Improvement of skills for solving ill-defined problems

Klein, Gary; Weitzenfeld, Julian

doi:10.1037/e532182009-001

Cited by 6 publications

(10 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The evidence for the flexecution model came primarily from research on military planning. Initially, evidence was gathered from work underscoring the challenges of wicked problems (Brehmer, 2005; Dorner, 1996; Klein, 1996; Klein & Weitzenfeld, 1978) and from field research based on exercises with military planning teams (Klein & Miller, 1999; Klein et al, 1996; Schmitt & Klein, 1999; Ross, Klein, Thunholm, Schmitt, & Baxter, 2003; Ross, Thunholm, et al, 2003). Its precursor, the recognitional planning model, has also fuelled work by others to look at rapid re-planning in complex operational environments (Cheah et al, 2005; Thunholm, 2005).…”

Section: Sensemaking As a Process Of Adaptive Understandingmentioning

confidence: 99%

Adaptive skill as the Conditio sine qua non of expertise.

Ward

Gore

Hutton³

et al. 2018

Journal of Applied Research in Memory and Cognition

View full text Add to dashboard Cite

This critical interpretive research synthesis is on the topic of adaptation and skill. After an initial identification of 1995 abstracts we identified and collated a database of 140 publications that explicitly reference expertise and adaptation. We found that empirical data on adaptive skill are sparse and the literature base is largely conceptual. We differentiate the adaptive nature of expertise from routine or every day skill, and we redress the balance between what constitutes expertise and when expertise matters. We present an overview of current models of expertise including a project that we completed for the UK Ministry of Defence on the nature of adaptive skill. We discuss implications for future training by presenting empirically based training principles designed to develop adaptive skill. We assert that adaptive skill is the conditio sine qua non of expertise and conclude with suggestions for further research.

show abstract

Section: Sensemaking As a Process Of Adaptive Understandingmentioning

confidence: 99%

Adaptive skill as the Conditio sine qua non of expertise.

Ward

Gore

Hutton³

et al. 2018

Journal of Applied Research in Memory and Cognition

View full text Add to dashboard Cite

show abstract

“…21 People discover and define goals during the attempt to reach them. The nature of such problem solving is to simultaneously pursue the goal and define it.…”

Section: Solving Wicked Problemsmentioning

confidence: 99%

Flexecution as a Paradigm for Replanning, Part 1

Klein¹

2007

IEEE Intell. Syst.

View full text Add to dashboard Cite

79Published by the IEEE Computer Society Rather, flexecution entails changing the goals themselves based on discoveries made during execution. In pursuing illdefined goals, we must expect to revise and even replace the goals we initially stated during the planning phase.One of my objectives in writing these essays is to describe the importance of goal discovery to planners and project managers who might not appreciate the difficulties posed by ill-defined goals. A second objective is to offer suggestions to computer scientists who design mixedinitiative systems about how to better support planning and execution with ill-defined goals.We'll begin with the notion of planning to set the stage for comparing planning using clear goals versus planning and execution using emergent goals. PlanningPlans are prescriptions or roadmaps for procedures that can be followed to reach some goal, with perhaps some modification based on monitoring outcomes. Planning is generally considered the process of choosing and organizing courses of action on the basis of assumptions about what will happen in the future. 1 Plans describe contingencies and interdependencies such as actions that must occur first as a precondition for later actions.The more clear and detailed your goals, the easier it is to construct a plan, prepare a timeline, and gauge progress. Clear goals can be sufficiently specified to enable planners to identify tasks that, if followed, will reach the intended goal. A plan specifies a set of actions with which you intend to transform a current situation into a goal state. This type of planning is essentially problem solving-finding a way to take some actions that will result in the transformation, as represented in figure 1a.Planning-as-problem-solving generally relies on a set of well-understood representations and mechanisms, such as planning graphs, task networks, search in a state space, chaining, type hierarchies, and constraints on variables. [2][3][4] These mechanisms and approaches seem to run into difficulty when faced with the intractability of large, messy, real-world problems. For such planning problems, the state spaces aren't completely predefined, and planning requires human decision making based on knowledge and sensitivity to context. [5][6][7] The field of intelligent planning systems has reached into new areas in recent decades, such as distributed planning and continuous planning 8 and mixed-initiative planning or "planning assistants." 9 My proposal is consistent with these developments, especially the notion of planning as a dialogue among human and machine agents. 10 Ill-defined goals and wicked problemsThe challenge of ill-defined goals arises when many or most of the goals' features can't be specified in advance, as illustrated in figure 1b. Herbert Simon and other researchers have written about the differences between wellstructured and ill-structured problems. 11 Here, I focus on the clarity of goals, which is just one dimension of the problem structure.We can represent well-defined goals using ...

show abstract

“…Klein and Weitzenfeld (1978) hypothesized that analogid reamning was a major source of goal clarification for ill-defined problems, so we would anticipate that we should see evidence for the use of analo$y in design.…”

Section: The Role Of Analogy In Designmentioning

confidence: 99%

“…Industrial applications to problems, such as marketing predictions and planning, seem feasible. The use of analogical reasoning for goal clarification has been described by Klein and Weitzenfeld (1978) as a means of addressing ill-defined problems. Comparison cases can be very helpful in identifying goal properties (thereby making the goal more well defined), in suggesting choices to be considered, and in providing information for anticipating the outcomes of certain choices.…”

Section: Theoretical Implicationsmentioning

confidence: 99%