Week 11 Flashcards
This week’s 11 objectives
By the end of this week you should be able to:
discuss how decision-making paradigms relate to notions of expertise
describe different types of problems and different models of how problem-solving takes place
discuss the nature of expert skilled performance in a specific domain
explain the role of ‘chunking’, pattern abstraction templates and schemas in domain specific expertise
outline the possible role of deliberate, effortful practice play in the acquisition of competence and expertise.
1.
Discuss how decision-making paradigms relate to notions of expertise
1
What does problem solving require?
(1) there are two states of affairs;
(2) the agent is in one state and wants to be in the other state;
(3) it is not apparent to the agent how the gap between the two states is to be bridged; and (4) bridging the gap is a consciously guided multi-step process. The second topic is analogical problem solving . In our everyday lives, we constantly use past experience and knowledge to assist us in our current task. Often we detect (and make effective use of) analogies or similarities between a current problem and ones solved in the past. The third topic is expertise . Individuals possessing expertise have considerable specialist knowledge in some given area or domain.
PROBLEM SOLVING: There are three major aspects to problem solving:
- It is purposeful (i.e., goal-directed).
- It involves controlled processes and is not totally reliant on “automatic” processes.
- A problem exists when someone lacks the relevant knowledge to produce an immediate solution. Thus, a problem for most people (e.g., a mathematical calculation) may not be so for a professional mathematician.
Analogical problem solving
In our everyday lives, we constantly use past experience and knowledge to assist us in our current task. Often we detect (and make effective use of) analogies or similarities between a current problem and ones solved in the past.
Expertise
Individuals possessing expertise have considerable specialist knowledge in some given area or domain. There is much overlap between expertise and problem solving in that experts are very efficient at solving numerous problems in their area of expertise. However, there are also important differences. Knowledge is typically more important in research on expertise than research on problem solving. There is more focus on individual differences in expertise research than research on problem solving. Indeed, a central issue in expertise is to identify the main differences (e.g., in knowledge, in strategic processing) between experts and novices.
Well-defined problems
Are ones in which all aspects of the problem are clearly specified, including the initial state or situation, the range of possible moves or strategies and the goal or solution.
The goal is well specified because it is clear when it has been reached (e.g., the centre of a maze).
Chess is a well-defined (although very complex) problem – there is a standard initial state, the rules specify all legitimate rules and the goal is to achieve checkmate.
Optimal strategy for solution.
Psychologists use these.
Person with brain damage found it very hard to work out preliminary plans to impose some structure on such problems and so could not solve them
Ill-defined problems
Ill-defined problems are underspecified. Suppose you set yourself the goal of becoming happier. There are endless strategies you could adopt and it is very hard to know ahead of time which would be most effective. Since happiness varies over time and is hard to define, how are you going to decide whether you have solved the problem of becoming happier?
Knowledge-rich problems
(e.g., chess problems) can only be solved by those having much relevant specific knowledge.
Knowledge-lean
problems do not require such knowledge because most of the information needed to solve the problem is contained in the initial problem statement. Most traditional research on problem solving involved knowledge-lean problems because such problems minimise individual differences in relevant knowledge.
Monty Hall problem:
In two out of three possible car– goat arrangements, the contestant would win by switching; therefore she should switch.
Why do people perform so poorly on this problem?
1. we typically use a heuristic or rule of thumb known as the uniformity fallacy. This fallacy involves assuming all available options are equally likely whether they are or not.
- the problem places substantial demands on the central executive (an attention-like component of working memory. Participants were much less likely to solve the Monty Hall problem if they performed a demanding task involving the central executive task at the same time (8% vs. 22%.
- Most people mistakenly believe the host’s actions are random . Burns and Wieth (2004) made the causal structure of the problem clearer. There are three boxers, one of whom was so good he was certain to win any bout. You select one boxer and then the other two boxers fight each other. The winner of this bout then fights the boxer you selected initially. You win if you choose the winner of this second bout.
Uniformity fallacy
This fallacy involves assuming all available options are equally likely whether they are or not.
Early research on problem solving was dominated by the Gestaltists, German psychologists flourishing between the 1920s and 1940s.
They distinguished between reproductive and productive thinking.
Reproductive thinking
Involves the systematic reuse of previous experiences
Productive thinking
involves a novel restructuring of the problem and is more complex.
Productive thinking involves insight Gestalt.
Insight involves a sudden restructuring of a problem and is sometimes accompanied by the “ah-ha experience”.
Insight is
“any sudden comprehension, realisation, or problem solution that involves a reorganisation of the elements of a person’s mental representation of a stimulus, situation, or event to yield a nonobvious or non-dominant interpretation”
Rapid solve a problem with insight if you are given clues about what you already know.
There has been controversy as to whether insight is a special process or whether it involves the same processes as other thinking tasks (the “business-as-usual” view).
Metcalfe and Wiebe (1987) recorded participants’ feelings of “warmth” (closeness to solution) during insight and non-insight problems. Warmth increased progressively during non-insight problems (as expected if they involve a sequence of processes). With insight problems, in contrast, the warmth ratings remained at the same low level until suddenly increasing dramatically just before the solution was reached.
Occurs unexpectedly and suddenly.
Differences in brain activity between insight and non-insight trials
Centred in the right hemisphere. More specifically, the anterior superior temporal
Why is the right hemisphere more associated with insight than the left hemisphere?
Integration of weakly active and distant associations occurs mostly in the right hemisphere. Such processing activities are very relevant for producing insight. In contrast, strong activation of closely connected associations occurs mostly in the left hemisphere.
Note the neuroscience evidence discussed here is correlational and so does not show that any given brain area is necessary for insightful problem solving.
How are hints useful?
They increase the number of solutions produced on insight problems. However, what is surprising is that even subtle hints are useful.
Hints can be effective without conscious awareness of their task relevance.
Incubation
A stage of problem solving in which the problem is put to one side for some time; it is claimed to facilitate problem solving.
The subconscious mind continues to work towards a solution during incubation and so incubation facilitates problem solution.
A meta analysis on incubation found:
- Incubation effects (generally fairly small) were reported in 73% of the studies.
Incubation effects were stronger with creative problems having multiple solutions than linguistic and verbal problems having a single solution.
Incubation often widens the search for knowledge, which may be more useful with multiple-solution problems.
The effects were larger when there was a fairly long preparation time prior to incubation. This may have occurred because an impasse or block in thinking is more likely to develop when preparation time is long.
Why is incubation beneficial?
Control information relating to the strategies tried by the problem solver is forgotten during incubation. This forgetting makes it easier for problem solvers to adopt a new approach after the incubation period.
Forgetting misleading information is important.
Participants solved insight problems in the presence or absence of misleading clues. One group worked continuously while the other group had a two-minute incubation period. There was a beneficial effect of incubation only when the break allowed misleading information to be forgotten.
Representational change theory
We often encounter a block or impasse when solving a problem because we have represented it wrongly.
According to his representational change theory, we typically need to change the problem representation for insight to occur. This can happen in three ways:
1 Constraint relaxation : inhibitions on what is regarded as permissible are removed.
2. Re-encoding : some aspect of the problem representation is reinterpreted.
3. Elaboration : new problem information is added to the representation.
What is new about this theory is the assumption that a search process may be necessary even after an impasse has been overcome by insight.
Solution hints are most useful when individuals have just reached a block or impasse. At that point, they have formed a problem representation (which is not the case earlier). However, they have not become excessively fixated on it (as happens after reaching an impasse). As predicted, hints before or after an impasse improved performance less than those given at the point of impasse.
Limitations:
1. we often cannot predict when (or why) a problem’s
representation will change.
2 . De-emphasised important individual differences in problem-solving skills (e.g., working memory capacity).
- the theory mistakenly implies that constraint relaxation is typically sufficient to solve insight problems. However, we have seen that this is not the case with respect to the nine-dot problem.
Flow chart of insight problem solving.
Initially, a problem representation is established using prior knowledge and perceptual processes. The problem representation is searched by heuristics (rules of thumb). If this proves unsuccessful, an impasse is encountered. This leads to a change in the problem representation and this new representation is also searched by heuristics. This process is continued until a solution is found or the problem is abandoned.
Functional fixedness - Past experience:
Gestaltists
Functional fixedness occurs when we mistakenly assume that any given object has only a limited number of uses.
Past experience generally increases our ability to solve problems.
Gestaltists argued that this is not always the case.
Indeed, numerous failures on insight problems occur because we are misled by our past experience.
Negative effects of past experience are shown clearly in the phenomenon of functional fixedness.
How can we overcome the negative effects of functional fixedness?
Two steps were involved:
- Notice an infrequently noticed or new feature.
- Form a solution based on that obscure feature.
How can we overcome the negative effects of functional fixedness?
In almost every case, two steps were involved: TACKS 1. Notice an infrequently noticed or new feature.
2.Form a solution based on that obscure feature.
Mental set
The tendency to use a familiar problem-solving strategy that has proved successful in the past even when it is not appropriate.
Mental set involves continuing to use a previously successful problem-solving strategy even when it is inappropriate or sub-optimal.
Mental set is often useful in spite of its drawbacks – it allows successive problems of the same type to be solved rapidly and with few processing demands.
Chess players: Their eye movements revealed they were still looking at features of the chessboard position related to the familiar solution. Thus, their direction of attention remained partly under the control of processes producing the initial familiar solution.
How can we minimise the effects of the mental set?
Human Problem Solving . Their central insight was that the strategies we use when tackling complex problems take account of our limited ability to process and store information.
Limited short term capacity - complex information processing is one step at a time.
problem space for each problem. .
A problem space
Consists of the initial state of the problem, the goal state, all possible mental operators (e.g., moves) that can be applied to any state to change it into a different state, and all the intermediate problem states.
How do we solve well-defined problems with our limited processing capacity?
Newell and Simon (1972), we rely heavily on heuristics . Heuristics are rules of thumb that are easy to use and often produce reasonably accurate answers. Heuristics can be contrasted with algorithms , which are generally complex methods or procedures guaranteed to lead to problem solution.
Algorithm
A computational procedure providing a specified set of steps to problem solution.
- Can be contrasted with heuristics.
Means– ends analysis
A heuristic method for solving problems based on creating a sub-goal to reduce the difference between the current state and the goal state.
According to Newell and Simon, the most important heuristic method is means– ends analysis.
Useful and helps with problem solving.
Means-ends analysis, the problem solver begins by envisioning the end, or ultimate goal, and then determines the best strategy for attaining the goal in his current situation. If, for example, one wished to drive from New York to Boston in the minimum time possible,
Use of means– ends analysis requires knowledge of goal location, and so only the goal-information group could use that heuristic. However, the problem was designed so means– ends analysis would not be useful – every correct move involved turning away from the goal.
Hill climbing heuristic
Involves changing the present state within the problem into one closer to the goal. It is simpler than means– ends analysis and is mostly used when the problem solver has no clear understanding of the problem structure. The hill-climbing heuristic involves a focus on short-term goals , and so often does not lead to problem solution.
A simple heuristic used by problem solvers in which they focus on making moves that will apparently put them closer to the goal.
The hill-climbing heuristic involves a focus on short-term goals , and so often does not lead to problem solution. Someone using this heuristic is like a climber who tries to reach the highest mountain peak in the area by using the strategy of always moving upwards. This may work, but it is likely that the climber will find himself/herself trapped on a hill separated by several valleys from the highest peak.
It is simpler than means– ends analysis and is mostly used when the problem solver has no clear understanding of the problem structure.
Progress monitoring
MacGregor et al.- individuals engaged in problem solving use a heuristic known as progress monitoring . - involves assessing their rate of progress towards the goal.
If progress is too slow to solve the problem within the maximum number of moves allowed, people adopt a different strategy.
- A heuristic or rule of thumb in which slow progress towards problem solution triggers a change of strategy.
Problem may be abandoned.
Planning
People with damage to the prefrontal cortex find it harder to plan ahead.
It is generally assumed most people presented with complex problems will engage in some preliminary planning.
Left dorsolateral prefrontal cortex is involved in initial planning.
Patients with right prefrontal damage had impaired planning in part because they made premature commitments to various decisions.
Functional fixedness
Is failing to solve problems, because one assumes from past experience that a given object has only a limited number of uses.
How much Explicit Planning do most people use on complex problems?
Most problem solvers engage in only a modest amount of planning because of limited short-term memory capacity.
Problem-solving processes
Occur below the level of conscious awareness
Most problem solvers engage in
Little planning.
The evidence suggests problem solvers engage in deliberate preplanning some of the time. However, some problem-solving processes occur below the level of conscious awareness and many people often make little use of preplanning.
Cognitive miser
Someone who is economical with their time and effort when performing a thinking task.
Cognitive miserliness
Many theorists have proposed dual-process theories to account for the strategies used by individuals performing cognitive tasks such as judgement and reasoning.
Most dual-process theorists argue that many people are cognitive misers .
A cognitive miser is someone who is typically economical with his/her time and effort on tasks requiring thinking.
Low scorers on the Cognitive Reflection Test perform relatively poorly on a wide range of judgement and reasoning tasks
Low score are cognitive misers.
Cognitive Reflection Test correlates positively with intelligence.
There is overlap between the notion of cognitive miser and Newell and Simon’s (1972) focus on problem solvers’ use of heuristics or rules of thumb.
In both cases, individuals resort to simple (and sometimes inaccurate) strategies. However, there is a difference. Newell and Simon assumed we use heuristics because we are forced to by our limited processing capacity. In contrast, cognitive misers use heuristics because they are reluctant to engage in effortful processing rather than because they cannot.
ANALOGICAL PROBLEM SOLVING Analogical problem solving involves solving problems by using analogies.
An analogy is “a comparison between two objects, or systems of objects, that highlights respects in which they are thought to be similar”
Analogies are useful as they
Reduced uncertainty and facilitated rapid, approximate problem solving.
Three main types of similarity between problems:
- Superficial similarity : Solution-irrelevant details (e.g., specific objects) are common to the two problems.
- Structural similarity : Causal relations among some of the main components are shared by both problems.
- Procedural similarity : Procedures for turning the solution principle into concrete operations are common to both problems.
Findings: analogy detection If you were given a problem, would you use a relevant analogy to solve it?
Some findings are discouraging. Gick and Holyoak A problem was used in which a patient with a malignant stomach tumour can only be saved by a special kind of ray. However, a ray strong enough to destroy the tumour will also destroy the healthy tissue, whereas a ray that does not harm healthy tissue will be too weak to destroy the tumour. Only 10% of participants solved this problem when presented on its own.
Why did Gick and Holyoak’s (1980) participants fail to make spontaneous use of the relevant, memorised story?
The lack of superficial similarities between the story and the problem was important. When the story was superficially similar to the problem (it involved a surgeon using rays on a cancer), 88% of participants spontaneously recalled it when given the radiation problem.
The production paradigm
In contrast, people in everyday life generally produce their own analogies: Blanchette and Dunbar (2000) confirmed previous findings showing that participants given the reception paradigm often selected analogies based on superficial similarities. However, those given the production paradigm mostly produced analogies sharing structural features with the current problem.
Analogy
A comparison between two objects (or between a current and previous problem) that emphasises similarities between them.
Much of the time, we cope successfully with novel situations by relating them to situations we have encountered previously.
Newell and Simon assumed we use heuristics because we are forced to by our limited processing capacity.
In contrast, cognitive misers use heuristics because they are reluctant to engage in effortful processing rather than because they cannot. KEY TERM Analogy A comparison between two objects (or between a current and previous problem) that emphasises similarities between them.
Analogies were useful –
they reduced uncertainty and facilitated rapid, approximate problem solving.
Sequential processing stages Four-term analogy problems involve three sequential processing stages:
- Encoding of the first pair of words based on the relationship between them;
- Mapping (a connection is formed between the first words of each pair and an inference drawn as to the fourth word);
- Response (decision concerning the correctness of the fourth word).
What processes are involved in analogical problem solving or reasoning?
Analogies can be detected unconsciously.
The working memory is involved in?
Analytical problem solving.
Participants received verbal analogies (e.g., BLACK:WHITE::NOISY:QUIET) and decided whether they were true or false. They also received picture-based analogies involving cartoon characters. These tasks were performed on their own or while participants performed an additional task imposing demands on one component of the working memory system. What did Morrison et al. (2001) find?
First, performance on verbal and pictorial analogies was impaired when the additional task involved the central executive (an attention-like system). Thus, solving analogies requires the limited capacity of the central executive. Second, performance on verbal analogies was impaired when the additional task involved the phonological loop (used for verbal rehearsal). This happened because both tasks involved verbal processing. Third, performance on pictorial analogies suffered when the additional task involved the visuo-spatial sketchpad (used for basic visual and spatial processing).
The Raven’s test is used as?
a measure of fluid intelligence (non-verbal intelligence applied to novel problems). In addition, however, it is a test involving geometrical analogies (the correct answer is chosen based on analogical reasoning). As such, it is theoretically important to determine dimensions of individual differences influencing test performance.
Several studies have assessed the relationship between Raven’s Advanced Progressive Matrices and working memory capacity (the ability to process and store information at the same time
The overall correlation between those two measures was +0.50.
This relationship is due mainly to Raven’s items involving new rule combinations rather than the same rules as previous items. Individuals high in working memory capacity may have superior Raven’s performance because they have superior attentional or executive control than low scorers or because they have greater attentional capacity.
Expertise
The high level of knowledge and performance in a given domain that an expert has achieved through years of systematic practice.
The end point of such long-term learning is the development of expertise.
The end point of such long-term learning is the development of expertise . Expertise involves a very high level of thinking and performance in a given domain (e.g., chess) as a result of many years of practice.
studies on expertise have typically used “knowledge-rich” problems r
Knowledge rich problems
Studies on expertise have used knowledge rich problems requiring much knowledge beyond that contained in the problem.
Chess masters recalled the positions much more accurately than less expert players (91% vs. 43%, respectively). Why?
This is due to differences in stored chess positions rather than in memory ability – there were no group differences in remembering random board positions.
What is a template?
As applied to chess, an abstract schematic structure consisting of a mixture of fixed and variable information about chess pieces and positions.
It is an abstract, schematic structure more general than an actual board position.
Each template consists of a core (fixed information) plus slots (containing variable information about pieces and locations).
Each template typically stores information relating to about ten pieces although it can be larger than that. Their possession of slots makes templates adaptable and flexible.
Template theory predictions are:
- It predicts that chess positions are stored in three templates, some of which are relatively large.
- It is assumed that outstanding chess players owe their excellence mostly to their superior template-based knowledge of chess rather than their use of slow, strategy-based processes. This template-based knowledge can be accessed rapidly and allows expert players to narrow down the possible moves they need to consider. If these assumptions are correct, the performance of outstanding players should remain high.
- It is assumed that expert chess players store away the precise board locations of pieces after studying a board position. In addition, it is assumed that chess pieces close together are most likely to be found in the same template
the have better recall than random players
How do the strategies used by medical experts differ from those of unskilled ones? Theorists differ in their answers. However, the distinction between explicit and implicit reasoning is central to many theoretical viewpoints.
Explicit and implicit reasoning.
Explicit reasoning is slow, deliberate and associated with conscious awareness. In contrast,
Implicit reasoning is fast, automatic, and not associated with conscious awareness. The crucial assumption is that medical experts engage mainly in implicit reasoning while novices rely mostly on explicit reasoning. Note that dual process theories of judgement and reasoning involve rather similar distinctions between deliberate, explicit processes and rapid, implicit ones.
When an expert doctor fixates on the cancer almost immediately, what does this mean?
It suggests they used holistic or global processes. In contrast, the least expert doctors relied on a slower processing strategy.
Experts out perform non experts because of their?
Superior knowledge.
Medical groups should have produced more accurate diagnoses when given verbal descriptions as well as case photographs.
That was, indeed, the case with the least expert group. In striking contrast, the more expert groups (including dermatologists) performed better when not given the verbal descriptions. Experts used a rapid visual strategy and the verbal descriptions interfered with their ability to use that strategy effectively.
Experts can make accurate diagnoses without?
Relying on slow, analytic processes. An over simplification.
Analytic thinking enhanced the diagnostic performance of experts with complex cases but not simple ones. In contrast, non-experts derived no benefit from engaging in analytic thinking.
Plasticity Changes
Changes in the brain structure and function dependent on experience that affect behaviour.
What are the differences between chess and medical expertise?
Knowledge is stored may differ between the two kinds of expertise. Much of the knowledge possessed by chess experts consists of fairly abstract templates.
In contrast, the knowledge possessed by medical experts is probably less abstract and more visual in nature.
Second, chess experts have to relate a current chess position to their stored knowledge and then consider their subsequent moves and those of their opponent.
In contrast, the task of medical experts is more narrowly focused on relating information about a specific case to their stored knowledge.
Plasticity
“changes in structure and function of the brain that affect behaviour and that are related to experience or training”.
It is likely that structural changes resulting from plasticity facilitate further learning and the enhancement of expertise.
Hippocampus (long term memory) is of main importance for?
Memorising many details such as the streets when your profession is a cab driver.
Does acquisition of The Knowledge have a direct effect on the hippocampus?
Experienced London cab drivers have a greater volume of grey matter in the posterior hippocampus than novice drivers or other control groups, and older full-time cab drivers have greater grey matter volume in this area than those of the same age who have retired.
Disadvantage:
Taxi drivers performed poorly on tasks requiring them to learn and remember new word– word or object– place associations.
These drivers had a smaller volume of grey matter than other people in the anterior hippocampus, which is important for processing novel stimuli and encoding information. The very extensive involvement of the hippocampus in learning The Knowledge may impair the ability to acquire new information.
Expertise can be developed through deliberate practice.
Deliberate practice has four aspects:
- The task is at an appropriate level of difficulty (not too easy or hard).
- The learner is given informative feedback about his/her performance.
- The learner has adequate chances to repeat the task.
- The learner has the opportunity to correct his/her errors.
Deliberate practice is a form of practice that?
Involves the learner being provided with informative feedback and having the chance to correct his/her errors.
What happens as a result of prolonged deliberate practice?
Experts can reduce the negative effects of having limited working memory capacity.
They put forward the notion of long-term working memory .
Long-term working memory
Used by experts to store relevant information rapidly in long-term memory and to access it through retrieval cues in Working Memory
An example to show the nature of long-term working memory. Novice chess player try to learn the positions of chess pieces on a board.
The novice must rely very largely on working memory (a system of limited capacity that processes and stores information briefly. In contrast, the expert player can use his/her huge relevant knowledge to store much of the information directly in long-term memory and thus enhance his/her recall of the board positions. In other words, the expert uses long-term working memory but the novice does not.
There is reasonable support for the notion that experts use long-term working memory to enhance their ability to remember task-relevant information.
A student received extensive practice (one hour a day for two years) on the digit-span task in which random digits are recalled immediately in the correct order. His initial digit span was seven digits, but this increased dramatically to 80 digits at the end of practice. This is ten times the average performance level!
How did the student increase the amount of digits?
He started by using his great knowledge of running times. For example, if the first few digits were “3594” he would note this was Bannister’s world-record time for the mile and so store these four digits as a single unit or chunk. After that, he organised chunks into a hierarchical retrieval structure. Thus, SF made very effective use of long-term working memory.
What are the neuroimaging findings in studies of experts performing tasks involving use of working memory.?
There were two main findings.
- the experts showed decreased activation in prefrontal and parietal areas as chunks were created and retrieved.
- experts showed increased activation in medial temporal regions strongly associated with long-term memory as knowledge structures were created and retrieved. This pattern of findings differed from that of non-experts and suggests only experts used long-term working memory extensively.
Some individuals who have developed a high level of expertise decide to abandon their area of expertise. Why does this happen?
According to Ericsson the main reason is a reduction in the amount of deliberate practice. This causes a reduction in performance level, which in turn leads to drop out. Evidence supportive of this proposed sequence was reported in a study on elite young chess players who had dropped out of competitive chess.
The existence of a positive correlation between deliberate practice and expert performances does not establish causality. Why?
The amount of time any individual devotes to deliberate practice is typically not under experimental control. Individuals having high levels of innate talent and/or encountering early success are generally the ones most motivated to engage in substantial amounts of deliberate practice. Thus, correlations between amount of practice and skill level probably depend on two factors: 1. deliberate practice enhances skill level; 2. early success leads to greater subsequent practice.
Campitelli and Gobet identified three predictions from deliberate practice theory:
- All individuals who engage in massive deliberate practice should achieve very high skill levels.
- The variability across individuals in the number of hours required to achieve high expertise should be relatively small.
- Everyone’s skill level should benefit comparably from any given amount of deliberate practice.
Most research on problem solving focuses on?
Problems requiring no special knowledge.
Research on expertise requires?
Considerable background knowledge.
Analogical problem solving focuses on ?
The use of previous knowledge and experience on a current problem.
Expertise research is concerned with?
What differentiates experts from novices in a given area.
• Gestalt approach: insight and role of experience.
There is behavioural, neuroimaging and verbal report evidence for the existence of insight. It can be facilitated by subtle hints. Incubation often benefits problem solving because misleading information or ineffective strategies are forgotten. There is evidence supporting the assumptions of representational change theory that solving insight problems often requires constraint relaxation and/or re-encoding of the problem representation. However, constraint relaxation is often insufficient on its own. The phenomena of functional fixedness and mental set show past experience can have negative effects on problem solving. Functional fixedness can be reduced by focusing on obscure features of an object and basing solutions on those features.
Problem-solving strategies.
Problem solvers make extensive use of heuristics or rules of thumb such as hill climbing, means– ends analysis, and progress monitoring. Much problem solving involves successive stages of problem representation, planning and plan execution. Evidence from brain-damaged patients and neuroimaging indicates that the prefrontal cortex (especially the dorsolateral prefrontal cortex) is heavily involved in planning and problem solving generally. Many problem solvers rely relatively little on deliberate pre-planning but make use of non-conscious learning processes. Cognitive misers fail to solve problems they have the ability to solve.
Analogical problem solving.
Analogical problem solving depends on three kinds of similarity: superficial, structural and procedural. Failures to use analogies often occur through failures of memory retrieval. Such failures can be reduced if problem solvers identify the underlying structure of the current problem. Four-term analogy problems have three sequential stages of encoding, mapping or inference, and response. Several brain regions (especially within the prefrontal cortex) are involved in analogical reasoning. Individuals high in working memory capacity perform better than those low in capacity on analogical reasoning because they have great attentional control and attentional capacity.
Chess-playing expertise.
Expertise is typically assessed by using knowledge-rich problems. Expert chess players differ from non-expert ones in possessing far more templates containing knowledge of chess positions. These templates permit expert players to identify good moves rapidly. However, the precise information contained in templates remains unclear. In addition, the template approach deemphasises the importance to chess performance of slow search processes and complex strategies.
Medical expertise.
Medical experts (e.g., radiologists) often rely more than non-experts on fast, automatic processes in diagnosis. This is revealed by eye-movement data indicating that experts rapidly fixate relevant information and ignore task-irrelevant information. Slow, analytic processes can enhance diagnostic performance but the precise circumstances in which this is the case remain to be determined. Medical expertise involves more visual and less abstract knowledge than chess expertise. It is also more narrowly focused than chess expertise in that the primary goal is diagnosis rather than “diagnosis” of the current position plus complex planning of future moves.
Brain plasticity.
There is accumulating evidence that there are differences in brain structure between experts and non-experts. Training studies (especially in music) have shown these changes in brain structure are often caused by experience and reflect brain plasticity. The structural changes associated with brain plasticity probably provide experts with an additional benefit compared to non- experts.
Deliberate practice.
According to Ericsson, the development of expertise depends on deliberate practice involving informative feedback and the opportunity to correct errors. Deliberate practice is necessary (but not sufficient) for the development of expertise. The importance of innate talent is suggested by the variability in the amount of practice required to achieve high expertise and individual differences in the benefits of a given amount of practice. Individual differences in innate ability are especially important in broad domains (e.g., career success). It may be mainly individuals of high innate ability who are motivated to devote thousands of hours to deliberate practice.
Bowden et al. (2005) presented participants with three cue words (e.g., “fence”, “card” and “master”), and participants would have to think of a word (e.g., “post”). A problem such as this is referred to as:
Remote associate’s test.
Duncker’s (1945) study on human problem solving demonstrated the notion of:
Mental set
According to Ohlsson (1992), changing the representation of a problem, so that restrictions on what is regarded as possible are removed, is termed:
Constraint relaxation
Failing to solve problems, because one assumes from past experience that a given object has only a limited number of uses, has been called:
Functional fixedness
Newell and Simon (1972) included the initial stage of the problem, the goal state, all of the possible moves and intermediate states of the problem, in what they deemed the:
Problem space
According to Newell and Simon (1972), an important heuristic that involves changing the present state within the problem to one closer to the goal is called:
Hill climbing
Which of the following is a criticism of Newell and Simon’s (1972) computational model of problem solving?
It is not well suited to multiple-move problems requiring serial processing
According to Chen (2002), a current problem may be similar to a previous one because causal relations among some of the main components are shared by both problems. This is termed:
Structural similarity
In a study of expertise in chess players, what term has been used to describe a schematic structure that is more general than an actual board position?
Template
Routine expertise
- Using acquired knowledge to solve familiar problems efficiently. For example, by using templates, schemas or scripts.
Adaptive expertise
Using acquired knowledge to develop strategies for dealing with novel problems. For example by extracting or matching patterns.
Routine expertise is?
A lower level order of thinking than adaptive expertise, as the situation is generally known and can be seen as a kind of competence. True expertise in a field comes when the expert is able to adapt to new situations and apply their domain specific knowledge to them.
Routine expertise is?
A lower level order of thinking than adaptive expertise, as the situation is generally known and can be seen as a kind of competence. True expertise in a field comes when the expert is able to adapt to new situations and apply their domain specific knowledge to them.
Expertise and decision-making
Going back to Kahneman and his System 1 and System 2 ways of thinking, experts have plenty of knowledge regarding System 2, and analyse situations within this system very well. They have very well-programmed ‘shortcuts’—so they can use their System 1 to make good decisions with little mental effort. It appears that experts have different knowledge representations from non-experts. It may be true that they use automated System 1 decision-making during expert performance, but communicate their expertise in terms of System 2 explicit rules.
Chunking
Chunking is the remembering of a chunk or package of information (a unit of meaning) by a pattern fragment key. For example, the number 26 might be a cue or key for a whole chunk of remembered information about a pattern of play in a sport.
You may remember from Week 5 that your short term memory holds 7 +/-2 chunks of information at a time (Miller, 1956). Experts appear to be able to expand their working memory by having fast information retrieval and manipulation by chunking. The unitary store model of memory—where short-term working memory is made up of activated long-term memory—might be a mechanism for expanding working memory.
Deliberate effortful practice
Deliberate effortful practice involves trying to build up patterns of information that will give us access to adaptive expertise. We extract patterns that are successful in terms of leading to particular outcomes. Generally, a familiarity with a situation is necessary to extract the relevant chunks (see the chunking information above).
We choose tasks that are difficult in the domain we want to learn about and we practise those things and get feedback on the task. Consider the following:
Task is at appropriate level of difficulty (not too easy, not too hard).
Learner is given informative feedback about performance.
Learner has adequate chance to repeat task.
Learner has opportunity to correct errors.
Repetition allows for the extraction of patterns of task relevant information (chunks).
Example of effortful practice
Think of a child learning to kick a ball. The child can be given detailed instructions as to how to kick the ball and the physical mechanisms involved. However, in order to kick the ball on target, the child must practise the task. Feedback is given via how successful the kick is in connecting with the target. The child adapts their approach to the task based on the opportunity to correct errors based on feedback. Therefore, deliberate effortful practice is difficult—particularly if you are a cognitive miser.
