Troubleshooting consists of using generic or ad hoc methods, in an orderly way, to find solutions to problems. Some problem-solving techniques developed and used in artificial intelligence, computer science, engineering, mathematics, or medicine are related to mental problem-solving techniques studied in psychology.
Video Problem solving
Definisi
The term problem solving is used in a variety of disciplines, sometimes with different perspectives, visual, and often with different terminology. For example, it is a mental process in the psychology and computerization process in computer science. Problems can also be classified into two different types (unclear and well-defined) from which the exact solution must be made. An unclear problem is a problem that has no clear purpose, solution path, or expected solution. Conversely, well-defined issues have specific objectives, clear path solutions, and expected solutions are obvious. These problems also allow for early planning of more than obscure issues. Solving problems sometimes involves dealing with pragmatics (logic) and semantics (problem interpretation). The ability to understand what the purpose of the problem is, and what rules can be applied, is the key to solving the problem. Sometimes problems require abstract thinking and produce creative solutions.
Psychology
Thomas J. D'Zurilla in 1988 defines problem solving as "the cognitive-affective-behavioral process through which an individual (or group) tries to identify, discover, or find effective ways to address the problems faced in everyday life". This is an evolutionary impulse for living organisms and coping skills that are essential for dealing with various problems. The problem solving specifically in psychology refers to the state of desire to achieve a definite 'goal' of the present state which is not directly moving toward the goal, far from it, or requiring more complex logic to find a description of a lost condition or a step toward a goal. In every case "where you want to be" is a country you imagine (or written) where you want and the solution is situation- or context-specific. This process includes troubleshooting or 'problem analysis', problem formation, generating alternative strategies, implementation and verification of selected solutions. The outstanding feature of the problem is that there is the goal to achieve and how you get there depending on the problem orientation (problem solving style and skill) and systematic analysis. The nature of the process and the method of solving human problems is the field of study and work for mental health professionals. Methods of studying problem solving include introspection, behaviorism, simulation, computer modeling, and experimentation. Social psychologists look into the aspects of people-environment relationships of problem and problem-solving methods that are independent and interdependent. Problem solving has been defined as high-level cognitive processes and intellectual functions requiring more routine or fundamental modulation and control skills.
Troubleshooting has two primary domains: math problem solving and personal troubleshooting. Both are seen in some difficulties or obstacles encountered. Empirical research shows that self and interpersonal skills; approach to collaborative and instrumental problems (it helps in a broad and reflective understanding of problem situations and better results); smoothness of strategy (number and diversity of strategies) and conceptual clarity that can lead to action-identification (Vallacher & Wegner, 1987); a temporary lifetime perspective that leads to selectivity in strategy (focusing on issues and strategies that focus on emotions); self-efficacy and intimacy issues; the formation of 'carry over' relationships (egalitarian friendships, romantic bonds, gangs, hygges, etc.) that help individuals move through life and provide a sense of identity (Antonucci, Birditt, & Ajrouch, 2011); negotiations; type of relationship (mandatory vs voluntary); typing gender; focuses on focused emotion issues and strategies as some of the strategies and factors that affect everyday problem solving. Neuropsychologists have learned that individuals with frontal lobe injuries with deficits in emotional control and reasoning can be overcome with effective rehabilitation and can increase the capacity of the wounded to solve everyday problems (Rath, Simon, Langenbahn, Sherr, & Diller, 2003 ).
Interpersonal daily problem solving depends on the individual's individual motivational and contextual components. One such component is the emotional valence of the "real world" problem and can inhibit or assist the problem solving performance. Researchers have focused on the role of emotion in problem solving (D'Zurilla & Goldfried, 1971; D'Zurilla & Nezu, 1982), suggesting that poor emotional control may disrupt the focus on the target task and hamper problem solving and the possibility leads to negative outcomes such as fatigue, depression, and inertia (Rath, Langenbahn, Simon, Sherr, & Diller, 2004). In conceptualization, human problem solving consists of two related processes: problem orientation, motivation/attitude/affective approach to problem situations and problem-solving skills. The study concludes that people's strategies combine with their goals (Hoppmann & Blanchard-Fields, 2010, Berg et al., 1998) and they come from the natural process of comparing themselves with others (Sonstegard and Bitter, 1998).
Cognitive science
The earliest experimental work of the Gestaltists in Germany puts the start of a problem-solving study (eg, Karl Duncker in 1935 with his book Productive thinking psychics ). Then this experimental work continued until the 1960s and early 1970s with research conducted on relatively simple (but new to participants) laboratory tasks of problem solving. Choosing simple novel tasks is based on a clearly defined, short-term solution to complete it, which allows researchers to track the participants' steps in the problem-solving process. The underlying assumption of the researcher is that simple tasks such as the Hanoi Tower correspond to the main characteristics of the "real world" problem and thus the typical cognitive processes in the participants' attempt to solve simple problems are the same for the "real world" problem as well; simple problems are used for convenience reasons and with the hope that generalization thinking for more complex issues will become possible. Perhaps the most famous and most impressive example of this research is the work of Allen Newell and Herbert A. Simon. Other experts have pointed out that the principle of decomposition enhances the problem-solving ability to make good judgments.
Computer science and algorithmics
In computer science and in the artificial intelligence section associated with algorithms ("algorithmic"), troubleshooting includes a number of techniques known as algorithms, heuristics, root problem analysis, etc. In this discipline, problem solving is part of a larger one. processes that include problem-solving, de-duplication, analysis, diagnosis, improvement, etc.
Engineering
Troubleshooting is used when a product or process fails, so corrective action can be taken to prevent further failures. It can also be applied to a product or process before the actual event of failure, that is when potential problems are predictable and analyzed, and mitigation is applied so that problems never really occur. Techniques such as Failure Mode Effect Analysis can be used to proactively reduce the probability of a problem occurring.
Military science
In military science, problem solving is related to the concept of "final state", the desired conditions or situation that the strategists want to generate. The ability to solve important problems in any military rank, but very important at the command and control level, where he really correlates with an in-depth understanding of qualitative and quantitative scenarios. The Effectiveness troubleshooting is "the criteria used to assess changes in system behavior, capabilities, or operating environments that are bound to measure the achievement of the final state, the achievement of goals, or the creation of securities". Planning for troubleshooting is "the process that determines and explains how to employ 'means' with 'certain way' to achieve 'goals' (solution of problem)."
More
Forensic engineering is an important failure analysis technique that involves searching for defects and product defects. Corrective action can then be taken to prevent further failures.
Reverse engineering attempts to discover the original problem-solving logic used in developing a product by separating it.
Other troubleshooting tools are linear and nonlinear programming, queuing systems, and simulations.
Maps Problem solving
Troubleshooting strategy
The troubleshooting strategy is the steps that will be used to find the problem (s) that are on the way to achieving its own goals. Firend problem solving model (PSM) is practical in application and incorporates conventional 5WH approach, with systematic process of inquiry, implementation and assessment cycle. Some would call this a "problem-solving cycle" (Bransford & Stein, 1993). In this cycle people will recognize problems, define problems, develop strategies to fix problems, regulate knowledge of problem cycles, figure out the resources available at the user's disposal, monitor one's progress, and evaluate solutions for accuracy. The reason for the so-called cycle is that once someone is done with another problem it will usually show up.
Blanchard-Fields (2007) looks at the problem solving of one of two terms. The former sees problems that have only one solution (such as a math problem, or fact-based question) based on psychometric intelligence. Others are socio-emotional and unpredictable with an ever-changing answer (like what your favorite color is or what you should get someone for Christmas).
The following techniques are usually called troubleshooting strategies'
- Abstract: solve the problem in the system model before applying it to the real system
- Analogy: using solutions that solve analog problems
- Brainstorming: (especially among groups of people) suggests a large number of solutions or ideas and incorporates and develops them until the optimal solution is found
- Divide and conquer: breaking big and complex problems into smaller and resolvable issues
- Hypothesis testing: assuming a possible explanation for the problem and trying to prove (or, in some contexts, disprove) the assumption
- Lateral thinking: approaching solutions indirectly and creatively
- End-of-the-line analysis: chooses action on each step to move closer to the goal
- Focus object method: synthesizes seemingly mismatched characteristics of different objects into something new
- Morphological analysis: assess the output and interaction of the entire system
- Evidence: try to prove that the problem can not be solved. The point at which the failing proof will be the starting point to complete it
- Reduction: turning the problem into another problem for which the solution exists
- Research: use existing ideas or adapt existing solutions to similar problems
- Root cause analysis: identify the cause of the problem
- Trials: test possible solutions until the right solution is found
Troubleshooting methods
- Eight Problem Solving Disciplines
- GROW model
- How to fix it
- OODA circles (observe, orient, decide, and act)
- PDCA (plan-do-check-action)
- Analysis of root causes
- Diagnosis of RPR problem (quick problem resolution)
- TRIZ (in Russian: Teoriya Resheniya Izobretatelskikh Zadach , "inventor solving theory")
- A3 troubleshooting
- System dynamics
- Hive mind
Common barriers
Common barriers to problem solving are mental constructs that hinder our ability to properly solve problems. These obstacles prevent people from solving problems in the most efficient way. Five of the most common processes and factors that researchers identify as barriers to problem solving are confirmation bias, mental settings, functional provisions, unnecessary constraints, and irrelevant information.
Confirmation bias
In the field of science there is a set of fundamental standards, the scientific method, which describes the process of discovery of facts or truth about the world through unbiased consideration of all pertinent information and through impartial observation and/or experiment with that information. According to this method, one can accurately find solutions to perceived problems by performing these steps. The scientific method does not prescribe a process limited to scientists, but more than that everyone can practice in their respective fields of work as well as in their personal lives. Confirmation of bias can be described as one of the unconscious or inadvertent of the scientific method. Thus when a person shows a confirmation bias, someone formally or informally collects the data and then observes and experiments with the data in such a way that it further supports a previously formed idea that may or may not have motivation . Research has found that professionals in the field of scientific studies are also subject to confirmation bias. Andreas Hergovich, Reinhard Schott, and Christoph Burger's online experiments, for example, suggest that professionals in the field of psychological research tend to see scientific studies aligned with better-formed insights than studies that are not in tune with the beliefs they set.
Motivation refers to a person's desire to defend or find a proof of belief (eg, religious belief) that is important to a person. According to Raymond Nickerson, one can see the consequences of confirmation bias in real life situations, which range in severity from inefficient government policies to genocide. Due to the latter and the most severe of these cognitive barriers, Nickerson argues that those involved in committing genocide of those accused of magic, cruelty that occurred from the fifteenth to the seventeenth centuries, show a confirmation bias with motivation. Researcher Michael Allen found evidence for a confirmation bias with motivation in schoolchildren who worked to manipulate their science experiments in such a way that would generate their expectations of results. However, confirmation bias does not always require motivation. In 1960, Peter Cathcart Wason conducted an experiment in which participants first looked at three numbers and then created a hypothesis that proposed a rule that could be used to create the triplet of that number. When testing their hypothesis, participants tend to only make additional triplets of numbers that will confirm their hypothesis, and are less likely to make triplets that will negate or disprove their hypothesis. Thus research also shows that people can and work to confirm a theory or idea that does not support or involve significant personal beliefs.
Mental Set
The mental set was first articulated by Abraham Luchins in the 1940s and is shown in his famous water jug ​​experiment. In this experiment, participants were asked to fill a jar with a certain amount of water using only another jug ​​(usually three) with a different maximum capacity as a tool. After Luchins gave the participants a set of water jug ​​problems that could all be solved using a single technique, he would then give them a problem that could be solved using the same technique or a new and simpler method. Luchin found that participants tended to use the same techniques they were accustomed to though the possibility of using a simpler alternative. Thus the mental set illustrates a person's tendency to attempt to solve a problem in such a way that has proven successful in previous experience. However, as Luchin's work suggests, such methods for finding solutions that have been successful in the past may be inadequate or optimal for new but similar problems. Therefore, it is often necessary for people to move beyond their mental set to find a solution. This is again demonstrated in the Norman Maier 1931 experiment, which challenges participants to solve problems by using household objects (tang) in an unconventional way. Maier observes that participants often can not see objects in a way that deviates from their typical usage, a phenomenon that is considered a special form of the mental set (more specifically known as functional fixedness, which is the topic of the following section). As people cling firmly to their mental set, they are said to be experiencing fixation, apparent obsession or preoccupation with repeated failing strategies. In the late 1990s, researcher Jennifer Wiley worked to reveal that expertise can work to create mental sets in people who are considered experts in certain fields, and he further obtained evidence that the mental set created by expertise can lead to the development of fixation.
Functional functionalities
Functional determination is a specific form of mental arrangement and fixation, alluded to earlier in the Maier experiment, and furthermore it is another way in which cognitive bias can be seen throughout everyday life. The German team and Clark Barrett describe this barrier as a fixed design of an object that inhibits an individual's ability to see it serve other functions. In more technical terms, these researchers explain that "[s] ubjects becomes" fixed "in the object design function, and problem solving suffers relative to the control conditions in which the function object is not shown." Functional determination is defined as having only the main function of the object itself inhibiting that capability serves a purpose other than its original function. In a study that highlights the main reason that young people are immune to functional determinations, it is stated that "functional determinations... [are when] subjects are impeded in achieving solutions to problems with their knowledge of the conventional functions of an object." Furthermore, it is important to note that functional determinations can be easily expressed in common situations. For example, imagine the following situation: a man sees an insect on the floor that he wants to kill, but the only thing in his hand today is a can of air freshener. If the man starts searching for something at home to kill the insect instead of realizing that the air freshener can actually be used not only has its main function to refresh the air, it is said to be functional. provision. The man's knowledge of the cans presented as a pure air freshener hampers his ability to realize that it can also be used to serve other purposes, which in this case is as a tool to kill insects. Functional determination can occur on many occasions and may cause us to have certain cognitive biases. If we only see objects as serving one main focus than we fail to realize that objects can be used in various ways other than the intended purpose. This in turn can cause many problems with troubleshooting. Common sense seems to be a reasonable answer to fixed functionality. One can make this argument because it seems rather easy to consider the possible use of alternatives to an object. Perhaps using common sense to solve this problem can be the most accurate answer in this context. With the example mentioned earlier, it would seem very reasonable to use air fresheners to kill bugs rather than looking for something else to serve that function but, as the study shows, this often does not happen.
Functionality still limits the ability of people to solve problems accurately by causing a person to have a very narrow way of thinking. Functional determination can be seen in other types of learning behaviors as well. For example, research has found a functional determination in many educational instances. Researchers Furio, Calatayud, Baracenas, and Padilla stated that "... functional determination can be found in the concept of learning and in solving chemical problems." There is more emphasis on this function that is seen in the subject of this and other types.
There are several hypotheses in terms of how functional provisions relate to problem solving. There are also many ways in which a person can have problems when thinking of a particular object by having this function. If there is one way in which a person usually thinks of something rather than some way then this can cause obstacles in how that person thinks about a particular object. It can be seen as narrow-minded thinking, defined as the way in which one can not see or accept certain ideas in a particular context. The functional gap is closely related to this as mentioned earlier. This can be done intentionally and or unintentionally, but for the most part it seems that the process of solving this problem is done in an unintentional way.
Functional gaps can affect problem solvers at least in two specific ways. The first relates to time, because functional determination causes people to spend more time than is necessary to solve a given problem. Secondly, functional determination often causes the solver to make more attempts to solve problems than they would make if they did not experience this cognitive impediment. In the worst case, functional determination can actually prevent a person from being aware of the solution to the problem. Functional determination is a common occurrence, which affects the lives of many people.
Unnecessary limitations
Unnecessary constraints are another common barrier that people face when trying to solve a problem. This particular phenomenon occurs when the subject, trying to solve the problem unconsciously, places limits on existing tasks, which in turn forces him to become more innovative in their thinking. The breaker breaks through the barriers when they are fixated on a way to solve their problems, and it becomes increasingly difficult to see anything but the method they have chosen. Usually, solvers experience this when trying to use the methods they have experienced from success, and they can not help but try to get them to work in the current state, even if they see that it is counterproductive.
Groupthink, or taking the mindset of the rest of the group members, can also act as an unnecessary obstacle when trying to solve a problem. This is due to the fact that with everyone thinking the same thing, stopping at the same conclusion, and obstructing themselves to think beyond this. This is very common, but the most famous example of this barrier is itself present is a well-known example of a dot problem. In this example, there are nine points spanning three dots, and three dots running up and down. The breaker is then asked to draw no more than four lines, without lifting pen or pencil from paper. This series of lines should connect all points on the paper. Then, what usually happens is that the subject creates an assumption in their mind that they must connect the dots without letting the pen or pencil out of the square points. Standardized procedures like these can often lead to mentally created barriers like this, and researchers have found the correct 0% solution level within the time set for the task to be completed. Enforced constraints prevent the solver from thinking beyond the point boundaries. From this phenomenon the expression that "thinking outside the box" is lowered.
This issue can be quickly resolved by the dawn of realization, or insights . A few minutes of struggling solving problems can bring this sudden insight, in which the breaker quickly sees the solution clearly. Problems like these are usually solved through insight and can be very difficult for a subject depending on how they craft problems in their minds, how they make use of their past experiences, and how much they conjure up this information in their work memories. In the case of a nine-point example, the breakers have been incorrectly arranged in their minds because of the constraints they have placed on the solution. In addition, people experience struggles as they try to compare problems with their previous knowledge, and they think they have to maintain their line within the dots and not go beyond. They do this because trying to imagine the connected dots outside the square puts a strain on their working memory.
Fortunately, the solution to the problem becomes apparent when insight occurs after an incremental movement is made toward the solution. These small movements occur without the knowledge of the solver. Then when the insights are fully realized, the "aha" moment occurs for the subject. These moments of insight may take a long time to manifest or not at other times, but the way forward comes after working hard to overcome these obstacles remains the same.
Irrelevant information
Irrelevant information is information presented in an unrelated or unimportant problem with a specific problem. In the specific context of the problem, irrelevant information will not be useful in helping solve a particular problem. Often irrelevant information is damaging the troubleshooting process. This is a common barrier that many people struggle to get through, especially if they are not aware of it. Irrelevant information making solving relatively simple problems much more difficult.
For example: "Fifteen percent of people in Topeka have unlisted phone numbers.You choose 200 names at random from Topeka's phonebook.How many of these people have unlisted phone numbers?"
People who are not registered in the phone book will not be among the 200 names you choose. People who see this task naturally want to use the 15% given to them in trouble. They see that there is information available and they immediately think that it needs to be used. This is of course not true. Such questions are often used to test students who take aptitude tests or cognitive evaluation. They are not meant to be difficult but they are meant to require thought that is not necessarily common. Irrelevant information is usually represented in math problems, a specific word problem, in which numerical information is laid for the purpose of challenging individuals.
One reason irrelevant information is so effective at keeping someone off topic and away from relevant information is how it is represented. The way information is represented can make a big difference in how difficult the problem should be overcome. Whether a problem is represented visually, verbally, spatially, or mathematically, irrelevant information can have a major impact on how long a problem should be resolved; or is it possible. The problem of Buddhist monks is a classic example of irrelevant information and how it can be represented in various ways:
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- A Buddhist monk starts at dawn one day walking up the mountain, reaching the summit at sunset, meditating on it for several days until one dawn as he begins walking back to the foot of the mountain, which he reaches at sunset. Not making assumptions about starting or stopping or about his pace during the trip, proving that there is a place on the road he occupies at the same hour of the day on two separate trips.
This problem is almost impossible to solve because of how the information is represented. Because it is written in a way that represents information verbally, it causes us to try and create a mental picture of the paragraph. This is often very difficult especially with all the irrelevant information involved in the question. This example is made easier to understand when paragraphs are represented visually. Now if the same problem is asked, but it is also accompanied by a corresponding graph, it would be much easier to answer this question; irrelevant information will no longer work as street blocking. By representing the problem visually, there are no difficult words to understand or scenarios to imagine. The visual representation of this problem has removed the difficulty of solving it.
This type of representation is often used to make difficult problems easier. They can be used on tests as a strategy to remove Irrelevant Information, which is one of the most common barriers when dealing with problem solving issues. Identifying the important information presented in a problem and then being able to correctly identify its usefulness is essential. Being aware of irrelevant information is the first step in overcoming this general obstacle.
Cognitive science: two schools
In cognitive science, the researcher realizes that the problem-solving process differs across the domain of knowledge and across skill levels (eg Sternberg, 1995) and that, consequently, the findings obtained in the laboratory can not always generalize to problem-solving situations outside the laboratory, an emphasis on real-world problem solving since the 1990s. This emphasis has been expressed differently in North America and Europe. While North American research typically concentrates on studying problem solving in separate domain of natural knowledge, many European studies have focused on novels, complex problems, and have been done with computer scenarios (see Funke, 1991, for an overview).
Europe
In Europe, two major approaches have emerged, initiated by Donald Broadbent (1977; see Berry & Broadbent, 1995) in Great Britain and others by Dietrich DÃÆ'¶rner (1975, 1985; see DÃÆ'¶rner & , 1995) in Germany. Both approaches place emphasis on relatively complex, semantic, and computer-rich laboratory tasks, built to resemble real-life problems. But the approach is somewhat different in their theoretical and methodological objectives. The tradition initiated by Broadbent emphasizes the difference between a cognitive problem-solving process that operates under consciousness versus out-of-consciousness, and usually uses well-defined mathematical computerized systems. The tradition initiated by DÃÆ'¶rner, on the other hand, has an interest in the interaction of cognitive, motivational, and social components of problem solving, and utilizes extremely complex computerized scenarios that contain up to 2,000 highly interconnected variables (eg, ¶rner, Kreuzig, Reither & amp; StÃÆ'¤udel's 1983 LOHHAUSEN project, Ringelband, Misiak & Kluwe, 1990). Buchner (1995) describes two traditions in detail.
North America
In North America, initiated by Herbert A. Simon's work on "learning by doing" in rich semantic domains (eg Anzai & Simon, 1979; Bhaskar & Simon, 1977), researchers began investigating solving problems separately at Different nature of domain knowledge - such as physics, writing, or playing chess - thus releasing their efforts to extract the global theory of problem solving (eg Sternberg & Frensch, 1991). In contrast, these researchers often focus on developing problem solving in specific domains, namely in the development of skills (eg Anderson, Boyle & Reiser, 1985; Chase & amp; Simon; 1973; Chi, Feltovich & Glaser, 1981).
Areas that attract a bit intensive attention in North America include:
- Reading (Stanovich & Cunningham, 1991) Writing
- (Bryson, Bereiter, Scardamalia & Joram, 1991)
- Calculations (Sokol & amp; McCloskey, 1991)
- Political decision making (Voss, Wolfe, Lawrence & Engle, 1991)
- Managerial troubleshooting (Wagner, 1991)
- Reason for lawyer (Amsel, Langer & Loutzenhiser, 1991)
- Mechanical troubleshooting (Hegarty, 1991)
- Troubleshooting in electronics (Lesgold & Lajoie, 1991)
- Computer skills (Kay, 1991)
- Game play (Frensch & amp; Sternberg, 1991)
- Personal troubleshooting (Heppner & Krauskopf, 1987)
- Mathematical troubleshooting (PÃÆ'³lya, 1945; Schoenfeld, 1985)
- Social problem solving (D'Zurilla & Goldfreid, 1971; D'Zurilla & Nezu, 1982)
- Troubleshooting for innovation and discovery: TRIZ (Altshuller, 1994)
Characteristics of complicated issues
As explained by Dietrich DÃÆ'¶rner and later expanded by Joachim Funke, complex problems have several distinctive characteristics that can be summarized as follows:
- Complexity (large number of items, interrelations and decisions)
- enumerability
- heterogeneity
- connectivity (hierarchical relationships, communication relationships, allocation relations)
- Dynamics (time considerations)
- temporary constraint
- temporary sensitivity
- phase effects
- dynamic uncertainty
- Intransparency (lack of clarity of the situation)
- start opacity
- advanced opacity
- Polytely (lots of goals)
- inexpressiveness
- controversy
- mortality
Collective troubleshooting
Problem solving is applied on many levels - from individual to civilization. Collective problem solving refers to collective problem solving.
Social problems and global problems are usually only solvable collectively.
It has been noted that the complexity of contemporary problems has transcended individual cognitive capacities and requires different but complementary skills and collective problem-solving abilities.
Collective intelligence is shared or a group of intelligence arising from collaboration, collective efforts, and many individual rivals.
In a 1962 research report, Douglas Engelbart attributes collective intelligence to organizational effectiveness, and predicts that proactively 'adding to human intelligence' will produce multiple effects in group problem solving: "The three people working together in this enlarged fashion seem to be more than three times more effective in solving complicated problems such as one self-enlarged person ".
Henry Jenkins, a key theorist of new media and media convergence, refers to the theory that collective intelligence can be attributed to media convergence and participatory culture. He criticized contemporary education for failing to incorporate online collective problem-solving trends into the classroom, stating "whereas the collective intelligence community encourages job ownership as a group, individual classroom school". Jenkins argues that interaction within the knowledge community builds important skills for young people, and teamwork through the collective intelligence community contributes to the development of those skills.
The collective impact is the commitment of a group of actors from different sectors to the general agenda to solve a particular social problem, using a structured collaboration form.
After World War II the United Nations, the Bretton Woods and WTO organizations were created and collective problem solving at the international level crystallized since the 1980s in about 3 types of these organizations. Because these global institutions remain state-centered or state-centered, it has been surprisingly called that a country-state-centered or collective-state approach to problem solving is collective rather than alternative.
Crowdsourcing is the process of gathering ideas, thoughts, or information from many independent participants, with the aim of finding the best solution to the challenges. Modern information technology allows a large number of subjects to be involved as well as systems managing these suggestions that deliver good results. With the internet, new capacity for collective, including planetary-scale, problem-solving has been created.
See also
Note
References
Source of the article : Wikipedia
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