Eureka effect

From Wikipedia, the free encyclopedia

A 16th century woodcut of Archimedes' eureka moment

 

The eureka effect (also known as the Aha! moment or eureka moment) refers to the common human experience of suddenly understanding a previously incomprehensible problem or concept. Some research describes the Aha! effect (also known as insight or epiphany) as a memory advantage, but conflicting results exist as to where exactly it occurs in the brain, and it is difficult to predict under what circumstances one can predict an Aha! moment

Insight is a psychological term that attempts to describe the process in problem solving when a previously unsolvable puzzle becomes suddenly clear and obvious. Often this transition from not understanding to spontaneous comprehension is accompanied by an exclamation of joy or satisfaction, an Aha! moment. A person utilizing insight to solve a problem is able to give accurate, discrete, all-or-nothing type responses, whereas individuals not using the insight process are more likely to produce partial, incomplete responses.

A recent theoretical account of the Aha! moment started with four defining attributes of this experience. First, the Aha! moment appears suddenly; second, the solution to a problem can be processed smoothly, or fluently; third, the Aha! moment elicits positive affect; fourth, a person experiencing the Aha! moment is convinced that a solution is true. These four attributes are not separate but can be combined because the experience of processing fluency, especially when it occurs surprisingly (for example, because it is sudden), elicits both positive affect and judged truth.

Insight can be conceptualized as a two phase process. The first phase of an Aha! experience requires the problem solver to come upon an impasse, where they become stuck and even though they may seemingly have explored all the possibilities, are still unable to retrieve or generate a solution. The second phase occurs suddenly and unexpectedly. After a break in mental fixation or re-evaluating the problem, the answer is retrieved. Some research suggest that insight problems are difficult to solve because of our mental fixation on the inappropriate aspects of the problem content. In order to solve insight problems, one must "think outside the box". It is this elaborate rehearsal that may cause people to have better memory for Aha! moments. Insight is believed to occur with a break in mental fixation, allowing the solution to appear transparent and obvious.

History and etymology

The effect is named from a story about the ancient Greek polymath Archimedes. In the story, Archimedes was asked (c. 250 BC) by the local king to determine whether a crown was pure gold. During a subsequent trip to a public bath, Archimedes noted that water was displaced when his body sank into the bath, and particularly that the volume of water displaced equaled the volume of his body immersed in the water. Having discovered how to measure the volume of an irregular object, and conceiving of a method to solve the king's problem, Archimedes allegedly leaped out and ran home naked, shouting "eureka" (I have found it). This story is now thought to be fictional, because it was first mentioned by the Roman writer Vitruvius nearly 200 years after the date of the alleged event, and because the method described by Vitruvius would not have worked. However, Archimedes certainly did important, original work in hydrostatics, notably in his On Floating Bodies.

Research

Initial research

Research on the Aha! moment dates back more than 100 years, to the Gestalt psychologists' first experiments on chimpanzee cognition. In his 1921 book, Wolfgang Köhler described the first instance of insightful thinking in animals: One of his chimpanzees, Sultan, was presented with the task of reaching a banana that had been strung up high on the ceiling so that it was impossible to reach by jumping. After several failed attempts to reach the banana, Sultan sulked in the corner for a while, then suddenly jumped up and stacked a few boxes upon each other, climbed them and thus was able to grab the banana. This observation was interpreted as insightful thinking. Köhler's work was continued by Karl Duncker and Max Wertheimer. 

The Eureka effect was later also described by Pamela Auble, Jeffrey Franks and Salvatore Soraci in 1979. The subject would be presented with an initially confusing sentence such as "The haystack was important because the cloth ripped". After a certain period of time of non-comprehension by the reader, the cue word (parachute) would be presented, the reader could comprehend the sentence, and this resulted in better recall on memory tests. Subjects spend a considerable amount of time attempting to solve the problem, and initially it was hypothesized that elaboration towards comprehension may play a role in increased recall. There was no evidence that elaboration had any effect for recall. It was found that both "easy" and "hard" sentences that resulted in an Aha! effect had significantly better recall rates than sentences that subjects were able to comprehend immediately. In fact equal recall rates were obtained for both "easy" and "hard" sentences which were initially non-comprehensible. It seems to be this non-comprehension to comprehension which results in better recall. The essence of the aha feeling underling insight problem solving was systemically empirically investigated by Danek et al. and Shen and his colleagues.

How people solve insight problems

Currently there are two theories for how people arrive at the solution for insight problems. The first is the progress monitoring theory. The person will analyze the distance from their current state to the goal state. Once a person realizes that they cannot solve the problem while on their current path, they will seek alternative solutions. In insight problems this usually occurs late in the puzzle. The second way that people attempt to solve these puzzles is the representational change theory. The problem solver initially has a low probability for success because they use inappropriate knowledge as they set unnecessary constraints on the problem. Once the person relaxes his or her constraints, they can bring previously unavailable knowledge into working memory to solve the problem. The person also utilizes chunk decomposition, where he or she will separate meaningful chunks into their component pieces. Both constraint relaxation and chunk decomposition allow for a change in representation, that is, a change in the distribution of activation across working memory, at which point they may exclaim, "Aha!" Currently both theories have support, with the progress monitoring theory being more suited to multiple step problems, and the representational change theory more suited to single step problems.

The Eureka effect on memory occurs only when there is an initial confusion. When subjects were presented with a clue word before the confusing sentence was presented, there was no effect on recall. If the clue was provided after the sentence was presented, an increase in recall occurred.

Memory

It had been determined that recall is greater for items that were generated by the subject versus if the subject was presented with the stimuli. There seems to be a memory advantage for instances where people are able to produce an answer themselves, recall was higher when Aha! reactions occurred. They tested sentences that were initially hard to understand, but when presented with a cued word, the comprehension became more apparent. Other evidence was found indicating that effort in processing visual stimuli was recalled more frequently than the stimuli that were simply presented. This study was done using connect-the-dots or verbal instruction to produce either a nonsense or real image. It is believed that effort made to comprehend something when encoding induces activation of alternative cues that later participate in recall.

Cerebral lateralization

Functional magnetic resonance imaging and electroencephalogram studies have found that problem solving requiring insight involves increased activity in the right cerebral hemisphere as compared with problem solving not requiring insight. In particular, increased activity was found in the right hemisphere anterior superior temporal gyrus.

Sleep

Some unconscious processing may take place while a person is asleep, and there are several cases of scientific discoveries coming to people in their dreams. Friedrich August Kekulé von Stradonitz said that the ring structure of benzene came to him in a dream where a snake was eating its own tail. Studies have shown increased performance at insight problems if the subjects slept during a break between receiving the problem and solving it. Sleep may function to restructure problems, and allow new insights to be reached. Henri Poincaré stated that he valued sleep as a time for "unconscious thought" that helped him break through problems.

Other theories

Professor Stellan Ohlsson believes that at the beginning of the problem-solving process, some salient features of the problem are incorporated into a mental representation of the problem. In the first step of solving the problem, it is considered in the light of previous experience. Eventually, an impasse is reached, where all approaches to the problem have failed, and the person becomes frustrated. Ohlsson believes that this impasse drives unconscious processes which change the mental representation of a problem, and cause novel solutions to occur.

General procedure for conducting ERP and EEG studies

When studying insight, or the Aha! effect, ERP or EEG general methods are used. Initially a baseline measurement is taken, which generally asks the subject to simply remember an answer to a question. Following this, subjects are asked to focus on the screen while a logogriph is shown, and then they are given time with a blank screen to get the answer, once they do they are required to press a key. After which the answer appears on the screen. The subjects are then asked to press one key to indicate that they thought of the correct answer and another to indicate if they got the answer wrong, finally, not to press a key at all if they were unsure or did not know the answer.

Evidence in EEG studies

Resting-state neural activity has a standing influence on cognitive strategies used when solving problems, particularly in the case of deriving solutions by methodical search or by sudden insight.^[3] The two cognitive strategies used involve both search and analysis of current state of a problem, to the goal state of that problem, while insight problems are a sudden awareness of the solution to a problem.

Subjects studied were first recorded on the base-line resting state of thinking. After being tested using the method described in the General Procedure for Conducting ERP and EEG Studies, the ratio of insight versus non-insight solution were made to determine whether an individual is classified as a high insight (HI) or a low insight (LI) individual. Discriminating between HI and LI individuals were important as both groups use different cognitive strategies to solve anagram problems used in this study. Right hemisphere activation is believed to be involved in Aha! effects, so it comes as no surprise that HI individuals would show greater activation in the right hemisphere than the left hemisphere when compared to the LI individuals. Evidence was found to support this idea, there was greater activation in HI subjects at the right dorsal-frontal (low-alpha band), right inferior-frontal (beta and gamma bands) and the right parietal (gamma band) areas. As for LI subjects, left inferior-frontal and left anterior-temporal areas were active (low-alpha band).

There were also differences in attention between individuals of HI and LI. It has been suggested that individuals who are highly creative exhibit diffuse attention, thus allowing them a greater range of environmental stimuli. It was found that individuals who displayed HI would have less resting state occipital alpha-band activity, meaning there would be less inhibition of the visual system. Individuals that were less creative were found to focus their attention, thus causing them to sample less of their environment. Although, LI individuals were shown to have more occipital beta activity, consistent with heightened focused attention.

Evidence in ERP studies

These results are more reflective of models, rather than empirical evidence, as source localization is hard to determine precisely. Due to the nature of these studies that use Chinese logographs, there is a difficulty in an exact translation; a language barrier certainly exists.

There are some difficulties that exist in brain imaging when it comes to insight, thus making it hard to discuss neural mechanisms. Issues include: that insight occurs when an unwarranted mental fixation is broken and when novel task related associations are formed on top of old cognitive skills.

One theory discussed found that "Aha" answers produced more negative ERP results, N380 in the ACC, than the "No-Aha" answers, 250–500 ms, after an answer was produced. The authors suspected that this N380 in the ACC, which plays the role of a warning sign of breaking the mental set, was a reflection of the Aha! effect. Another study was done showed that an Aha! effect was elicited at N320 which has a strong activation in the central-posterior region. These previous studies reflective the premise of the study, that the Aha! effect occurs in the anterior cingulate cortex, while this study finds results indicating the posterior cingulate cortex is responsible. It was found that there was a N350 in the posterior cingulate cortex for successful guessing of logographs, not in the anterior cingulate cortex. The posterior cingulate cortex seems to play a more non-executive function in monitoring and inhibiting the mind set and cognitive function.

Another significant finding of this study done by Qiu and Zhang (2008), was a late positive component (LPC) in successful guessing of the logograph and then recognition of the answer at 600 and 700 ms, post-stimulus, in the parahippocampal gyrus (BA34). The data suggests that the parahippocampus is involved in searching of a correct answer by manipulating it in working memory, and integrating relationships between the base of the target logograph. The parahippocampal gyrus may reflect the formation of novel associations while solving insight problem.

Another ERP study is fairly similar to the Qiu and Zhang, 2008 study, however, this study claims to have anterior cingulate cortex activation at N380, which may be responsible for the mediation of breaking the mental set. Other areas of interest were prefrontal cortex (PFC), the posterior parietal cortex, and the medial temporal lobe. If subjects failed to solve the riddle, and then were shown the correct answer, they displayed the feeling of insight, which reflected the electroencephalogram recordings. 

Overall, it is quite apparent that there are many aspects that can explain the Aha! effect. No particular area has been determined but from the information gathered, it seems that insight occurs in many parts of the brain, within a given time period.

Evidence in fMRI studies

A study with the goal of recording the activity that occurs in the brain during an Aha! moment using fMRIs was conducted in 2003 by Jing Luo and Kazuhisa Niki. Participants in this study were presented with a series of Japanese riddles, and asked to rate their impressions toward each question using the following scale: (1) I can understand this question very well and know the answer; (2) I can understand this question very well and feel it is interesting, but I do not know the answer; or (3) I cannot understand this question and do not know the answer. This scale allowed the researchers to only look at participants who would experience an Aha! moment upon viewing the answer to the riddle. In previous studies on insight, researchers have found that participants reported feelings of insight when they viewed the answer to an unsolved riddle or problem. Luo and Niki had the goal of recording these feelings of insight in their participants using fMRIs. This method allowed the researchers to directly observe the activity that was occurring in the participant's brains during an Aha! moment.

An example of a Japanese riddle used in the study: The thing that can move heavy logs, but cannot move a small nail → A river.

Participants were given 3 minutes to respond to each riddle, before the answer to the riddle was revealed. If the participant experienced an Aha! moment upon viewing the correct answer, any brain activity would be recorded on the fMRI. The fMRI results for this study showed that when participants were given the answer to an unsolved riddle, the activity in their right hippocampus increased significantly during these Aha! moments. This increased activity in the right hippocampus may be attributed to the formation of new associations between old nodes. These new associations will in turn strengthen memory for the riddles and their solutions. 

Although various studies using EEGs, ERPs, and fMRI's report activation in a variety of areas in the brain during Aha! moments, this activity occurs predominantly in the right hemisphere. More details on the neural basis of insight see a recent review named "New advances in the neural correlates of insight: A decade in review of the insightful brain"

Insight problems and problems with insight

Insight problems

The Nine Dot Problem

The Nine Dot Problem with solution. Most individuals fail to draw lines beyond the dots that compose the square, and are unable to solve this puzzle.

 

The Nine Dot Problem is a classic spatial problem used by psychologists to study insight. The problem consists of a 3 × 3 square created by 9 black dots. The task is to connect all 9 dots using exactly 4 straight lines, without retracing or removing one's pen from the paper. Kershaw & Ohlsson report that in a laboratory setting with a time limit of 2 or 3 minutes, the expected solution rate is 0%.

The difficulty with the Nine Dot Problem is that it requires respondents to look beyond the conventional figure-ground relationships that create subtle, illusory spatial constraints and (literally) "think outside of the box". Breaking the spatial constraints shows a shift in attention in working memory and utilizing new knowledge factors to solve the puzzle.

Verbal riddles

Verbal riddles are becoming popular problems in insight research. 

Example: "A man was washing windows on a high-rise building when he fell from the 40-foot ladder to the concrete path below. Amazingly, he was unhurt. Why? [Answer] He slipped from the bottom rung!"

Matchstick arithmetic

Matchstick arithmetic, which was developed and used by G. Knoblich, involves matchsticks that are arranged to show a simple but incorrect math equation in Roman numerals. The task is to correct the equation by moving only one matchstick. 

Two examples of Matchstick Arithmetic Problems.

Anagrams

Anagrams involve manipulating the order of a given set of letters in order to create one or many words. The original set of letters may be a word itself, or simply a jumble.

Example: Santa can be transformed to spell Satan.

Rebus puzzles

Rebus puzzles, also called "wordies", involve verbal and visual cues that force the respondent to restructure and "read between the lines" (almost literally) to solve the puzzle.

Some examples:

1. Puzzle: you just me [Answer: just between you and me]
2. Puzzle: PUNISHMENT [Answer: capital punishment]
3. Puzzle:

   i i i 

   OOOOO

[Answer: circles under the eyes]

Remote Associates Test (RAT)

The Remote Associates Test (known as the RAT) was developed by Martha Mednick in 1962 to test creativity. However, it has recently been utilized in insight research. 

The test consists of presenting participants with a set of words, such as lick, mine, and shaker. The task is to identify the word that connects these three seemingly unrelated ones. In this example, the answer is salt. The link between words is associative, and does not follow rules of logic, concept formation or problem solving, and thus requires the respondent to work outside of these common heuristical constraints. 

Performance on the RAT is known to correlate with performance on other standard insight problems.

The Eight Coin Problem

In this problem a set of 8 coins is arranged on a table in a certain configuration, and the subject is told to move 2 coins so that all coins touch exactly three others. The difficulty in this problem comes from thinking of the problem in a purely 2-dimensional way, when a 3-dimensional approach is the only way to solve the problem.

Problems with insight

Insight research is problematic because of the ambiguity and lack of agreement among psychologists of its definition. This could largely be explained by the phenomenological nature of insight, and the difficulty in catalyzing its occurrence, as well as the ways in which it is experimentally "triggered". 

An example where another solution than the evident solution (number 6) must be found.

 

The pool of insight problems currently employed by psychologists is small and tepid, and due to its heterogeneity and often high difficulty level, is not conducive of validity or reliability. 

One of the biggest issues surrounding insight problems is that for most participants, they're simply too difficult. For many problems, this difficulty revolves around the requisite restructuring or re-conceptualization of the problem or possible solutions, for example, drawing lines beyond the square composed of dots in the Nine-Dot Problem. 

Furthermore, there are issues related to the taxonomy of insight problems. Puzzles and problems that are utilized in experiments to elicit insight may be classified in two ways. "Pure" insight problems are those that necessitate the use of insight, whereas "hybrid" insight problems are those that can be solved by other methods, such as the trial and error. As Weisberg (1996) points out, the existence of hybrid problems in insight research poses a significant threat to any evidence gleaned from studies that employ them. While the phenomenological experience of insight can help to differentiate insight-solving from non-insight solving (by asking the respondent to describe how they solved the problem, for example), the risk that non-insight solving has been mistaken for insight solving still exists. Likewise, issues surrounding the validity of insight evidence is also threatened by the characteristically small sample sizes. Experimenters may recruit an initially adequate sample size, but because of the level of difficulty inherent to insight problems, only a small fraction of any sample will successfully solve the puzzle or task given to them; placing serious limits on usable data. In the case of studies using hybrid problems, the final sample is at even greater risk of being very small by way of having to exclude whatever percentage of respondents solved their given puzzle without utilizing insight.

The Aha! effect and scientific discovery

There are several examples of scientific discoveries being made after a sudden flash of insight. One of the key insights in developing his special theory of relativity came to Albert Einstein while talking to his friend Michele Besso:

I started the conversation with him in the following way: "Recently I have been working on a difficult problem. Today I come here to battle against that problem with you." We discussed every aspect of this problem. Then suddenly I understood where the key to this problem lay. Next day I came back to him again and said to him, without even saying hello, "Thank you. I've completely solved the problem."

However, Einstein has said that the whole idea of special relativity did not come to him as a sudden, single eureka moment, and that he was "led to it by steps arising from the individual laws derived from experience". Similarly, Carl Friedrich Gauss said after a eureka moment: "I have the result, only I do not yet know how to get to it."

Sir Alec Jeffreys had a eureka moment in his lab in Leicester after looking at the X-ray film image of a DNA experiment at 9:05 am on Monday 10 September 1984, which unexpectedly showed both similarities and differences between the DNA of different members of his technician's family. Within about half an hour, he realized the scope of DNA profiling, which uses variations in the genetic code to identify individuals. The method has become important in forensic science to assist detective work, and in resolving paternity and immigration disputes. It can also be applied to non-human species, such as in wildlife population genetics studies. Before his methods were commercialized in 1987, Jeffreys' laboratory was the only center carrying out DNA fingerprinting in the world.

Brainstorming

From Wikipedia, the free encyclopedia

 

Brainstorming is a group creativity technique by which efforts are made to find a conclusion for a specific problem by gathering a list of ideas spontaneously contributed by its members.

 

In other words, brainstorming is a situation where a group of people meet to generate new ideas and solutions around a specific domain of interest by removing inhibitions. People are able to think more freely and they suggest many spontaneous new ideas as possible. All the ideas are noted down and those ideas are not criticized and after brainstorming session the ideas are evaluated. The term was popularized by Alex Faickney Osborn in the 1963 book Applied Imagination.

Origin

Advertising executive Alex F. Osborn began developing methods for creative problem-solving in 1939. He was frustrated by employees’ inability to develop creative ideas individually for ad campaigns. In response, he began hosting group-thinking sessions and discovered a significant improvement in the quality and quantity of ideas produced by employees. He first termed the process as organized ideation and was later dubbed by participants as "brainstorm sessions", taking the concept after the use of "the brain to storm a problem." During the period when Osborn made his concept, he started writing on creative thinking, and the first notable book where he mentioned the term brainstorming is "How to Think Up" in 1942. Osborn outlined his method in the 1948 book Your Creative Power in chapter 33, "How to Organize a Squad to Create Ideas".

One of Osborne's key recommendations was for all the members of the brainstorming group to be provided with a clear statement of the problem to be addressed prior to the actual brainstorming session. He also explained that the guiding principle is that the problem should be simple and narrowed down to a single target. Here, brainstorming is not believed to be effective in complex problems because of a change in opinion over the desirability of restructuring such problems. While the process can address the problems in such a situation, tackling all of them may not be feasible.

Osborn's method

brainstorming activity conducting

 

Osborn claimed that two principles contribute to "ideative efficacy," these being:

1. defer judgment;
2. reach for quantity.

Following these two principles were his four general rules of brainstorming, established with intention to:

• reduce social inhibitions among group members;
• stimulate idea generation;
• increase overall creativity of the group.

1. Go for quantity: This rule is a means of enhancing divergent production, aiming to facilitate problem solving through the maxim quantity breeds quality. The assumption is that the greater the number of ideas generated the bigger the chance of producing a radical and effective solution.
2. Withhold criticism: In brainstorming, criticism of ideas generated should be put 'on hold'. Instead, participants should focus on extending or adding to ideas, reserving criticism for a later 'critical stage' of the process. By suspending judgment, participants will feel free to generate unusual ideas.
3. Welcome wild ideas: To get a good long list of suggestions, wild ideas are encouraged. They can be generated by looking from new perspectives and suspending assumptions. These new ways of thinking might give you better solutions.
4. Combine and improve ideas:As suggested by the slogan "1+1=3". It is believed to stimulate the building of ideas by a process of association.

Applications

Osborn notes that brainstorming should address a specific question; he held that sessions addressing multiple questions were inefficient. 

Further, the problem must require the generation of ideas rather than judgment; he uses examples such as generating possible names for a product as proper brainstorming material, whereas analytical judgments such as whether or not to marry do not have any need for brainstorming.

Groups

Osborn envisioned groups of around 12 participants, including both experts and novices. Participants are encouraged to provide wild and unexpected answers. Ideas receive no criticism or discussion. The group simply provide ideas that might lead to a solution and apply no analytical judgment as to the feasibility. The judgments are reserved for a later date.^[6]

Variations

Nominal group technique

Participants are asked to write their ideas anonymously. Then the facilitator collects the ideas and the group votes on each idea. The vote can be as simple as a show of hands in favor of a given idea. This process is called distillation. 

After distillation, the top ranked ideas may be sent back to the group or to subgroups for further brainstorming. For example, one group may work on the color required in a product. Another group may work on the size, and so forth. Each group will come back to the whole group for ranking the listed ideas. Sometimes ideas that were previously dropped may be brought forward again once the group has re-evaluated the ideas. 

It is important that the facilitator be trained in this process before attempting to facilitate this technique. The group should be primed and encouraged to embrace the process. Like all team efforts it may take a few practice sessions to train the team in the method before tackling the important ideas.

Group passing technique

Each person in a circular group writes down one idea, and then passes the piece of paper to the next person, who adds some thoughts. This continues until everybody gets his or her original piece of paper back. By this time, it is likely that the group will have extensively elaborated on each idea. 

The group may also create an "idea book" and post a distribution list or routing slip to the front of the book. On the first page is a description of the problem. The first person to receive the book lists his or her ideas and then routes the book to the next person on the distribution list. The second person can log new ideas or add to the ideas of the previous person. This continues until the distribution list is exhausted. A follow-up "read out" meeting is then held to discuss the ideas logged in the book. This technique takes longer, but it allows individuals time to think deeply about the problem.

Team idea mapping method

This method of brainstorming works by the method of association. It may improve collaboration and increase the quantity of ideas, and is designed so that all attendees participate and no ideas are rejected.

The process begins with a well-defined topic. Each participant brainstorms individually, then all the ideas are merged onto one large idea map. During this consolidation phase, participants may discover a common understanding of the issues as they share the meanings behind their ideas. During this sharing, new ideas may arise by the association, and they are added to the map as well. Once all the ideas are captured, the group can prioritize and/or take action.

Directed brainstorming

Directed brainstorming is a variation of electronic brainstorming (described below). It can be done manually or with computers. Directed brainstorming works when the solution space (that is, the set of criteria for evaluating a good idea) is known prior to the session. If known, those criteria can be used to constrain the ideation process intentionally.

In directed brainstorming, each participant is given one sheet of paper (or electronic form) and told the brainstorming question. They are asked to produce one response and stop, then all of the papers (or forms) are randomly swapped among the participants. The participants are asked to look at the idea they received and to create a new idea that improves on that idea based on the initial criteria. The forms are then swapped again and respondents are asked to improve upon the ideas, and the process is repeated for three or more rounds.

In the laboratory, directed brainstorming has been found to almost triple the productivity of groups over electronic brainstorming.

Guided brainstorming

A guided brainstorming session is time set aside to brainstorm either individually or as a collective group about a particular subject under the constraints of perspective and time. This type of brainstorming removes all cause for conflict and constrains conversations while stimulating critical and creative thinking in an engaging, balanced environment. 

Participants are asked to adopt different mindsets for pre-defined period of time while contributing their ideas to a central mind map drawn by a pre-appointed scribe. Having examined a multi-perspective point of view, participants seemingly see the simple solutions that collectively create greater growth. Action is assigned individually. 

Following a guided brainstorming session participants emerge with ideas ranked for further brainstorming, research and questions remaining unanswered and a prioritized, assigned, actionable list that leaves everyone with a clear understanding of what needs to happen next and the ability to visualize the combined future focus and greater goals of the group.

Individual brainstorming

"Individual brainstorming" is the use of brainstorming in solitary situations. It typically includes such techniques as free writing, free speaking, word association, and drawing a mind map, which is a visual note taking technique in which people diagram their thoughts. Individual brainstorming is a useful method in creative writing and has been shown to be superior to traditional group brainstorming.

Question brainstorming

This process involves brainstorming the questions, rather than trying to come up with immediate answers and short term solutions. Theoretically, this technique should not inhibit participation as there is no need to provide solutions. The answers to the questions form the framework for constructing future action plans. Once the list of questions is set, it may be necessary to prioritize them to reach to the best solution in an orderly way.

"Questorming" is another term for this mode of inquiry.

Methods to improving brainstorming sessions

There a number of ways that groups can improve the effectiveness and quality of their brainstorming sessions.

• Avoiding face-to-face groups: Using face-to-face groups can increase production blocking, evaluation apprehension, social matching and social loafing.
• Stick to the rules: Brainstorming rules should be followed, and feedback should be given to members that violate these rules. Violations of brainstorming rules tend to lead to mediocre ideas.
• Pay attention to everyone’s ideas: People tend to pay more attention to their own ideas, however brainstorming requires exposure to the ideas of others. A method to encourage members to pay attention to others’ ideas is to make them list the ideas out or ask them to repeat others’ ideas.
• Include both individual and group approaches: One method that helps members integrate their ideas into the group is brainwriting. This is where members write their ideas on a piece of paper and then pass it along to others who add their own ideas.
• Take breaks: Allow silence during group discussions so that members have time to think things through.
• Do not rush: Allow lots of time for members to complete the task. Although working under pressure tends to lead to more solutions initially, the quality is usually lower than if more time is spent on the task.
• Stay persistent: Members should stay focused and persist at the task even when productivity is low.
• Facilitate the session: A skilled discussion leader should lead and coordinate the brainstorming sessions. This leader can motivate members, correct mistakes, and provide a clear standard of work. They can also be used to keep track of all the ideas and make sure that these ideas are available to everyone.

Alternatives to brainstorming

If brainstorming does not work for your group, there are some alternatives that you could use instead.

• Buzzgroups: Larger groups can form subgroups that come up with ideas when the larger group is stumped. Afterwards, these subgroups come back together and discuss their ideas as a whole group.
• Bug list: Group members write down all the little problems or irritations concerning the issue they are working on, and then the group discusses solutions for each of these “bugs”.
• Stepladder technique: A method where new members state their ideas before listening to the group’s position.
• Synectics: A leader guides the group and discusses their goals, wishes, and frustrations using analogies, metaphors, and fantasy.

Electronic brainstorming (EBS)

Although the brainstorming can take place online through commonly available technologies such as email or interactive web sites, there have also been many efforts to develop customized computer software that can either replace or enhance one or more manual elements of the brainstorming process. 

Early efforts, such as GroupSystems at University of Arizona or Software Aided Meeting Management (SAMM) system at the University of Minnesota, took advantage of then-new computer networking technology, which was installed in rooms dedicated to computer supported meetings. When using these electronic meeting systems (EMS, as they came to be called), group members simultaneously and independently entered ideas into a computer terminal. The software collected (or "pools") the ideas into a list, which could be displayed on a central projection screen (anonymized if desired). Other elements of these EMSs could support additional activities such as categorization of ideas, elimination of duplicates, assessment and discussion of prioritized or controversial ideas. Later EMSs capitalized on advances in computer networking and internet protocols to support asynchronous brainstorming sessions over extended periods of time and in multiple locations.

Introduced along with the EMS by Nunamaker and colleagues at University of Arizona was electronic brainstorming (EBS). By utilizing customized computer software for groups (group decision support systems or groupware), EBS can replace face-to-face brainstorming. An example of groupware is the GroupSystems, a software developed by University of Arizona. After an idea discussion has been posted on GroupSystems, it is displayed on each group member's computer. As group members simultaneously type their comments on separate computers, those comments are anonymously pooled and made available to all group members for evaluation and further elaboration.

Compared to face-to-face brainstorming, not only does EBS enhanced efficiency by eliminating travelling and turn-taking during group discussions, it also excluded several psychological constraints associated with face-to-face meetings. Identified by Gallupe and colleagues, both production blocking (reduced idea generation due to turn-taking and forgetting ideas in face-to-face brainstorming) and evaluation apprehension (a general concern experienced by individuals for how others in the presence are evaluating them) are reduced in EBS. These positive psychological effects increase with group size. A perceived advantage of EBS is that all ideas can be archived electronically in their original form, and then retrieved later for further thought and discussion. EBS also enables much larger groups to brainstorm on a topic than would normally be productive in a traditional brainstorming session.

Computer supported brainstorming may overcome some of the challenges faced by traditional brainstorming methods. For example, ideas might be "pooled" automatically, so that individuals do not need to wait to take a turn, as in verbal brainstorming. Some software programs show all ideas as they are generated (via chat room or e-mail). The display of ideas may cognitively stimulate brainstormers, as their attention is kept on the flow of ideas being generated without the potential distraction of social cues such as facial expressions and verbal language. EBS techniques have been shown to produce more ideas and help individuals focus their attention on the ideas of others better than a brainwriting technique (participants write individual written notes in silence and then subsequently communicate them with the group). The production of more ideas has been linked to the fact that paying attention to others' ideas leads to non-redundancy, as brainstormers try to avoid to replicate or repeat another participant's comment or idea. Conversely, the production gain associated with EBS was less found in situations where EBS group members focused too much on generating ideas that they ignored ideas expressed by others. The production gain associated with GroupSystem users' attentiveness to ideas expressed by others has been documented by Dugosh and colleagues. EBS group members who were instructed to attend to ideas generated by others outperformed those who were not in terms of creativity. 

According to a meta-analysis comparing EBS to face-to-face brainstorming conducted by DeRosa and colleagues, EBS has been found to enhance both the production of non-redundant ideas and the quality of ideas produced. Despite the advantages demonstrated by EBS groups, EBS group members reported less satisfaction with the brainstorming process compared to face-to-face brainstorming group members.

Some web-based brainstorming techniques allow contributors to post their comments anonymously through the use of avatars. This technique also allows users to log on over an extended time period, typically one or two weeks, to allow participants some "soak time" before posting their ideas and feedback. This technique has been used particularly in the field of new product development, but can be applied in any number of areas requiring collection and evaluation of ideas.

Some limitations of EBS include the fact that it can flood people with too many ideas at one time that they have to attend to, and people may also compare their performance to others by analyzing how many ideas each individual produces (social matching).

Incentives

Some research indicates that incentives can augment creative processes. Participants were divided into three conditions. In Condition I, a flat fee was paid to all participants. In the Condition II, participants were awarded points for every unique idea of their own, and subjects were paid for the points that they earned. In Condition III, subjects were paid based on the impact that their idea had on the group; this was measured by counting the number of group ideas derived from the specific subject's ideas. Condition III outperformed Condition II, and Condition II outperformed Condition I at a statistically significant level for most measures. The results demonstrated that participants were willing to work far longer to achieve unique results in the expectation of compensation. 

Challenges to effective group brainstorming

A good deal of research refutes Osborn's claim that group brainstorming could generate more ideas than individuals working alone. For example, in a review of 22 studies of group brainstorming, Michael Diehl and Wolfgang Stroebe found that, overwhelmingly, groups brainstorming together produce fewer ideas than individuals working separately. However, this conclusion is brought into question by a subsequent review of 50 studies by Scott G. Isaksen showed that a misunderstanding of the tool, and weak application of the methods (including lack of facilitation), and the artificiality of the problems and groups undermined most such studies, and the validity of their conclusions.

Several factors can contribute to a loss of effectiveness in group brainstorming. 

Blocking:

 

Because only one participant may give an idea at any one time, other participants might forget the idea they were going to contribute or not share it because they see it as no longer important or relevant. Further, if we view brainstorming as a cognitive process in which "a participant generates ideas (generation process) and stores them in short-term memory (memorization process) and then eventually extracts some of them from its short-term memory to express them (output process)", then blocking is an even more critical challenge because it may also inhibit a person's train of thought in generating their own ideas and remembering them.

Collaborative fixation:

Exchanging ideas in a group may reduce the number of domains that a group explores for additional ideas. Members may also conform their ideas to those of other members, decreasing the novelty or variety of ideas, even though the overall number of ideas might not decrease.

Evaluation apprehension:

Evaluation apprehension was determined to occur only in instances of personal evaluation. If the assumption of collective assessment were in place, real-time judgment of ideas, ostensibly an induction of evaluation apprehension, failed to induce significant variance.

Free-writing:

Individuals may feel that their ideas are less valuable when combined with the ideas of the group at large. Indeed, Diehl and Stroebe demonstrated that even when individuals worked alone, they produced fewer ideas if told that their output would be judged in a group with others than if told that their output would be judged individually. However, experimentation revealed free-writing as only a marginal contributor to productivity loss, and type of session (i.e., real vs. nominal group) contributed much more.

Personality characteristics:

Extroverts have been shown to outperform introverts in computer mediated groups. Extroverts also generated more unique and diverse ideas than introverts when additional methods were used to stimulate idea generation, such as completing a small related task before brainstorming, or being given a list of the classic rules of brainstorming.

Social matching:

One phenomenon of group brainstorming is that participants will tend to alter their rate of productivity to match others in the group. This can lead to participants generating fewer ideas in a group setting than they would individually because they will decrease their own contributions if they perceive themselves to be more productive than the group average. On the other hand, the same phenomenon can also increase an individual's rate of production to meet the group average.

Greatness

From Wikipedia, the free encyclopedia

Krönung des Tugendhelden (c. 1612–1614) by Peter Paul Rubens

 

Monument of Peter the Great in Saint Petersburg

 

Greatness is a concept of a state of superiority affecting a person or object in a particular place or area. Greatness can also be attributed to individuals who possess a natural ability to be better than all others. The concept carries the implication that the particular person or object, when compared to others of a similar type, has clear advantage over others. As a descriptive term it is most often applied to a person or their work, and may be qualified or unqualified. An example of an expression of the concept in a qualified sense would be "Abraham Lincoln is the definition of greatness" or "Franklin D. Roosevelt was one of the greatest wartime leaders". In the unqualified sense it might be stated "George Washington achieved greatness within his own lifetime", thus implying that "greatness" is a definite and identifiable quality. Application of the terms "great" and "greatness" is dependent on the perspective and subjective judgements of those who apply them. Whereas in some cases the perceived greatness of a person, place or object might be agreed upon by many, this is not necessarily the case, and the perception of greatness may be both fiercely contested and highly individual.

Historically, in Europe, rulers were sometimes given the attribute "the Great", as in Alexander the Great, Frederick the Great, and Catherine the Great. Starting with the Roman consul and general Pompey, the Latin equivalent Magnus was also used, as in Pompeius Magnus, Albertus Magnus, and Carolus Magnus. The English language uses the Latin term magnum opus, (literally "great work") to describe certain works of art and literature. 

Since the publication of Francis Galton's Hereditary Genius in 1869, and especially with the accelerated development of intelligence tests in the early 1900s, there has been a vast amount of social scientific research published relative to the question of greatness. Much of this research does not actually use the term great in describing itself, preferring terms such as eminence, genius, exceptional achievement, etc. Historically the major intellectual battles over this topic have focused around the questions of nature versus nurture or person versus context. Today the importance of both dimensions is accepted by all, but disagreements over the relative importance of each are still reflected in variations in research emphases.

"Jesus teaches about greatness" (Matthew 18) by Julius Schnorr von Karolsfeld, 1860

Genetic approaches

The early research had a strong genetic emphasis and focused on intelligence as the driving force behind greatness.

Hereditary Genius – Galton (1869)

The earliest such research, Hereditary Genius by Francis Galton (1869), argued that people vary hugely in “natural ability” which is inherited biologically. Those at the very top end of the range, i.e., geniuses, become the leaders and great achievers of their generation. To prove this thesis Galton collected data showing that genius clusters in what he termed “Notable Family Lines”, such as those of Bernoulli, Cassini, Darwin, Herschel, and Jussieu in science, or Bach in music.

Galton then calculated the odds of eminent people having eminent relations, taking into account the closeness of the biological connection (e.g., son vs grandson), and the magnitude of achievement of the eminent parent. His findings were as anticipated: the more famous the parent (i.e., the greater level of presumed “natural ability”), the greater likelihood there would be illustrious relatives; and the closer the blood tie, the greater those odds.

Early Mental Traits of 300 Geniuses – Cox (1926)

Catharine Cox’s book on The Early Mental Traits of Three Hundred Geniuses (1926), was similar to Galton’s in its orientation. Using the method that her mentor, Stanford Psychology Professor Lewis Terman, had developed for differentiating children in terms of intelligence, Cox coded records of childhood and adolescent achievements of 301 historic eminent leaders and creators to estimate what their IQs would have been on the basis of intellectual level of such achievements relative to the age at which they were accomplished. For example, John Stuart Mill reportedly studied Greek at 3, read Plato at 7, and learned calculus at 11. As such, what he was doing at 5, the average person couldn’t do until 9 years, 6 months of age, giving Mill an estimated IQ of 190.

Cox found that the perceived eminence of those with the highest IQs was higher than that of those attaining lower IQ estimates, and that those with higher IQs also exhibited more versatility in their achievements. For example, da Vinci, Michelangelo, Descartes, Benjamin Franklin, Goethe, and others with IQs in the mid 160s or above were superior in their versatility to those attaining lower scores, such as George Washington, Palestrina, or Philip Sheridan.

Both Cox and Galton have been criticized for failing to take account of the role of nurture, or more specifically socio-economic and educational advantage, in the achievements of these historical greats.

Cultural approach

There was one major anthropological study of genius, and it was triggered specifically by the author’s contentions with Galton’s work.

Configurations of Cultural Growth – Kroeber (1944)

Alfred Kroeber’s Configurations of Cultural Growth (1944) looked at many of the same historic greats as did Galton and Cox, but from a completely different orientation. As a cultural anthropologist, Kroeber maintained that, in Simonton's words, “culture takes primacy over the individual in any account of human (behavior), and that historic geniuses are no exception…” 

To prove his thesis, Kroeber collected “long lists of notable figures from several nationalities and historic eras”, and then grouped them within a field and a shared cultural context, e.g., “Configuration for American Literature”. Then within these groupings he listed his notables in “strict chronological order”, identifying the most eminent figures by using capital letters for their surnames (e.g. EMERSON, LONGFELLOW, POE, WHITMAN, etc. in above configuration).

Kroeber found that genius never appeared in isolation, but rather, in Simonton's words, that “one genius cluster(ed) with others of greater and lesser fame in adjacent generations”. He also found that there were historical “crests” and “troughs” in every field. These fluctuations in the appearance of genius were much too rapid to be explained by the simple mechanism of genetic inheritance along family lines.

Kroeber argued, in Simonton's words, that his “configurations” were due to “emulations”: “Geniuses cluster in history because the key figures of one generation emulate those in the immediately preceding generations… (until) it attains a high point of perfection that stymies further growth”. At this point the “tradition degenerates into empty imitation, as most creative minds move on to greener pastures”.

Recent research is consistent with these explanations; but many aspects of the developmental process from birth to the attainment of greatness remain unaccounted for by Kroeber’s anthropological approach.

Developmental approaches

Retrospective studies, involving extensive interviews with individuals who have attained eminence, or at least exceptional levels of achievement, have added much to our understanding of the developmental process. Two studies in particular stand out.

Scientific Elite – Zuckerman (1977)

Harriet Zuckerman’s Scientific Elite: Nobel Laureates in the United States, is based on many sources of research evidence, including a series of forty-one extended interviews with American winners of the Nobel Prize for science. 

Zuckerman reported her results around two main topics: How the Prize is Awarded, and Career Development of the Scientific Elite.

 

In relation to the question of the career development of the scientific elite Zuckerman uses the phrase "accumulation of advantage" to describe her findings. In her words: “Scientists who show promise early in their careers (are) given greater opportunities in the way of research training and facilities. To the extent that these scientists are as competent as the rest or more so, they ultimately will do far better in terms of both role performance and reward… rewards (which) can be transformed into resources for further work.. (and hence over time) scientists who are initially advantaged gain even greater opportunities for further achievement and rewards.”

To see if ‘accumulation of advantage’ was operating in the career development of the scientific elite, Zuckerman compared the careers of future laureates with those of “members of the United States National Academy of Sciences and the scientific rank and file” along a number of dimensions including socioeconomic origins, status of undergraduate and graduate education, the process of moving into the scientific elite, and first jobs and professorships.

She also interviewed forty-one Nobel laureates extensively about their "apprenticeships" to "master" scientists while they were doing their doctoral research, and other aspects of their career development related to the above topics.

Zuckerman concluded that evidence of "accumulative of advantage" was clearly present over the course of development, with result that her research “… cast(s) considerable doubt on the conclusion that marked differences in performance between the ultra-elite and other scientists reflect equally marked differences in their initial capacities to do scientific work”.

Developing Talent in Young People – Bloom et al (1985)

Benjamin Bloom and five colleagues conducted extensive interviews with 120 “young men and women (as well as their parents and influential teachers)… who had reached the highest levels of accomplishment” in six fields – Olympic sprint swimmers, Top 10 rated professional tennis players, concert pianists, accomplished sculptors, exceptional mathematicians, and outstanding research neurologists.

They report many findings relevant to the “talent development process", including:

• Development was tied throughout to the values, interests, resources, and personal investments of the family of origin. In most families “introduction to the field and initial… skill development occurred” because the “(p)arents (or other family members), in pursuing their own interests, created situations that intrigued, interested, or involved the child… The child’s interest was rewarded or encouraged…” and the parents then provided other ways to extend this interest.
• The “work ethic” is central to talent development. It is developed by “the home environment” and “…directly related to learning and participation in the chosen talent field”.
• “Each group of parents strongly encouraged their children’s development in a particularly highly approved talent field (related to the parents’ own “special interests”) and gave much less support to other possible talent fields and activities.”
• “Families and teachers were crucial at every point along the way to excellence… what families and teachers do at different times and how they do it clearly sets the stage for exceptional learning in each talent field”.
• “Few… (of the) individuals (included in this study) were regarded as child prodigies”; and, as a result, this research “raises (serious) questions about earlier views of special gifts and innate abilities as necessary prerequisites of talent development”.

Recent approaches

A 1995 book by Hans Eysenck argues that a “personality trait” called Psychoticism is central to becoming a creative genius; and a more recent book by Bill Dorris (2009) looks at the influence of “everything from genetics to cultural crises”, including chance, over the course of development of those who attain greatness. 

Hans Eysenck's book, Genius: The Natural History of Creativity (1995), "construct(s)... a model of genius and creativity" whose "novelty lies in (its) attempt to make personality differences central to the argument".

In particular Eysenck is interested in a personality trait called “psychoticism … chief among (whose) cognitive features is a tendency to over-inclusiveness, i.e., an inclination not to limit one's associations to relevant ideas, memories, images, etc."

He considers a massive range of experimental psychological research in order to establish the underlying genetic, neuro-chemical mechanisms which may be operating to influence levels of creativity associated with fluctuations in “the tendency towards over-inclusiveness indicative of psychoticism..."

Eysenck's assessment of his overall argument is as follows: "There is no hint that the theory is more than a suggestion of how many disparate facts and hypotheses can be pulled together into a causal chain, explaining… the apogee of human endeavor - genius. If the theory has one point in its favour it is that every step can be tested experimentally, and that many steps have already received positive support from such testing." 

The Arrival of The Fittest - Dorris (2009)

Bill Dorris's book, The Arrival of The Fittest: How The Great Become Great (2009), attempts to address a number of issues which remain unanswered on the subject. These include the role of chance over the course of development, the importance of the development of unique personal characteristics to achieving greatness, and the influence of changes in the wider worlds surrounding the person - from interpersonal to societal - on the course of an individual's development.

Dorris argues that those who attain ‘greatness’ are credited with solving a key generational problem in a field and/or society (e.g., Einstein resolving the conflict between Newton and Maxwell in physics at the outset of the 20th century; or Woody Guthrie providing a voice for the outcasts of the Great Depression of the 1930s).

Dorris’s core argument is that those who become ‘great’ start out with sufficient genetic potential and then are able, over two or more decades, to obtain matches/fits with “the right kind of problems” to extend the development of these genetic biases into what Dorris terms, “key characteristics”. These are the intellectual, personality, and self characteristics which eventually turn out to be required to solve a key generational problem in their field and/or society.

Dorris argues that there are four types of matching processes which occur over the course of such development. These refer to matches between the developmental needs of the person and the opportunities and resources essential to engaging in problem solving activities that stimulate further development of those aspects of intelligence, personality, and self which eventually become key characteristics.

Two of these matching processes are covered extensively in the existing research literature: continuous matching and cumulative matching.

The other two of the matching processes described by Dorris are completely new to this book: catalytic matching and chaotic matching. 

Dorris’s argument in relation to catalytic matching is that anyone who eventually becomes a ‘great’ will have experienced one or more sustained periods of exceptionally accelerated development of their key characteristics, accelerations which serve massively to differentiate them from their former peers in terms of both development and visibility within the field.

This acceleration occurs because the person becomes the focal point (star) of a self-reinforcing system of expertise and resources (catalytic system) which thrives off this person’s accelerated development and visibility.

Dorris's argument in relation to chaotic matching is that access to the resources and learning opportunities essential to the development of key characteristics of an eventual ‘great’ often occurs not due to the efforts/planning of the individual, but simply due to chance events in the interpersonal, institutional or societal worlds around the person, who (unlike perhaps millions of equally capable peers) becomes the beneficiary of these chance events – events which Dorris argues can change a person’s entire future in much the same way as a lottery jackpot or a Titanic ticket.

Dorris documents his theoretical arguments with extensive case studies of a wide range of individuals, including Einstein, Elvis, Monet, Mozart, da Vinci, Abraham Lincoln, Watson and Crick, basketball great Bill Russell, Louis Armstrong, Bill Gates, Alfred Hitchcock, Woody Guthrie, and Norma Jeane/Marilyn Monroe.