what are characteristics of problem solving

10 Characteristics of Good Problem Solvers

Professional psychologist, motivational writer

Good problem solvers are good thinkers. They have less drama and problems to begin with and don't get overly emotional when faced with a problem. They usually see problems as challenges and life experiences and try to stand above them, objectively.

Good problem solvers use a combination of intuition and logic to come up with their solutions. Intuition has more to do with the emotional and instinctive side of us and logic is more related to our cognition and thinking. Good problem solvers use both of these forces to get as much information as they can to come up with the best possible solution. In addition, they are reasonably open minded but logically skeptical.

Some of the general characteristics of good problem solvers are:

1. They don't need to be right all the time: They focus on finding the right solution rather than wanting to prove they are right at all costs.

2. They go beyond their own conditioning: They go beyond a fixated mind set and open up to new ways of thinking and can explore options.

3. They look for opportunity within the problem: They see problems as challenges and try to learn from them.

4. They know the difference between complex and simple thinking: They know when to do a systematic and complex thinking and when to go through short cuts and find an easy solution.

5. They have clear definition of what the problem is: They can specifically identity the problem.

6. They use the power of words to connect with people: They are socially well developed and find ways to connect with people and try to find happy-middle solutions.

7. They don't create problems for others: They understand that to have their problem solved they can't create problems for others. Good problems solvers who create fair solutions make a conscious effort not to harm others for a self-interest intention. They know such acts will have long term consequences even if the problem is temporarily solved.

8. They do prevention more than intervention: Good problem solvers have a number of skills to prevent problems from happening in the first place. They usually face less drama, conflict, and stressful situations since they have clear boundaries, don't let their rights violated and do not violate other people's rights. They are more of a positive thinker so naturally they are surrounded with more positivity and have more energy to be productive.

9. They explore their options: They see more than one solution to a problem and find new and productive ways to deal with new problems as they arise. They also have a backup plan if the first solution does not work and can ask for support and advise when needed.

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10. They have reasonable expectations: Good problem solvers have reasonable expectations as to what the solution would be. They understand that there are many elements effecting a situation and that idealistic ways of thinking and going about solving a problem will be counterproductive.

At the end, good problem solvers do not have too many irrational fears when dealing with problems. They can visualize the worst case scenario, work their way out of it and let go of the fear attached to it. Fear can make your logic and intuition shady and your decisions unproductive.

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Characteristics of Artificial Intelligence Problems

Problems in Artificial Intelligence (AI) come in different forms, each with its own set of challenges and potential for innovation. From image recognition to natural language processing, AI problems exhibit distinct characteristics that shape the strategies and techniques used to tackle them effectively. In this article, we delve into the fundamental characteristics of AI problems, providing light on what makes them so fascinating and formidable.

Table of Content

Key Terminologies in Artificial Intelligence Problems

Addressing the challenges of ai problems, examples of ai applications and challenges across domains, characteristics of artificial intelligence problems - faqs.

Before exploring the characteristics, let's clarify some essential AI concepts:

• Problem-solving: Problem-solving is a process that is a solution provided to a complex problem or task. When dealing with AI, problem-solving involves creating algorithms and methods of artificial intelligence that will empower machines to imitate humans’ capabilities of logical and reasonable thinking in certain situations.
• Search Space: Searching space refers to the area where an agent involved in the problem-solving process can examine all the possible states or settings with the hope of discovering a solution. It covers a gamut of options that the agent might select for arriving at the same destination.
• State: An entity represents some unique and specific arrangement of elements in a problem-solving situation. States can be assigned to different locations, challenges, or dangers that the problem-solving agent faces while looking for a solution to the problem within the search space.
• Search Algorithm: A search algorithm describes any process or method targeted for examining and exploring the given problem space to find a solution. Algorithm decision-making has diverging levels of complexity and effectiveness. They are studied to help in the discovery of the most suitable results.
• Heuristic: Heuristic is a thumb rule or guiding principle that is used to make intelligent decisions or solve the problems that are encountered during the process. Applying heuristics in AI is prevalent in prioritizing search paths or evaluating probable solutions based on their likelihood of finishing successfully.
• Optimization: The problem of optimization implies finding the best solution for process selection among the set of feasible alternatives submitted to some previously set objectives or criteria. AI optimization approaches are employed to deal optimally with complex issues through performance and efficiency improvement.

By understanding these key terminologies, we can better grasp the characteristics of AI problems and the techniques used to address them. These concepts form the foundation of AI problem-solving and provide the framework for developing innovative solutions to real-world challenges.

Let's explore the core characteristics that differentiate AI problems:

• Learning and adaptation: AI systems should be capable of learning from data or experiences and adapting their behaviour accordingly. This enables them to improve performance over time and handle new situations more effectively.
• Complexity: AI problems often involve dealing with complex systems or large amounts of data. AI systems must be able to handle this complexity efficiently to produce meaningful results.
• Uncertainty: AI systems frequently operate in environments where outcomes are uncertain or incomplete information is available. They must be equipped to make decisions or predictions under such conditions.
• Dynamism: Environments in which AI systems operate can change over time. These changes may occur unpredictably or according to specific rules, requiring AI systems to continually adjust their strategies or models.
• Interactivity : Many AI applications involve interaction with users or other agents. Effective AI systems should be able to perceive, interpret, and respond to these interactions in a meaningful way.
• Context dependence: The behavior or performance of AI systems may depend on the context in which they operate. Understanding and appropriately responding to different contexts is essential for achieving desired outcomes.
• Multi-disciplinary: AI problems often require knowledge and techniques from multiple disciplines, including computer science, mathematics, statistics, psychology, and more. Integrating insights from these diverse fields is necessary for developing effective AI solutions.
• Goal-oriented Design: AI systems are typically designed to achieve specific objectives or goals. Designing AI systems with clear objectives in mind helps guide the development process and ensures that the resulting systems are focused on achieving meaningful outcomes.

These characteristics collectively shape the challenges and opportunities involved in developing and deploying AI systems across various domains and applications.

The characteristics of AI problems present unique challenges that require innovative approaches to solution development. Some of the key aspects to consider in tackling these challenges include:

• Complexity and Uncertainty: AI difficulties are sometimes characterized by highly variable domains that are difficult to predict exactly. Hence, AI algorithms should be installed with the skill of dealing with unclear circumstances and should make decisions that are based on imperfect data or noisy information.
• Algorithmic Efficiency: Among the key challenges of this approach are the enormous search spaces, computational resources, and the efficiency of the algorithms in terms of problem-solving. Strategies like caching, pruning, and parallelization are among the most widely used implementations for better algorithmic speed.
• Domain Knowledge Integration: Such numerous AI problems involve the ability to capture the rules and reasoning of the real world to model and solve the questions correctly. The AI machines that have been trained with expertise from relevant domains improve the accuracy and effectiveness of the applications in the real world.
• Scalability and Adaptability: AI solutions should be able to process large datasets and complex cases at the same time, and they should also be versatile by responding to shifts in conditions and requirements. Strategies such as machine learning and reinforcement learning allow systems to do more than just perform according to the given tasks at hand; they empower systems to learn and progress over time.
• Ethical and Social Implications: AI technologies elicit ethical and social limitations concerning problems of bias, justice, privacy, and responsible office. Taking these implications into account, along with ethical frameworks, compliance frameworks, and stakeholder engagement, is essential. This approach will help position cryptocurrencies as a secure and trustworthy investment.
• Interpretability and Explainability: To achieve interpretability and explainability of AI algorithms for the sake of understanding and confidence among users and stakeholders, these algorithms should be knowable and comprehensible enough. Examples like chatbots producing natural-like conversation could better clarify the working scheme of AI technology.
• Robustness and Resilience: AI machinery should perform against its being hacked or affected by adversarial attacks, inaccuracies (errors), and environmental changes. Robustness testing, the construction of mechanisms for error handling, and the building up of redundancy must be taken seriously by AI systems to ensure their reliability and stability.
• Human-AI Collaboration: Successful human-AI entente is the key component to making the most of our advantages as well as artificial intelligence skills. Achieving AI solutions that are capable of supporting human skills and more importantly, preferences will reduce human efforts correspondingly and bring the best performance.

By addressing these challenges through innovative methodologies and interdisciplinary collaboration, we can harness the full potential of AI to solve complex problems and drive societal progress.

1. Robotics

Problem: A delivery robot navigating a busy warehouse to locate and retrieve a specific item.

Characteristics:

• Complexity: Industrial storage is networked, in the middle of things, with obstacles, and other robots and people moving unpredictably. This robot must process the visual scene, plan the route effectively, and detect and avoid possible collisions.
• Dynamism: A combination of outside factors leads to change, which is a constant inside the warehouse. Unpredictable system failures or spontaneous tasks can make the robot change its means and decision-making at the moment of need.
• Uncertainty: Sensor data (such as images obtained from a camera) might be noisy, incomplete, and unstable. The robot could be handling decisions based on fragmented or formless pieces of information.

2. Natural Language Processing (NLP)

Problem: A sentiment analysis system in NLP classifying customer reviews as positive, negative, or neutral.

• Subjectivity: Human language is nuanced. Sarcasm, irony, and figurative expressions can be difficult for machines to accurately interpret.
• Need for Context: Understanding sentiment may depend on cultural references, product-specific knowledge, or even the reviewer's prior interactions with the company.
• Ambiguity: A single word or phrase could have multiple meanings, affecting the overall sentiment of the text.

3. Computer Vision

Problem: A medical image recognition system in Computer Vision designed to detect tumors in X-rays or MRI scans.

• Complexity: Medical images are highly detailed and can exhibit subtle variations. The system needs to distinguish between healthy tissue and potential abnormalities.
• Uncertainty: Images may contain noise or artifacts. The presence of a tumor might not be immediately obvious, requiring the system to handle ambiguity.
• Ethical Considerations: False positives or false negatives have serious consequences for patient health. Accuracy, transparency, and minimizing bias are crucial.

The premises of AI-based problems – complexity, uncertainty, subjectivity, and more, – bring an unavoidable difficulty to the table. These features must be known for building appropriate AI because this is necessary. Through the use of machine learning, probabilistic reasoning, and knowledge representation which are referred to as the tools in AI development alongside the ethical considerations, these designers and scientists can face such complexities well and give shape to AI in a way that will be beneficial to society.

Q. What are the core characteristics that differentiate AI problems?

The core characteristics of AI problems include complexity, uncertainty and ambiguity, lack of clear problem definition, non-linearity, dynamism, subjectivity, interactivity, context sensitivity, and ethical considerations.

Q. Can you explain the concept of problem-solving in AI?

Problem-solving in AI involves creating algorithms and methods that enable machines to imitate human capabilities of logical and reasonable thinking in certain situations.

Q. What is meant by the term "search space" in AI?

Search space refers to the area where an agent involved in the problem-solving process can examine all the possible states or settings with the hope of discovering a solution.

Q. How do AI algorithms address challenges such as complexity and uncertainty?

AI algorithms are designed to handle unclear circumstances and make decisions based on imperfect data or noisy information.

Q. What are some examples of AI applications and the challenges they face?

Examples include robotics (e.g., delivery robots navigating busy warehouses), natural language processing (e.g., sentiment analysis of customer reviews), and computer vision (e.g., medical image recognition for detecting tumors).

Q. What role do ethical considerations play in AI development?

Ethical considerations are crucial in AI development to address issues such as bias, justice, privacy, and responsibility, ensuring that AI technologies are deployed responsibly and ethically.

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Problem-Solving Mastery: Your Roadmap to Effective Solutions

• Job Skills , Life skills , Soft skills

In today’s rapidly evolving world, problem-solving skills have become more critical. The ability to identify, analyze, and find effective solutions to complex challenges is highly valued across various domains, including education, business, and personal life. Problem-solving skills empower individuals to overcome obstacles, make informed decisions, and confidently navigate uncertain situations. They are key personal and professional success drivers, enabling individuals to adapt to change, innovate, and seize opportunities.

This article will delve into the essential steps for mastering problem-solving skills. We will explore the characteristics of effective problem solvers and highlight the step-by-step process they follow to tackle problems. From defining the problem and gathering information to evaluating solutions and implementing the chosen course of action, we will cover each stage in detail, providing valuable insights and practical strategies. Additionally, we will discuss various techniques and tools that can enhance problem-solving abilities and address common challenges individuals encounter. Whether you are a student, professional, or simply looking to enhance your problem-solving skills, this article will serve as a comprehensive guide to equip you with the necessary knowledge and techniques to become a proficient problem solver.

Understanding Problem Solving

A. definition of problem-solving.

Problem-solving is a fundamental skill applicable across diverse academic, professional, and personal contexts. It plays a crucial role in business, science, engineering, and everyday life, enabling individuals to overcome obstacles, achieve goals, and improve outcomes.

Here are some definitions with sources-

“Problem-solving is the cognitive process of identifying, analyzing, and resolving obstacles or difficulties encountered to achieve a desired goal or outcome.”

  Source: – Simon, H. A. (1972). Theories of Bounded Rationality. Decision and Organization, 1(1), 161-176.

  “Problem-solving refers to the systematic approach of finding solutions to challenges by utilizing logical thinking, analytical skills, and creativity.”

Source: – D’Zurilla, T. J., & Nezu, A. M. (2007). Problem-Solving Therapy: A Positive Approach to Clinical Intervention. Springer Publishing Company.

  “Problem-solving is the cognitive process of identifying, analyzing, and overcoming obstacles through the application of problem-solving strategies, critical thinking , and decision-making skills.”

Source: – Fogler, H. S., LeBlanc, S. E., & Rizzo, E. (2020). Strategies for Creative Problem Solving. Pearson.

“Problem-solving involves the ability to define problems, generate potential solutions, evaluate alternatives, and implement the best course of action, resulting in effective decision making and successful resolution of challenges.”

Source: –  Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How People Learn: Brain, Mind, Experience, and School : Expanded Edition. National Academies Press.

B. The role of problem-solving in personal and professional life

The Role of Problem-Solving in Personal and Professional Life:

1. Personal Life:

   a. Decision Making: Problem-solving is crucial in making informed decisions about personal matters, such as career choices, relationships, and financial planning.

   b. Resolving Conflicts: Effective problem-solving skills help resolve conflicts and disputes, fostering healthier relationships and communication.

   c. Adaptability: Problem-solving enables individuals to navigate life’s challenges and adapt to changing circumstances, enhancing personal growth and resilience.

   d. Goal Achievement: By identifying obstacles and finding solutions, problem-solving helps individuals overcome barriers and progress towards achieving personal goals.

2. Professional Life:

   a. Innovation and Creativity: Problem-solving is at the core of innovation, enabling individuals to identify opportunities, develop new ideas, and implement creative solutions.

   b. Decision Making: Effective problem-solving skills aid in making sound business decisions, analyzing data, and evaluating options to achieve desired outcomes.

   c. Troubleshooting and Crisis Management : Problem-solving is crucial in addressing workplace issues, identifying root causes, and implementing solutions to operational challenges and crises.

   d. Collaboration and Teamwork: Problem-solving skills facilitate effective collaboration and teamwork, as individuals work together to analyze problems, generate ideas, and implement solutions.

   e. Continuous Improvement: By identifying inefficiencies and finding better solutions, problem-solving drives continuous improvement in processes, products, and services.

   f. Leadership: Strong problem-solving abilities are essential for effective leadership, as leaders navigate complex situations, inspire teams, and drive organizational success.

Overall, problem-solving is vital in personal and professional life, empowering individuals to overcome obstacles, make informed decisions, foster innovation, and achieve desired outcomes. It promotes adaptability, resilience, and growth, enhancing overall success and satisfaction in various aspects of life.

Characteristics of Effective Problem Solvers

Here are some Characteristics of Effective Problem Solvers:

1. Critical Thinking: Effective problem solvers possess strong critical thinking skills. They can analyze situations objectively, evaluate information, identify patterns, and make logical connections to understand the underlying causes of problems.

2. Analytical Skills: Effective problem solvers can break down complex problems into smaller, more manageable components. They can examine each component individually, identify relevant factors, and assess their interrelationships to understand the problem comprehensively.

3. Creativity and Innovative Thinking: Effective problem solvers think outside the box and are open to unconventional ideas and solutions. They approach problems creatively, seeking new perspectives, alternative approaches, and innovative solutions.

4. Persistence and Resilience: Effective problem solvers persevere when facing obstacles and setbacks. They are resilient and maintain a positive attitude, viewing challenges as opportunities for growth and learning rather than insurmountable barriers.

5. Adaptability and Flexibility: Effective problem solvers are adaptable and flexible in their thinking and approach. They are open to adjusting their strategies, considering different viewpoints, and embracing change as they navigate complex problem-solving situations.

6. Systems Thinking: Effective problem solvers consider the larger context and understand the interconnectedness of various factors. They can see how different elements within a system influence each other and recognize the ripple effects of their decisions and actions.

7. Collaboration and Communication: Effective problem solvers are skilled in collaboration and communication. They actively listen to others, seek input and feedback, and can articulate their thoughts and ideas clearly. They can work well in teams, leveraging diverse perspectives and expertise to find optimal solutions.

8. Decision Making: Effective problem solvers are proficient in decision-making . They gather relevant information, weigh different options, assess risks and benefits, and make informed choices based on a logical and rational evaluation process.

9. Continuous Learning: Effective problem solvers have a growth mindset and a thirst for knowledge. They actively seek opportunities to learn new skills, expand their knowledge base, and stay updated on industry trends and advancements.

10. Emotional Intelligence: Effective problem solvers possess emotional intelligence, allowing them to understand and manage their emotions and empathize with others. They can navigate interpersonal dynamics, handle conflicts constructively, and foster positive relationships while solving problems.

These characteristics collectively contribute to the effectiveness of problem solvers, enabling them to approach challenges with a systematic, innovative, and resilient mindset, ultimately leading to successful problem resolution and achieving desired outcomes.

The Problem-Solving Process

Here is The Problem-Solving Process Step by Step:

Step 1: Defining the Problem:

1. Identifying the root cause: To effectively solve a problem, it’s important to identify the underlying cause or causes. This involves digging deeper to understand the factors or circumstances that led to the problem’s occurrence.

2. Clarifying the desired outcome: Clearly defining the desired outcome provides a clear direction for problem-solving. It helps in setting goals and measuring the success of the solution.

Step 2: Gathering information and analyzing the situation:

1. Collecting relevant data and facts: Gathering relevant data and facts about the problem is crucial for making informed decisions. This involves collecting information from reliable sources, conducting surveys, interviews, or analyzing existing data.

2. Conducting research and seeking different perspectives: Researching the problem and seeking different perspectives allows for a comprehensive understanding of the situation. This may involve studying case studies, consulting experts, or getting insights from people who have faced similar challenges.

Step 3: Generating potential solutions:

1. Brainstorming techniques: Brainstorming involves generating many ideas without judgment. It encourages creativity and open-mindedness, allowing for the exploration of various solutions.

2. Considering multiple options: Considering multiple options helps in expanding the range of possibilities. It involves evaluating different approaches, strategies, or alternatives to find the most effective solution.

Step 4: Evaluating and selecting the best solution:

1. Assessing pros and cons: Evaluating the potential solutions involves assessing their advantages and disadvantages. This helps in understanding the potential benefits and drawbacks of each option.

2. Using decision-making tools and techniques: Decision-making tools and techniques, such as decision matrices, cost-benefit analysis, or SWOT analysis, can provide a structured approach to evaluating and comparing different solutions. They help in making an informed decision.

Step 5: Implementing the chosen solution:

1. Developing an action plan: A detailed action plan outlines the steps and tasks needed to implement the chosen solution. It includes setting deadlines, assigning responsibilities, and allocating necessary resources.

2. Overcoming potential obstacles: Anticipating potential obstacles and challenges helps develop contingency plans. By identifying potential barriers in advance, proactive measures can be taken to overcome them and ensure a smoother implementation process.

Step 6: Monitoring and evaluating the outcomes:

1. Assessing the solution’s effectiveness: Regularly monitoring and evaluating the outcomes of the implemented solution is crucial. This involves measuring the results against the desired outcome and assessing whether the solution effectively addresses the problem.

2. Making adjustments if necessary: If the desired outcomes are not achieved or new issues arise, it may be necessary to adjust the solution or implementation plan. This ensures continuous improvement and adaptability throughout the problem-solving process.

By following this step-by-step process, individuals and teams can approach problem-solving systematically and comprehensively, increasing the chances of finding effective solutions and achieving desired outcomes.

Techniques and Strategies for Effective Problem Solving

Here are some Techniques and Strategies for Effective Problem Solving:

A. SWOT analysis (Strengths, Weaknesses, Opportunities, Threats):

SWOT analysis is a widely used technique for understanding a situation or organization’s internal strengths and weaknesses and the external opportunities and threats it faces. It involves identifying and analyzing these four factors to gain insights into the current state and potential future scenarios. One can effectively capitalize on opportunities and mitigate threats by understanding strengths and weaknesses.

B. Root cause analysis:

Root cause analysis is a technique used to identify the underlying cause or causes of a problem. It involves digging deeper into the problem to determine the fundamental reasons for its occurrence. By identifying and addressing the root cause, rather than just treating symptoms, one can prevent the problem from recurring and find long-term solutions.

C. Pareto analysis:

Pareto analysis, also known as the 80/20 rule, is a technique that helps prioritize tasks or issues based on their significance. It involves identifying the vital few (20%) contributing to the majority (80%) of the problem. One can achieve the greatest impact with limited resources by focusing efforts on addressing the most significant factors.

D. Six Thinking Hats technique:

The Six Thinking Hats technique, developed by Edward de Bono, is a method for approaching problem-solving from different perspectives. Each “hat” represents a different thinking mode or mindset, such as logical, creative, critical, etc. By consciously adopting these different perspectives, individuals or teams can explore different angles, consider various factors, and enhance problem-solving.

E. Design thinking approach:

The design thinking approach is a human-centered problem-solving methodology. It emphasizes empathy, collaboration, and experimentation to understand the user’s needs, ideate innovative solutions, and iterate through prototypes. It involves several stages, including empathizing with users, defining the problem, ideating potential solutions, prototyping, and testing. This approach encourages a creative and iterative problem-solving process that delivers solutions meeting user needs.

By utilizing these techniques and strategies for effective problem-solving, individuals and teams can enhance their problem-solving capabilities, think more critically and creatively, and arrive at comprehensive and innovative solutions to address various challenges.

Overcoming Common Challenges in Problem-Solving 

Now we discuss how to overcome Common Challenges in Problem-Solving:

A. Emotional barriers and biases:

1. Self-awareness: Recognize and acknowledge your emotions and biases that may hinder the problem-solving process.

2. Objective perspective: Strive to approach problems with an open mind and consider alternative viewpoints.

3. Seek feedback: Involve others in problem-solving to gain diverse perspectives and challenge your biases.

B. Fear of failure and risk aversion:

1. Embrace a growth mindset: View failures as learning opportunities and be open to taking calculated risks.

2. Break problems into smaller steps: Breaking down complex problems into smaller, manageable tasks can help reduce the Fear of failure.

3. Experiment and iterate: Implement solutions in iterative stages, allowing for adjustments and learning from setbacks.

C. Lack of communication and collaboration:

1. Active listening: Listen attentively to others’ perspectives, fostering effective communication and understanding.

2. Encourage participation: Create a supportive environment where everyone feels comfortable contributing ideas and insights.

3. Foster teamwork: Promote collaboration and establish clear roles and responsibilities within problem-solving teams.

D. Ineffective time management:

1. Prioritize tasks: Identify the most critical aspects of the problem and allocate time accordingly.

2. Set deadlines and milestones: Establish specific deadlines for each step of the problem-solving process to stay on track.

3. Avoid distractions: Minimize interruptions and focus on the task by creating a conducive work environment.

By addressing these common problem-solving challenges, individuals and teams can enhance their problem-solving effectiveness and achieve better outcomes. Overcoming emotional barriers and biases, embracing risk-taking, fostering effective communication and collaboration, and managing time efficiently are key factors in successful problem-solving endeavors. By developing strategies to tackle these challenges, individuals can unlock their problem-solving potential and approach challenges with confidence and resilience.

Developing Problem-Solving Skills 

Is it possible to develop problem-solving skills? Yes, it is possible. But How? 

A. Continuous learning and skill development:

1. Stay curious: Cultivate a continuous learning mindset by seeking new knowledge, exploring different perspectives, and staying updated on industry trends.

2. Acquire relevant knowledge: Develop a solid foundation in the areas relevant to problem-solving, such as critical thinking, analytical skills, creativity, and decision-making.

3. Pursue professional development: Attend workshops, training programs, and online courses on problem-solving techniques and strategies.

B. Seeking feedback and reflection:

1. Welcome constructive criticism: Seek feedback from peers, mentors, or supervisors to gain insights into areas for improvement in your problem-solving approach.

2. Reflect on past experiences: Evaluate your problem-solving efforts, identify strengths and weaknesses, and learn from your successes and failures.

3. Develop self-awareness: Understand your thinking patterns, biases, and emotional reactions to improve your problem-solving skills.

C. Practicing problem-solving exercises and scenarios:

1. Solve puzzles and brain teasers: Engage in activities that challenge your problem-solving abilities, such as puzzles, riddles, or logic games.

2. Simulate problem-solving scenarios: Create hypothetical problem-solving situations and brainstorm potential solutions to enhance your critical thinking and decision-making skills.

3. Participate in group problem-solving activities: Collaborate with others in problem-solving exercises or workshops to foster teamwork and develop effective communication skills.

D. Engaging in real-life problem-solving experiences:

1. Embrace challenges: Seek opportunities to tackle real-world problems, whether at work, in personal projects, or community initiatives.

2. Apply problem-solving techniques: Utilize the problem-solving process and relevant strategies to address issues encountered in various aspects of life.

3. Learn from experiences: Reflect on your problem-solving approach in real-life situations, identify areas of improvement, and adjust your strategies accordingly.

Developing problem-solving skills is an ongoing process that requires continuous learning, practice, and application in both simulated and real-life scenarios. By investing time and effort in skill development, seeking feedback, reflecting on experiences, and engaging in problem-solving activities, individuals can strengthen their problem-solving abilities and effectively address complex challenges.

Applying Problem-Solving Skills in Different Areas

Now we will discuss Applying Problem-Solving Skills in Different Areas:

A. Problem-solving in the workplace:

Problem-solving skills are highly valuable in the workplace as they enable individuals to address challenges, make informed decisions, and contribute to organizational success. In a professional setting, problem-solving involves identifying and analyzing issues, generating effective solutions, and implementing them to achieve desired outcomes. It often requires collaboration, critical thinking, and creative problem-solving techniques. Effective problem-solving in the workplace can lead to increased productivity, improved teamwork, and innovation.

B. Problem-solving in personal relationships:

Problem-solving skills play a crucial role in maintaining healthy and constructive personal relationships. Conflicts and challenges are inevitable with family members, friends, or romantic partners. Applying problem-solving skills in personal relationships involves active listening, empathy, and open communication. It requires identifying and understanding the issues, finding common ground, and working towards mutually beneficial solutions. Problem-solving in personal relationships helps build trust, strengthen connections, and promote harmony.

C. Problem-solving in entrepreneurship:

Problem-solving is an essential skill for entrepreneurs, as it drives innovation and the ability to identify and seize opportunities. Entrepreneurs face various challenges, such as market competition, resource constraints, and changing customer needs. Applying problem-solving skills in entrepreneurship involves identifying market gaps, analyzing customer pain points, and developing innovative solutions. Entrepreneurs must be adaptable, resilient, and creative in finding solutions that address real-world problems and create customer value.

D. Problem-solving in everyday life:

Problem-solving skills are not limited to specific areas but are applicable in everyday life. From simple tasks to complex decisions, problem-solving helps navigate challenges efficiently. Everyday problem-solving involves assessing situations, setting goals, considering available resources, and making informed choices. It can range from troubleshooting technology issues to managing personal finances, resolving conflicts, or finding solutions to logistical problems. Developing problem-solving skills in everyday life leads to increased self-confidence, improved decision-making abilities, and overall personal effectiveness.

In all these areas, applying problem-solving skills enables individuals to approach challenges with a structured and analytical mindset, find practical solutions, and overcome obstacles effectively. It empowers individuals to think critically, adapt to changing circumstances, and positively contribute to various aspects of their lives.

Case Studies of Successful Problem Solving

Here are some Case Studies of Successful Problem Solving:

A. Real-life examples of problem-solving success stories:

1. NASA’s Apollo 13 Mission: The Apollo 13 mission faced a critical problem when an oxygen tank exploded, jeopardizing the lives of the astronauts. Through collaborative problem-solving, the NASA team on the ground and the astronauts in space worked together to develop innovative solutions, such as building a makeshift CO2 filter, conserving power, and navigating a safe return to Earth.

2. Apple’s iPhone Development: Apple faced the challenge of creating a revolutionary smartphone that combined multiple functions in a user-friendly design. Through rigorous problem-solving, Apple’s team developed groundbreaking solutions, such as the touch screen interface, intuitive user experience, and integration of various technologies, leading to the successful launch of the iPhone.

3. Toyota’s Lean Manufacturing System: Toyota encountered production inefficiencies and quality issues. By implementing problem-solving techniques, such as the Toyota Production System, the company focused on waste reduction, continuous improvement, and empowering employees to identify and solve problems. This increased productivity, improved quality, and a competitive advantage in the automotive industry.

B. Analysis of the problem-solving strategies employed:

1. Collaborative Problem-Solving: Successful problem-solving often involves collaboration among individuals or teams. Organizations can tackle complex challenges more effectively by leveraging diverse perspectives, knowledge, and skills.

2. Innovative Thinking: Problem-solving success stories often involve innovative thinking to address issues in novel ways. This may include exploring new technologies, challenging conventional wisdom, or adopting creative approaches that disrupt the status quo.

3. Systematic Approach: Effective problem-solving requires a systematic approach that involves defining the problem, gathering relevant information, analyzing options, and implementing solutions. This structured method provides a comprehensive understanding of the problem and helps identify the most appropriate action.

4. Continuous Improvement: Many successful problem-solving cases are committed to continuous improvement. Organizations embracing a learning and adaptability culture are better equipped to identify and solve problems efficiently, leading to long-term success.

5. Customer-Centric Solutions: Problem-solving strategies that prioritize understanding and meeting customer needs tend to yield successful outcomes. Organizations can develop solutions that deliver value and drive customer satisfaction by placing the customer at the center of problem-solving efforts.

Analyzing the problem-solving strategies employed in these case studies provides valuable insights into the approaches, techniques, and mindsets that contribute to successful problem resolution. It highlights the importance of collaboration, innovation, systematic thinking, continuous improvement, and customer focus in achieving positive outcomes.

Conclusion:

In conclusion, problem-solving skills are vital in various aspects of life, including personal, professional, and entrepreneurial endeavors. Through this article, we have explored the importance of problem-solving, its Definition, its role in different areas, characteristics of effective problem solvers, the problem-solving process, and techniques for effective problem-solving. We have also examined case studies of successful problem-solving and analyzed the strategies employed.

Recap of key points:

1. Problem-solving skills are crucial for personal, professional, and entrepreneurial success.

2. Effective problem solvers possess critical thinking, creativity, adaptability, and perseverance.

3. The problem-solving process involves defining the problem, gathering information, generating solutions, evaluating options, implementing the chosen solution, and monitoring outcomes.

4. Techniques like SWOT analysis, root cause analysis, Pareto analysis, Six Thinking Hats, and design thinking provide valuable frameworks for problem-solving.

As you have learned about the importance and various aspects of problem-solving, I encourage you to apply these skills in your own life. Problem-solving is not a mere intellectual exercise but a practical tool that can lead to personal growth, professional success, and positive societal contributions. Developing and honing your problem-solving abilities allows you to navigate challenges, make informed decisions, and find innovative solutions.

Embrace a continuous improvement mindset and a willingness to think outside the box. Seek opportunities to apply problem-solving skills in your relationships, workplace, entrepreneurial ventures, and everyday life. Remember that each challenge presents an opportunity for growth and learning. You can overcome obstacles and achieve desired outcomes by approaching problems with a structured and analytical mindset, considering multiple perspectives, and employing effective problem-solving techniques.

Incorporate problem-solving into your daily life and encourage others to do the same. By doing so, you contribute to a more proactive and solution-oriented society. Remember, problem-solving is a skill that can be developed and refined through practice and experience. So, take on challenges, embrace creativity, and be a proactive problem solver.

Start applying problem-solving skills today, and you will witness the positive impact it can have on your life and the lives of those around you.

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Problem-Solving Strategies and Obstacles

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Sean is a fact-checker and researcher with experience in sociology, field research, and data analytics.

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From deciding what to eat for dinner to considering whether it's the right time to buy a house, problem-solving is a large part of our daily lives. Learn some of the problem-solving strategies that exist and how to use them in real life, along with ways to overcome obstacles that are making it harder to resolve the issues you face.

What Is Problem-Solving?

In cognitive psychology , the term 'problem-solving' refers to the mental process that people go through to discover, analyze, and solve problems.

A problem exists when there is a goal that we want to achieve but the process by which we will achieve it is not obvious to us. Put another way, there is something that we want to occur in our life, yet we are not immediately certain how to make it happen.

Maybe you want a better relationship with your spouse or another family member but you're not sure how to improve it. Or you want to start a business but are unsure what steps to take. Problem-solving helps you figure out how to achieve these desires.

The problem-solving process involves:

• Discovery of the problem
• Deciding to tackle the issue
• Seeking to understand the problem more fully
• Researching available options or solutions
• Taking action to resolve the issue

Before problem-solving can occur, it is important to first understand the exact nature of the problem itself. If your understanding of the issue is faulty, your attempts to resolve it will also be incorrect or flawed.

Problem-Solving Mental Processes

Several mental processes are at work during problem-solving. Among them are:

• Perceptually recognizing the problem
• Representing the problem in memory
• Considering relevant information that applies to the problem
• Identifying different aspects of the problem
• Labeling and describing the problem

Problem-Solving Strategies

There are many ways to go about solving a problem. Some of these strategies might be used on their own, or you may decide to employ multiple approaches when working to figure out and fix a problem.

An algorithm is a step-by-step procedure that, by following certain "rules" produces a solution. Algorithms are commonly used in mathematics to solve division or multiplication problems. But they can be used in other fields as well.

In psychology, algorithms can be used to help identify individuals with a greater risk of mental health issues. For instance, research suggests that certain algorithms might help us recognize children with an elevated risk of suicide or self-harm.

One benefit of algorithms is that they guarantee an accurate answer. However, they aren't always the best approach to problem-solving, in part because detecting patterns can be incredibly time-consuming.

There are also concerns when machine learning is involved—also known as artificial intelligence (AI)—such as whether they can accurately predict human behaviors.

Heuristics are shortcut strategies that people can use to solve a problem at hand. These "rule of thumb" approaches allow you to simplify complex problems, reducing the total number of possible solutions to a more manageable set.

If you find yourself sitting in a traffic jam, for example, you may quickly consider other routes, taking one to get moving once again. When shopping for a new car, you might think back to a prior experience when negotiating got you a lower price, then employ the same tactics.

While heuristics may be helpful when facing smaller issues, major decisions shouldn't necessarily be made using a shortcut approach. Heuristics also don't guarantee an effective solution, such as when trying to drive around a traffic jam only to find yourself on an equally crowded route.

Trial and Error

A trial-and-error approach to problem-solving involves trying a number of potential solutions to a particular issue, then ruling out those that do not work. If you're not sure whether to buy a shirt in blue or green, for instance, you may try on each before deciding which one to purchase.

This can be a good strategy to use if you have a limited number of solutions available. But if there are many different choices available, narrowing down the possible options using another problem-solving technique can be helpful before attempting trial and error.

In some cases, the solution to a problem can appear as a sudden insight. You are facing an issue in a relationship or your career when, out of nowhere, the solution appears in your mind and you know exactly what to do.

Insight can occur when the problem in front of you is similar to an issue that you've dealt with in the past. Although, you may not recognize what is occurring since the underlying mental processes that lead to insight often happen outside of conscious awareness .

Research indicates that insight is most likely to occur during times when you are alone—such as when going on a walk by yourself, when you're in the shower, or when lying in bed after waking up.

How to Apply Problem-Solving Strategies in Real Life

If you're facing a problem, you can implement one or more of these strategies to find a potential solution. Here's how to use them in real life:

• Create a flow chart . If you have time, you can take advantage of the algorithm approach to problem-solving by sitting down and making a flow chart of each potential solution, its consequences, and what happens next.
• Recall your past experiences . When a problem needs to be solved fairly quickly, heuristics may be a better approach. Think back to when you faced a similar issue, then use your knowledge and experience to choose the best option possible.
• Start trying potential solutions . If your options are limited, start trying them one by one to see which solution is best for achieving your desired goal. If a particular solution doesn't work, move on to the next.
• Take some time alone . Since insight is often achieved when you're alone, carve out time to be by yourself for a while. The answer to your problem may come to you, seemingly out of the blue, if you spend some time away from others.

Obstacles to Problem-Solving

Problem-solving is not a flawless process as there are a number of obstacles that can interfere with our ability to solve a problem quickly and efficiently. These obstacles include:

• Assumptions: When dealing with a problem, people can make assumptions about the constraints and obstacles that prevent certain solutions. Thus, they may not even try some potential options.
• Functional fixedness : This term refers to the tendency to view problems only in their customary manner. Functional fixedness prevents people from fully seeing all of the different options that might be available to find a solution.
• Irrelevant or misleading information: When trying to solve a problem, it's important to distinguish between information that is relevant to the issue and irrelevant data that can lead to faulty solutions. The more complex the problem, the easier it is to focus on misleading or irrelevant information.
• Mental set: A mental set is a tendency to only use solutions that have worked in the past rather than looking for alternative ideas. A mental set can work as a heuristic, making it a useful problem-solving tool. However, mental sets can also lead to inflexibility, making it more difficult to find effective solutions.

How to Improve Your Problem-Solving Skills

In the end, if your goal is to become a better problem-solver, it's helpful to remember that this is a process. Thus, if you want to improve your problem-solving skills, following these steps can help lead you to your solution:

• Recognize that a problem exists . If you are facing a problem, there are generally signs. For instance, if you have a mental illness , you may experience excessive fear or sadness, mood changes, and changes in sleeping or eating habits. Recognizing these signs can help you realize that an issue exists.
• Decide to solve the problem . Make a conscious decision to solve the issue at hand. Commit to yourself that you will go through the steps necessary to find a solution.
• Seek to fully understand the issue . Analyze the problem you face, looking at it from all sides. If your problem is relationship-related, for instance, ask yourself how the other person may be interpreting the issue. You might also consider how your actions might be contributing to the situation.
• Research potential options . Using the problem-solving strategies mentioned, research potential solutions. Make a list of options, then consider each one individually. What are some pros and cons of taking the available routes? What would you need to do to make them happen?
• Take action . Select the best solution possible and take action. Action is one of the steps required for change . So, go through the motions needed to resolve the issue.
• Try another option, if needed . If the solution you chose didn't work, don't give up. Either go through the problem-solving process again or simply try another option.

You can find a way to solve your problems as long as you keep working toward this goal—even if the best solution is simply to let go because no other good solution exists.

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By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Problem Solving

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• David H. Jonassen 2 &
• Woei Hung 3  

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Cognition ; Problem typology ; Problem-based learning ; Problems ; Reasoning

Problem solving is the process of constructing and applying mental representations of problems to finding solutions to those problems that are encountered in nearly every context.

Theoretical Background

Problem solving is the process of articulating solutions to problems. Problems have two critical attributes. First, a problem is an unknown in some context. That is, there is a situation in which there is something that is unknown (the difference between a goal state and a current state). Those situations vary from algorithmic math problems to vexing and complex social problems, such as violence in society (see Problem Typology ). Second, finding or solving for the unknown must have some social, cultural, or intellectual value. That is, someone believes that it is worth finding the unknown. If no one perceives an unknown or a need to determine an unknown, there is no perceived problem. Finding...

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7.3 Problem-Solving

Learning objectives.

By the end of this section, you will be able to:

• Describe problem solving strategies
• Define algorithm and heuristic
• Explain some common roadblocks to effective problem solving

   People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe be doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

The study of human and animal problem solving processes has provided much insight toward the understanding of our conscious experience and led to advancements in computer science and artificial intelligence. Essentially much of cognitive science today represents studies of how we consciously and unconsciously make decisions and solve problems. For instance, when encountered with a large amount of information, how do we go about making decisions about the most efficient way of sorting and analyzing all the information in order to find what you are looking for as in visual search paradigms in cognitive psychology. Or in a situation where a piece of machinery is not working properly, how do we go about organizing how to address the issue and understand what the cause of the problem might be. How do we sort the procedures that will be needed and focus attention on what is important in order to solve problems efficiently. Within this section we will discuss some of these issues and examine processes related to human, animal and computer problem solving.

PROBLEM-SOLVING STRATEGIES

   When people are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

Problems themselves can be classified into two different categories known as ill-defined and well-defined problems (Schacter, 2009). Ill-defined problems represent issues that do not have clear goals, solution paths, or expected solutions whereas well-defined problems have specific goals, clearly defined solutions, and clear expected solutions. Problem solving often incorporates pragmatics (logical reasoning) and semantics (interpretation of meanings behind the problem), and also in many cases require abstract thinking and creativity in order to find novel solutions. Within psychology, problem solving refers to a motivational drive for reading a definite “goal” from a present situation or condition that is either not moving toward that goal, is distant from it, or requires more complex logical analysis for finding a missing description of conditions or steps toward that goal. Processes relating to problem solving include problem finding also known as problem analysis, problem shaping where the organization of the problem occurs, generating alternative strategies, implementation of attempted solutions, and verification of the selected solution. Various methods of studying problem solving exist within the field of psychology including introspection, behavior analysis and behaviorism, simulation, computer modeling, and experimentation.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them (table below). For example, a well-known strategy is trial and error. The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

   Another type of strategy is an algorithm. An algorithm is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind in the same moment

Working backwards is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C. and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backwards heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

Further problem solving strategies have been identified (listed below) that incorporate flexible and creative thinking in order to reach solutions efficiently.

Additional Problem Solving Strategies :

• Abstraction – refers to solving the problem within a model of the situation before applying it to reality.
• Analogy – is using a solution that solves a similar problem.
• Brainstorming – refers to collecting an analyzing a large amount of solutions, especially within a group of people, to combine the solutions and developing them until an optimal solution is reached.
• Divide and conquer – breaking down large complex problems into smaller more manageable problems.
• Hypothesis testing – method used in experimentation where an assumption about what would happen in response to manipulating an independent variable is made, and analysis of the affects of the manipulation are made and compared to the original hypothesis.
• Lateral thinking – approaching problems indirectly and creatively by viewing the problem in a new and unusual light.
• Means-ends analysis – choosing and analyzing an action at a series of smaller steps to move closer to the goal.
• Method of focal objects – putting seemingly non-matching characteristics of different procedures together to make something new that will get you closer to the goal.
• Morphological analysis – analyzing the outputs of and interactions of many pieces that together make up a whole system.
• Proof – trying to prove that a problem cannot be solved. Where the proof fails becomes the starting point or solving the problem.
• Reduction – adapting the problem to be as similar problems where a solution exists.
• Research – using existing knowledge or solutions to similar problems to solve the problem.
• Root cause analysis – trying to identify the cause of the problem.

The strategies listed above outline a short summary of methods we use in working toward solutions and also demonstrate how the mind works when being faced with barriers preventing goals to be reached.

One example of means-end analysis can be found by using the Tower of Hanoi paradigm . This paradigm can be modeled as a word problems as demonstrated by the Missionary-Cannibal Problem :

Missionary-Cannibal Problem

Three missionaries and three cannibals are on one side of a river and need to cross to the other side. The only means of crossing is a boat, and the boat can only hold two people at a time. Your goal is to devise a set of moves that will transport all six of the people across the river, being in mind the following constraint: The number of cannibals can never exceed the number of missionaries in any location. Remember that someone will have to also row that boat back across each time.

Hint : At one point in your solution, you will have to send more people back to the original side than you just sent to the destination.

The actual Tower of Hanoi problem consists of three rods sitting vertically on a base with a number of disks of different sizes that can slide onto any rod. The puzzle starts with the disks in a neat stack in ascending order of size on one rod, the smallest at the top making a conical shape. The objective of the puzzle is to move the entire stack to another rod obeying the following rules:

• 1. Only one disk can be moved at a time.
• 2. Each move consists of taking the upper disk from one of the stacks and placing it on top of another stack or on an empty rod.
• 3. No disc may be placed on top of a smaller disk.

  Figure 7.02. Steps for solving the Tower of Hanoi in the minimum number of moves when there are 3 disks.

Figure 7.03. Graphical representation of nodes (circles) and moves (lines) of Tower of Hanoi.

The Tower of Hanoi is a frequently used psychological technique to study problem solving and procedure analysis. A variation of the Tower of Hanoi known as the Tower of London has been developed which has been an important tool in the neuropsychological diagnosis of executive function disorders and their treatment.

GESTALT PSYCHOLOGY AND PROBLEM SOLVING

As you may recall from the sensation and perception chapter, Gestalt psychology describes whole patterns, forms and configurations of perception and cognition such as closure, good continuation, and figure-ground. In addition to patterns of perception, Wolfgang Kohler, a German Gestalt psychologist traveled to the Spanish island of Tenerife in order to study animals behavior and problem solving in the anthropoid ape.

As an interesting side note to Kohler’s studies of chimp problem solving, Dr. Ronald Ley, professor of psychology at State University of New York provides evidence in his book A Whisper of Espionage  (1990) suggesting that while collecting data for what would later be his book  The Mentality of Apes (1925) on Tenerife in the Canary Islands between 1914 and 1920, Kohler was additionally an active spy for the German government alerting Germany to ships that were sailing around the Canary Islands. Ley suggests his investigations in England, Germany and elsewhere in Europe confirm that Kohler had served in the German military by building, maintaining and operating a concealed radio that contributed to Germany’s war effort acting as a strategic outpost in the Canary Islands that could monitor naval military activity approaching the north African coast.

While trapped on the island over the course of World War 1, Kohler applied Gestalt principles to animal perception in order to understand how they solve problems. He recognized that the apes on the islands also perceive relations between stimuli and the environment in Gestalt patterns and understand these patterns as wholes as opposed to pieces that make up a whole. Kohler based his theories of animal intelligence on the ability to understand relations between stimuli, and spent much of his time while trapped on the island investigation what he described as  insight , the sudden perception of useful or proper relations. In order to study insight in animals, Kohler would present problems to chimpanzee’s by hanging some banana’s or some kind of food so it was suspended higher than the apes could reach. Within the room, Kohler would arrange a variety of boxes, sticks or other tools the chimpanzees could use by combining in patterns or organizing in a way that would allow them to obtain the food (Kohler & Winter, 1925).

While viewing the chimpanzee’s, Kohler noticed one chimp that was more efficient at solving problems than some of the others. The chimp, named Sultan, was able to use long poles to reach through bars and organize objects in specific patterns to obtain food or other desirables that were originally out of reach. In order to study insight within these chimps, Kohler would remove objects from the room to systematically make the food more difficult to obtain. As the story goes, after removing many of the objects Sultan was used to using to obtain the food, he sat down ad sulked for a while, and then suddenly got up going over to two poles lying on the ground. Without hesitation Sultan put one pole inside the end of the other creating a longer pole that he could use to obtain the food demonstrating an ideal example of what Kohler described as insight. In another situation, Sultan discovered how to stand on a box to reach a banana that was suspended from the rafters illustrating Sultan’s perception of relations and the importance of insight in problem solving.

Grande (another chimp in the group studied by Kohler) builds a three-box structure to reach the bananas, while Sultan watches from the ground.  Insight , sometimes referred to as an “Ah-ha” experience, was the term Kohler used for the sudden perception of useful relations among objects during problem solving (Kohler, 1927; Radvansky & Ashcraft, 2013).

Solving puzzles.

   Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below (see figure) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

How long did it take you to solve this sudoku puzzle? (You can see the answer at the end of this section.)

   Here is another popular type of puzzle (figure below) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Did you figure it out? (The answer is at the end of this section.) Once you understand how to crack this puzzle, you won’t forget.

   Take a look at the “Puzzling Scales” logic puzzle below (figure below). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

What steps did you take to solve this puzzle? You can read the solution at the end of this section.

Pitfalls to problem solving.

   Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Albert Einstein once said, “Insanity is doing the same thing over and over again and expecting a different result.” Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but she just needs to go to another doorway, instead of trying to get out through the locked doorway. A mental set is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now.

Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

   Researchers have investigated whether functional fixedness is affected by culture. In one experiment, individuals from the Shuar group in Ecuador were asked to use an object for a purpose other than that for which the object was originally intended. For example, the participants were told a story about a bear and a rabbit that were separated by a river and asked to select among various objects, including a spoon, a cup, erasers, and so on, to help the animals. The spoon was the only object long enough to span the imaginary river, but if the spoon was presented in a way that reflected its normal usage, it took participants longer to choose the spoon to solve the problem. (German & Barrett, 2005). The researchers wanted to know if exposure to highly specialized tools, as occurs with individuals in industrialized nations, affects their ability to transcend functional fixedness. It was determined that functional fixedness is experienced in both industrialized and nonindustrialized cultures (German & Barrett, 2005).

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000 home? Why would the realtor show you the run-down houses and the nice house? The realtor may be challenging your anchoring bias. An anchoring bias occurs when you focus on one piece of information when making a decision or solving a problem. In this case, you’re so focused on the amount of money you are willing to spend that you may not recognize what kinds of houses are available at that price point.

The confirmation bias is the tendency to focus on information that confirms your existing beliefs. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in the table below.

Were you able to determine how many marbles are needed to balance the scales in the figure below? You need nine. Were you able to solve the problems in the figures above? Here are the answers.

   Many different strategies exist for solving problems. Typical strategies include trial and error, applying algorithms, and using heuristics. To solve a large, complicated problem, it often helps to break the problem into smaller steps that can be accomplished individually, leading to an overall solution. Roadblocks to problem solving include a mental set, functional fixedness, and various biases that can cloud decision making skills.

References:

Openstax Psychology text by Kathryn Dumper, William Jenkins, Arlene Lacombe, Marilyn Lovett and Marion Perlmutter licensed under CC BY v4.0. https://openstax.org/details/books/psychology

Review Questions:

1. A specific formula for solving a problem is called ________.

a. an algorithm

b. a heuristic

c. a mental set

d. trial and error

2. Solving the Tower of Hanoi problem tends to utilize a  ________ strategy of problem solving.

a. divide and conquer

b. means-end analysis

d. experiment

3. A mental shortcut in the form of a general problem-solving framework is called ________.

4. Which type of bias involves becoming fixated on a single trait of a problem?

a. anchoring bias

b. confirmation bias

c. representative bias

d. availability bias

5. Which type of bias involves relying on a false stereotype to make a decision?

6. Wolfgang Kohler analyzed behavior of chimpanzees by applying Gestalt principles to describe ________.

a. social adjustment

b. student load payment options

c. emotional learning

d. insight learning

7. ________ is a type of mental set where you cannot perceive an object being used for something other than what it was designed for.

a. functional fixedness

c. working memory

Critical Thinking Questions:

1. What is functional fixedness and how can overcoming it help you solve problems?

2. How does an algorithm save you time and energy when solving a problem?

Personal Application Question:

1. Which type of bias do you recognize in your own decision making processes? How has this bias affected how you’ve made decisions in the past and how can you use your awareness of it to improve your decisions making skills in the future?

anchoring bias

availability heuristic

confirmation bias

functional fixedness

hindsight bias

problem-solving strategy

representative bias

trial and error

working backwards

Answers to Exercises

algorithm:  problem-solving strategy characterized by a specific set of instructions

anchoring bias:  faulty heuristic in which you fixate on a single aspect of a problem to find a solution

availability heuristic:  faulty heuristic in which you make a decision based on information readily available to you

confirmation bias:  faulty heuristic in which you focus on information that confirms your beliefs

functional fixedness:  inability to see an object as useful for any other use other than the one for which it was intended

heuristic:  mental shortcut that saves time when solving a problem

hindsight bias:  belief that the event just experienced was predictable, even though it really wasn’t

mental set:  continually using an old solution to a problem without results

problem-solving strategy:  method for solving problems

representative bias:  faulty heuristic in which you stereotype someone or something without a valid basis for your judgment

trial and error:  problem-solving strategy in which multiple solutions are attempted until the correct one is found

working backwards:  heuristic in which you begin to solve a problem by focusing on the end result

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