Problem solving in the context of Decision-making process


Problem solving in the context of Decision-making process

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⭐ Core Definition: Problem solving

Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields. The former is an example of simple problem solving (SPS) addressing one issue, whereas the latter is complex problem solving (CPS) with multiple interrelated obstacles. Another classification of problem-solving tasks is into well-defined problems with specific obstacles and goals, and ill-defined problems in which the current situation is troublesome but it is not clear what kind of resolution to aim for. Similarly, one may distinguish formal or fact-based problems requiring psychometric intelligence, versus socio-emotional problems which depend on the changeable emotions of individuals or groups, such as tactful behavior, fashion, or gift choices.

Solutions require sufficient resources and knowledge to attain the goal. Professionals such as lawyers, doctors, programmers, and consultants are largely problem solvers for issues that require technical skills and knowledge beyond general competence. Many businesses have found profitable markets by recognizing a problem and creating a solution: the more widespread and inconvenient the problem, the greater the opportunity to develop a scalable solution.

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Problem solving in the context of Master's degree

A master's degree (from Latin magister) is a postgraduate academic degree awarded by universities or colleges upon completion of a course of study demonstrating mastery or a high-order overview of a specific field of study or area of professional practice. A master's degree normally requires previous study at the bachelor's level, either as a separate degree or as part of an integrated course. Within the area studied, master's graduates are expected to possess advanced knowledge of a specialized body of theoretical and applied topics; high order skills in analysis, critical evaluation, or professional application; and the ability to solve complex problems and think rigorously and independently.

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Problem solving in the context of Human intelligence

Human intelligence is the intellectual capability of humans, which is marked by complex cognitive feats and high levels of motivation and self-awareness. Using their intelligence, humans are able to learn, form concepts, understand, and apply logic and reason. Human intelligence is also thought to encompass their capacities to recognize patterns, plan, innovate, solve problems, make decisions, retain information, and use language to communicate.

There are conflicting ideas about how intelligence should be conceptualized and measured. In psychometrics, human intelligence is commonly assessed by intelligence quotient (IQ) tests, although the validity of these tests is disputed. Several subcategories of intelligence, such as emotional intelligence and social intelligence, have been proposed, and there remains significant debate as to whether these represent distinct forms of intelligence.

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Problem solving in the context of Thought

In their most common sense, thought and thinking refer to cognitive processes that occur independently of direct sensory stimulation. Core forms include judging, reasoning, concept formation, problem solving, and deliberation. Other processes, such as entertaining an idea, memory, or imagination, are also frequently considered types of thought. Unlike perception, these activities can occur without immediate input from the sensory organs. In a broader sense, any mental event—including perception and unconscious processes—may be described as a form of thought. The term can also denote not the process itself, but the resulting mental states or systems of ideas.

A variety of theories attempt to explain the nature of thinking. Platonism holds that thought involves discerning eternal forms and their interrelations, distinguishing these pure entities from their imperfect sensory imitations. Aristotelianism interprets thinking as instantiating the universal essence of an object within the mind, derived from sense experience rather than a changeless realm. Conceptualism, closely related to Aristotelianism, identifies thinking with the mental evocation of concepts. Inner speech theories suggest that thought takes the form of silent verbal expression, sometimes in a natural language and sometimes in a specialized "mental language," or Mentalese, as proposed by the language of thought hypothesis. Associationism views thought as the succession of ideas governed by laws of association, while behaviorism reduces thinking to behavioral dispositions that generate intelligent actions in response to stimuli. More recently, computationalism compares thought to information processing, storage, and transmission in computers.

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Problem solving in the context of Critical thinking

Critical thinking is the process of analyzing available facts, evidence, observations, and arguments to make sound conclusions or informed choices. It involves recognizing underlying assumptions, providing justifications for ideas and actions, evaluating these justifications through comparisons with varying perspectives, and assessing their rationality and potential consequences. The goal of critical thinking is to form a judgment through the application of rational, skeptical, and unbiased analyses and evaluation. In modern times, the use of the phrase critical thinking can be traced to John Dewey, who used the phrase reflective thinking, which depends on the knowledge base of an individual; the excellence of critical thinking in which an individual can engage varies according to it. According to philosopher Richard W. Paul, critical thinking and analysis are competencies that can be learned or trained. The application of critical thinking includes self-directed, self-disciplined, self-monitored, and self-corrective habits of the mind, as critical thinking is not a natural process; it must be induced, and ownership of the process must be taken for successful questioning and reasoning. Critical thinking presupposes a rigorous commitment to overcome egocentrism and sociocentrism, that leads to a mindful command of effective communication and problem solving.

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Problem solving in the context of Heuristics

A heuristic or heuristic technique (problem solving, mental shortcut, rule of thumb) is any approach to problem solving that employs a pragmatic method that is not fully optimized, perfected, or rationalized, but is nevertheless "good enough" as an approximation or attribute substitution. Where finding an optimal solution is impossible or impractical, heuristic methods can be used to speed up the process of finding a satisfactory solution. Heuristics can be mental shortcuts that ease the cognitive load of making a decision.

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Problem solving in the context of Engineering

Engineering is the practice of using natural science, mathematics, and the engineering design process to solve problems within technology, increase efficiency and productivity, and improve systems. The traditional disciplines of engineering are civil, mechanical, electrical, and chemical. The academic discipline of engineering encompasses a broad range of more specialized subfields, and each can have a more specific emphasis for applications of mathematics and science. In turn, modern engineering practice spans multiple fields of engineering, which include designing and improving infrastructure, machinery, vehicles, electronics, materials, and energy systems. For related terms, see glossary of engineering.

As a human endeavor, engineering has existed since ancient times, starting with the six classic simple machines. Examples of large-scale engineering projects from antiquity include impressive structures like the pyramids, elegant temples such as the Parthenon, and water conveyances like hulled watercraft, canals, and the Roman aqueduct. Early machines were powered by humans and animals, then later by wind. Machines of war were invented for siegecraft. In Europe, the scientific and industrial revolutions advanced engineering into a scientific profession and resulted in continuing technological improvements. The steam engine provided much greater power than animals, leading to mechanical propulsion for ships and railways. Further scientific advances resulted in the application of engineering to electrical, chemical, and aerospace requirements, plus the use of new materials for greater efficiencies.

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Problem solving in the context of Decision-making

In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options. It could be either rational or irrational. The decision-making process is a reasoning process based on assumptions of values, preferences and beliefs of the decision-maker. Every decision-making process produces a final choice, which may or may not prompt action.

Research about decision-making is also published under the label problem solving, particularly in European psychological research.

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Problem solving in the context of Science, technology, engineering, and mathematics

Science, technology, engineering, and mathematics (STEM) is an umbrella term used to group together the related technical disciplines of science, technology, engineering, and mathematics. It represents a broad and interconnected set of fields that are crucial for innovation and technological advancement. These disciplines are often grouped together because they share a common emphasis on critical thinking, problem-solving, and analytical skills. The term is typically used in the context of education policy or curriculum choices in schools. It has implications for workforce development, national security concerns (as a shortage of STEM-educated citizens can reduce effectiveness in this area), and immigration policy, with regard to admitting foreign students and tech workers.

There is no universal agreement on which disciplines are included in STEM; in particular, whether or not the science in STEM includes social sciences, such as psychology, sociology, economics, and political science. In the United States, these are typically included by the National Science Foundation (NSF), the Department of Labor's O*Net online database for job seekers, and the Department of Homeland Security. In the United Kingdom, the social sciences are categorized separately and are instead grouped with humanities and arts to form another counterpart acronym HASS (humanities, arts, and social sciences), rebranded in 2020 as SHAPE (social sciences, humanities and the arts for people and the economy). Some sources also use HEAL (health, education, administration, and literacy) as the counterpart of STEM.

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Problem solving in the context of Pragmatism

Pragmatism is a philosophical tradition that views language and thought as tools for prediction, problem solving, and action, rather than describing, representing, or mirroring reality. Pragmatists contend that most philosophical topics—such as the nature of knowledge, language, concepts, meaning, belief, and science—are best viewed in terms of their practical uses and successes.

Pragmatism began in the United States in the 1870s. Its origins are often attributed to philosophers Charles Sanders Peirce, William James and John Dewey. In 1878, Peirce described it in his pragmatic maxim: "Consider the practical effects of the objects of your conception. Then, your conception of those effects is the whole of your conception of the object."

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Problem solving in the context of Public policies

Public policy is an institutionalized proposal or a decided set of elements like laws, regulations, guidelines, and actions to solve or address relevant and problematic social issues, guided by a conception and often implemented by programs. These policies govern and include various aspects of life such as education, health care, employment, finance, economics, transportation, and all over elements of society. The implementation of public policy is known as public administration. Public policy can be considered the sum of a government's direct and indirect activities and has been conceptualized in a variety of ways.

They are created and/or enacted on behalf of the public, typically by a government. Sometimes they are made by Non-state actors or are made in co-production with communities or citizens, which can include potential experts, scientists, engineers and stakeholders or scientific data, or sometimes use some of their results. They are typically made by policy-makers affiliated with (in democratic polities) currently elected politicians. Therefore, the "policy process is a complex political process in which there are many actors: elected politicians, political party leaders, pressure groups, civil servants, publicly employed professionals, judges, non-governmental organizations, international agencies, academic experts, journalists and even sometimes citizens who see themselves as the passive recipients of policy."

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Problem solving in the context of Metacognition

Metacognition is an awareness of one's thought processes and an understanding of the patterns behind them. The term comes from the root word meta, meaning "beyond", or "on top of". Metacognition can take many forms, such as reflecting on one's ways of thinking, and knowing when and how oneself and others use particular strategies for problem-solving. There are generally two components of metacognition: (1) cognitive conceptions and (2) a cognitive regulation system. Research has shown that both components of metacognition play key roles in metaconceptual knowledge and learning. Metamemory, defined as knowing about memory and mnemonic strategies, is an important aspect of metacognition.

Writings on metacognition date back at least as far as two works by the Greek philosopher Aristotle (384–322 BC): On the Soul and the Parva Naturalia.

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Problem solving in the context of Lateral thinking

Lateral thinking is a manner of solving problems using an indirect and creative approach via reasoning that is not immediately obvious. Synonymous to thinking outside the box, it involves ideas that may not be obtainable using only traditional step-by-step logic. The cutting of the Gordian Knot is a classical example.

The term was first used in 1967 by Maltese psychologist Edward de Bono who used the Judgement of Solomon, the Nine Dots Puzzle, and the sewing machine (automating the work rather than adding more workers) as examples, among many others, of lateral thinking.

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Problem solving in the context of Cognitive skill

Cognitive skills are skills of the mind, as opposed to other types of skills such as motor skills, social skills or life skills. Cognitive skills include literacy, self-reflection, logical reasoning, abstract thinking, critical thinking, introspection and mental arithmetic. Cognitive skills vary in processing complexity, and can range from more fundamental processes such as perception and various memory functions, to more sophisticated processes such as decision making, problem solving and metacognition.

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Problem solving in the context of Advice (opinion)

Advice (also called exhortation) is a form of relating personal or institutional opinions, belief systems, values, recommendations or guidance about certain situations relayed in some context to another person, group or party. Advice is often offered as a guide to action and/or conduct. Put a little more simply, an advice message is advice about what might be thought, said, or otherwise done to address a problem, make a decision, or manage a situation.

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Problem solving in the context of Artificial intelligence

Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.

High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Alexa); autonomous vehicles (e.g., Waymo); generative and creative tools (e.g., language models and AI art); and superhuman play and analysis in strategy games (e.g., chess and Go). However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore."

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Problem solving in the context of Heuristic (psychology)

Heuristics (from Ancient Greek εὑρίσκω (heurískō) 'to find, discover') is the process by which humans use mental shortcuts to arrive at decisions. Heuristics are simple strategies that humans, animals, organizations, and even machines use to quickly form judgments, make decisions, and find solutions to complex problems. Often this involves focusing on the most relevant aspects of a problem or situation to formulate a solution. While heuristic processes are used to find the answers and solutions that are most likely to work or be correct, they are not always right or the most accurate. Judgments and decisions based on heuristics are simply good enough to satisfy a pressing need in situations of uncertainty, where information is incomplete. In that sense they can differ from answers given by logic and probability.

The economist and cognitive psychologist Herbert A. Simon introduced the concept of heuristics in the 1950s, suggesting there were limitations to rational decision making. In the 1970s, psychologists Amos Tversky and Daniel Kahneman added to the field with their research on cognitive bias. It was their work that introduced specific heuristic models, a field which has only expanded since. While some argue that pure laziness is behind the heuristics process, this could just be a simplified explanation for why people don't act the way we expected them to. Other theories argue that it can be more accurate than decisions based on every known factor and consequence, such as the less-is-more effect.

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