Design Problem Solving: Knowledge Structures and Control Strategies

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Where is it happening? How is it happening? When is it happening? With whom is it happening? To be an effective manager, you need to address issues more than people. Why is it happening? Write down a five-sentence description of the problem in terms of "The following should be happening, but isn't It may be helpful at this point to use a variety of research methods. Defining complex problems: If the problem still seems overwhelming, break it down by repeating steps until you have descriptions of several related problems.

Verifying your understanding of the problems: It helps a great deal to verify your problem analysis for conferring with a peer or someone else. Prioritize the problems: If you discover that you are looking at several related problems, then prioritize which ones you should address first. Understand your role in the problem: Your role in the problem can greatly influence how you perceive the role of others.

Look at potential causes for the problem It's amazing how much you don't know about what you don't know. Therefore, in this phase, it's critical to get input from other people who notice the problem and who are effected by it. It's often useful to collect input from other individuals one at a time at least at first. Otherwise, people tend to be inhibited about offering their impressions of the real causes of problems. Write down what your opinions and what you've heard from others. Regarding what you think might be performance problems associated with an employee, it's often useful to seek advice from a peer or your supervisor in order to verify your impression of the problem.

Write down a description of the cause of the problem and in terms of what is happening, where, when, how, with whom and why. Select an approach to resolve the problem When selecting the best approach, consider: Which approach is the most likely to solve the problem for the long term? Which approach is the most realistic to accomplish for now? Do you have the resources? Are they affordable? Do you have enough time to implement the approach? What is the extent of risk associated with each alternative? Plan the implementation of the best alternative this is your action plan Carefully consider "What will the situation look like when the problem is solved?

What systems or processes should be changed in your organization, for example, a new policy or procedure? Don't resort to solutions where someone is "just going to try harder". How will you know if the steps are being followed or not? How much time will you need to implement the solution? Write a schedule that includes the start and stop times, and when you expect to see certain indicators of success. Who will primarily be responsible for ensuring implementation of the plan?

Write down the answers to the above questions and consider this as your action plan. Communicate the plan to those who will involved in implementing it and, at least, to your immediate supervisor. Monitor implementation of the plan Monitor the indicators of success: Are you seeing what you would expect from the indicators? Will the plan be done according to schedule? If the plan is not being followed as expected, then consider: Was the plan realistic?

Are there sufficient resources to accomplish the plan on schedule? It included a clear motif but required deep search for the correct evaluation of the solution. In contrast, Neutral problem 2 was more difficult, an atypical problem with no clear motif or way of proceeding. The first problem not only yielded clear differences between the skill levels in the solution quality GM [0. While there were no significant differences among skill levels in the breadth of search, all other relevant protocol statistics e.

The parameters of depth and breadth of search for players of different skill on Neutral problem 1. Error bars present standard error of the mean. The second neutral problem was more difficult than the first and the quality of solutions was lower. Now there were no significant differences in mean depth, maximum depth, number of candidate moves, or number of episodes between skill levels Fig. Although there were indications that more skilled players solved the problem better 1.

The parameters of depth and breadth of search for players of different skill on Neutral problem 2. The difference between the two Neutral problems was striking and underlines the importance of familiarity. It thus seems that when there is a clear line of analysis as in the first Neutral problem, the more skilled players are, the more likely they are to find it and research it in greater depths and consequently get a better result Fig. Focused experience leads to acquisition of knowledge about a domain, its structure, common problems, and ways of dealing with those problems.

Unsurprisingly, people with a vast domain experience experts are able to solve problems and remember stimuli from the domain better than people with a limited experience novices. In this study, we used the specialization paradigm showing that, even among experts, with the same level of general expertise, there are differences that are connected with specific focused experience. Expert chess players both remembered and solved problems arising from their area of opening specialization better than problems outside their specialization. Additional evidence of the importance of context is provided by the result on the Neutral problems.

The same players who showed superior recall performance on the problems from within and inferior performance with the problems outside their specialization, now, in a context equally familiar to both groups, displayed similar recall performance. The most complex, finely tuned knowledge structures, templates, vary between individuals as a function of exposure to certain types of stimuli. In chess, they can be a consequence of opening specialization. Given that all participants in this study were highly skilled chess players, it is reasonable to assume that the difference in the recall between the two groups of differently specialized experts was a direct outcome of the differences in the structure of their templates.

When confronted with problems within their area of specialization, they were more likely to generate more successful solutions to such an extent that their performance was similar to that of the players nominally stronger for 1 SD but solved the same problems outside their area of specialization. The skill differences, however, were intact on the Neutral problems belonging to neither of the two areas of specialization. Although this would not be surprising to chess experts who know the advantage of being in a familiar situation, the results have theoretical significance and practical implications.

Just as the perceptual knowledge of chunks and templates grows with the exposure to opening specific stimuli within the domain, so does the knowledge of the possible actions that can be associated with them. Knowledge of perceptual patterns is of little use without knowing what methods should be used with them, but knowledge of methods is also insufficient for a high level of expertise without knowledge of the situations where these methods are likely to succeed.

These considerations have direct applied implications for education. Students were specifically encouraged to learn new perceptual chunks rather than to focus on the actions without knowing when they were appropriate. It is important to point out that even memory superiority of those individuals was based on their previous knowledge. When confronted with problems within their area of specialization, they investigated fewer solutions, spent less time, generated fewer episodes, and wandered less than players of the same level of skill who were outside their area of specialization but considered solutions in greater depth.

The players who were more familiar with the positions concentrated on the most likely solutions and investigated them in more detail. It is not surprising that greater depths of search were associated with the problems within the opening of specialization and greater breadth with the positions outside.

Problem Solving Techniques #2: Value Analysis

The problems outside the area of specialization were so unfamiliar that it sometimes was a real surprise for the players to be involved in solving such positions. I do not know anything about this opening! I do not play the Sicilian with White nor with Black so it is difficult for me to grasp the complete problematic in a short period of time. Well, I will have to try to do it using normal chess reasoning. The Neutral problems again provide the evidence on the importance of the context. The differences between skill levels in strategies, however, were in particular clear cut on the first Neutral problem.

Most notably, their depth of search was noticeably greater than that of their weaker colleagues. At first sight, this seems to contrast with the finding from de Groot and the main assumption in theories of expertise e. It is possible that deep search was not necessary for the best solution to be discovered in the position that de Groot used to draw his conclusion. The depth of search depends on the need for it. The differences that were observed on the specialization problems and the first neutral problem did not hold on the more difficult second neutral problem.

Most surprisingly, super experts also did not find better solutions although differences in both parameters were present favoring super experts. Finally, we saw that the strategies experts employ are flexible depending on the context which makes them difficult to pinpoint and teach. Different people, even if they are at the same high skill level, find different ways of dealing with problems that work well for them. The conclusion of this study is the opposite of the conclusion of previous studies using the specialization paradigm e.

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It might be possible for weaker players to adopt the strategy of searching extensively and deeply. The explorations focus of super experts was superior as evidenced by the quality of the solution. Search strategies must be directed by knowledge; otherwise it will be difficult to identify the relevant problem space for the correct solution that needs to be investigated. This research is based on a doctoral dissertation of the first author who was supported by Oxford University Clarendon and ORS scholarships.

The preparation of this paper was supported by an ESRC postdoctoral fellowship to the first author. We would like to thank Francis H. Marriot for statistical advice, Richard Palliser for the help in choosing stimuli, Anders Ericsson, Philip Ackerman, Christopher Chabris, Margje van de Wiel, and Christian Schunn for their comments on the previous drafts of the paper, as well as all the chess players who took part in the experiments. Factor analysis FA with Varimax rotation was conducted for French, Sicilian, and Neutral problems separately as well as for all positions together on the parameters extracted from the protocols of players.

All FA produced two factors that can be broadly classified as factors of depth and breadth of search.

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Number of branches and immediate reinvestigations were frequently found on the depth factor, while reinvestigations and total moves were mostly connected with the breadth factor. These measures did not show a consistent connection to either of the two factors across different position types. Therefore, we used only mean and maximal depth of search as the indicators of depth of search and number of candidates and episodes as the indicators of breadth of search.

Volume 33 , Issue 6. The full text of this article hosted at iucr. If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account.

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If the address matches an existing account you will receive an email with instructions to retrieve your username. Cognitive Science Volume 33, Issue 6. Free Access. Tools Request permission Export citation Add to favorites Track citation. Share Give access Share full text access. Share full text access. Please review our Terms and Conditions of Use and check box below to share full-text version of article. Abstract Expert chess players, specialized in different openings, recalled positions and solved problems within and outside their area of specialization.

Introduction How do experts solve problems? The specialization paradigm The specialization paradigm offers a possible way of avoiding the confounds in the expert—novice paradigm. Overview of the study In our study, we wanted to overcome the methodological problems identified in previous research, which compared experts to novices by using the specialization paradigm , and in previous use of the specialization paradigm by using problems in both areas of specialization and neutral problems. Method 2.

Participants Players who specialize in playing either the French or Sicilian defense participated in the experiment. Figure 1 Open in figure viewer PowerPoint. Familiarity To identify players who play the Sicilian or French defense, but not both, we employed a familiarity questionnaire with 16 positions.

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Design and procedure 2. Analysis 2. Statistical analysis We transformed the percentage of correctly recalled pieces using the arcsin function to obtain approximately normal distributions. Results and discussion 3. Note: The numbers indicate the deviation from the best solution on a scale where 1 is the value of a pawn. Smaller values denote better solutions with 0 being the best solution. Figure 2 Open in figure viewer PowerPoint.

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    Specialization Effect and Its Influence on Memory and Problem Solving in Expert Chess Players

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