems that uses analogues rather than rules.…”

Section: Strategies For Developing Situation Assessmentmentioning

confidence: 99%

“…However, in a naturalistic context, the problem-solving requirements of clarifying goals and evaluating possible solutions must merge with the decision requirements to assess situations and evaluate possible solutions. Klein and Weitzenfeld (1978) have pointed out that most naturalistic tasks involve ill-defined goals, so that the usual advice to first define the goal and then search for options is inappropriate, because the process would never get past this first step.…”

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Naturalistic Decision Making: Implications for Design

Klein¹

1993

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Public reporting burden tor thu collection of information n eitimated to average I hour oer reiponve. including the time tor reviewing imtructiom. vearching einting date tourcev gathering end maintaining the data needed, end completing end reviewing the collection of information Send commenti regarding thu burden eitimateor any other atpectof thit collection ot information, including suggestion, for reducing this burden, to watnington Headquarters Services. Directorate for information Operations and Reborn. 1215 Jefferson Davit Highway. Suite 120a. Arlington. VA 22202-4302. and to the Office of Management and Budget. Paperwork P-eduaion Protect (070*-OtM). Washington. DC 20501. AGENCY USE ONLY (leave blink)2. REPORT DATE April 1993 REPORT TYPE AND DATES COVEREDState-of-the-Art Report TITLE AND SUBTITLENaturalistic Decision Making: Implications for Design AUTHOR(S)Gary Klein, Ph.D. S. FUNDING NUMBERS DLA900-88-0393 PERFORMING ORGANIZATION NAME(S) AND AOORESS(ES)University Recent years have witnessed strong progress in understanding how people make decisions in operational settings.The emerging field of Naturalistic Decision Making (NDM) is at a point to afford system developers (including design engineers, human factors engineers, ergonomics specialists) different tools and methods for designing interfaces/systems that will better support decision making in those settings.Decision requirements can be identified from the early conceptual design phase through redesign.The NDM framework attempts to describe the way in which people handle difficult conditions within the context of the overall setting or task.This SOAR describes various decision strategies used by individuals and teams to assess a situation, diagnose a problem, and select a course of action.The impact of stress upon these strategies is also considered.To help understand what people are thinking as they perform difficult tasks, the procedures for conducting Cognitive Task Analyses to examine design requirements are also examined. SUBJECT TERMS PURPOSE:To describe the current state of knowledge about the way people make decisions in operational settings. This SOAR is written for system developers, including design engineers, human factors engineers, ergonomics specialists, and others who try to design systems, subsystems, and interfaces that will support better decision making.The problem addressed by this SOAR is that system developers usually aren't given details about how the people operating the system will use it to make difficult judgments and decisions. The SOAR explains how to obtain the decision requirements, and how to incorporate them into the design process. The SOAR also describes tools for identifying and using decision requirements. The SOAR is intended to show developers how to use decision requirements tools and methods to clarify system features and to design system interfaces that are easier to use at critical times. BOUNDS: This SOAR does NOT provide a detailed review of the decision-making literature of the past 35 years, since tha...

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Section: Strategies For Developing Situation Assessmentmentioning

confidence: 99%

mentioning

confidence: 99%

Naturalistic Decision Making: Implications for Design

Klein¹

1993

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“…Klein and Weitzenfeld [10] pointed out that the stage model is suitable for well-defined goals, but not for ill-defined goals in which the terminal state is unclear. If the goal is well defined, then it makes sense to specify it as completely as possible before proceeding.…”

Section: The Stage Model Of Problem Solvingmentioning

confidence: 99%

“…479-493, 1992. [10] Y. Bar-Shalom and K. Birmiwal, "Consistency and robustness of pdaf for target tracking in cluttered environments," Automatica, vol. 19, no.…”

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confidence: 99%

The role of leverage points in option generation

Klein

Wolf

1998

IEEE Trans. Syst., Man, Cybern. C

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157When the motion model depends on terrain information, the use of terrain-based densities (and conditional densities) becomes potentially much more effective than in the static case. In the static case, the prior density gradually becomes less and less influential with time as the estimates become more peaked. When the targets' movements depend on the terrain features, though, the terrain information can remain highly influential over time. VII. CONCLUSIONSIt is clear mathematically that the use of prior information can improve both association and estimation algorithms. In practice, however, using even moderately complicated prior densities is computationally expensive. In many cases, the use of prior information does not result in significant improvements, especially when used for data association. With limited computational resources it may be preferable to devote the available resources to other techniques, such as multiple hypothesis algorithms, batch algorithms, or the use of higher level reasoning. The terrain information might also be used in a gating algorithm, rather than to construct a prior density.While using the prior density can be expensive, there are cases where the extra expense is justified and where the prior provides especially valuable information. This suggests a hybrid approach. Dynamically allocating the available resources to tradeoff between the various approaches available should result in an algorithm with high performance across a broader range of input statistics. The problem then becomes to determine heuristics for effectively making the tradeoff decisions. Analyses such as those we have presented for the static problem can serve as a first step for developing these heuristics.Another area that needs further research is the representation scheme for the prior densities. The appropriate representation is a function of the class of densities to be represented, the expected class of sensor report and target state distributions, and of the particular association-estimation algorithms being used. While we have simply discretized over a rectangular grid, many other schemes are available, such as Gaussian mixtures, vectorized representations, neural nets, etc. In particular, for the cases we have considered, Fourier-domain density representations (characteristic functions) might be appropriate, especially if they can be efficiently bandlimited to the most useful frequency ranges.

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“…Further, such practice should comprise tasks that build upon the individual's current knowledge at a given time and should enable provision of performance feedback (Ericsson et al, 1993;Brandsford et al, 2000). Further, the educational psychology literature (e.g., Klein and Weitzenfeld, 1978) has presented frameworks for improving skills in solving ill-defined problems. However, the questions remains, "how may such approaches be implemented in an online context?"…”

Section: Background Literaturementioning

confidence: 99%

Toward an Understanding of Development of Learning to Solve Ill-Defined Problems in an Online Context: A Multi-Year Qualitative Exploratory Study

Peddibhotla

2016

OLJ

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The case study is a classic tool used in several educational programs that emphasizes solving of illdefined problems. Though it has been used in classroom-based teaching and educators have developed a rich repertoire of methods, its use in online courses presents different challenges. To explore factors that develop skills in solving ill-defined problems, I present results of a seven-year study seeking to develop tools for facilitating and assessing skills for case studies in an online graduate class. This study began with the introduction of a classroom-based case method into an online graduate class. Over the following years, I used three sources of data to make changes to the design of the course with respect to case studies: feedback from students, feedback from colleagues, and measurement of student performance. Findings suggest the following general approaches may work better in online classes involving case studies in particular, and more broadly in courses that teach solving of ill-defined problems: 1) immersion (or the use of drills) to support trial and error learning especially given the additional distractions of an online setting as compared to attending classes on campus; 2) structure to facilitate learning as it involves building skills based on absorptive capacity that students acquire from skills learned earlier; 3) social learning to enhance trial and error learning; 4) inductive learning that may be more appropriate to online teaching as compared to deductive learning; 5) provision of structure instead of participation by the instructor may encourage self-discovery of methods to solve ill-defined problems in an online context.

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Improvement of skills for solving‐ ill‐defined problems

Cited by 32 publications

References 10 publications

Naturalistic Decision Making: Implications for Design

Naturalistic Decision Making: Implications for Design

The role of leverage points in option generation

Toward an Understanding of Development of Learning to Solve Ill-Defined Problems in an Online Context: A Multi-Year Qualitative Exploratory Study

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