What is the general process model of problem solving?
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Learn core models and stages that explain how we approach complex problems and make choices in everyday and clinical contexts.
Mastering these models enhances your ability to analyze and improve problem-solving strategies in various settings, from everyday decisions to clinical interventions. You'll understand the cognitive steps involved and how to apply them effectively to optimize outcomes.
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| # | Front | Back | Hint |
|---|---|---|---|
| 1 | What is the general process model of problem solving? | The process model of problem solving involves identifying the problem, generating potential solutions, evaluating those solutions, selecting the best one, and then implementing and monitoring it. | Think of solving a puzzle step-by-step. |
| 2 | Name the major stages in the problem-solving process according to the problem-solving cycle. | 1. Problem identification, 2. Problem definition, 3. Generation of solutions, 4. Solution evaluation, 5. Implementation, 6. Monitoring and feedback. | Break down the cycle from recognizing to solving and checking. |
| 3 | What is heuristics in decision-making? | Heuristics are mental shortcuts or rules of thumb that simplify decision-making processes, often used to reduce cognitive load but can lead to biases. | Think of quick judgments based on experience. |
| 4 | Name an example of a common heuristic used in everyday decision-making. | The availability heuristic, where people judge the likelihood of an event based on how easily examples come to mind. | Remember how people fear plane crashes after hearing about a crash, despite low statistical risk. |
| 5 | What is the difference between a heuristic and an algorithm? | An algorithm is a step-by-step procedure guaranteed to produce a correct solution, whereas heuristics are mental shortcuts that do not guarantee a correct solution but are faster and more efficient. | Algorithms are like recipes; heuristics are like guesses. |
| 6 | Define the 'Means-Ends Analysis' model of problem solving. | Means-Ends Analysis involves comparing the current state to the desired goal, then selecting actions that reduce the difference, often by breaking the problem into subproblems. | Focus on narrowing the gap to reach your goal. |
| 7 | What is the 'trial and error' approach in problem solving? | Trial and error involves attempting multiple solutions until one works, often inefficient but useful when no clear strategy exists. | Like testing keys to open a lock. |
| 8 | Describe the 'Gestalt' approach to problem solving. | Gestalt theory emphasizes the importance of restructuring and insight, where the solution often emerges suddenly after a reorganization of the problem's elements. | Think of the 'Aha!' moment. |
| 9 | What role does insight play in problem solving? | Insight refers to a sudden realization or 'eureka' moment that leads to the solution of a problem, often involving restructuring the problem in the mind. | Like suddenly seeing the answer after thinking about it differently. |
| 10 | How does the 'Dual Process Theory' explain decision-making? | Dual Process Theory posits two systems: System 1 (fast, intuitive, automatic) and System 2 (slow, deliberate, analytical), which influence decision-making processes. | Think of intuition versus careful reasoning. |
| 11 | What is the 'bounded rationality' model? | Bounded rationality suggests that cognitive limitations and environmental constraints restrict rational decision-making, leading individuals to satisfice rather than optimize. | People settle for 'good enough' solutions. |
| 12 | Explain the concept of 'satisficing'. | Satisficing involves choosing the first option that meets a satisfactory threshold, rather than searching for the optimal choice. | Settling for 'good enough' instead of perfect. |
| 13 | What is the 'heuristic–algorithm gap' in decision-making? | It refers to the discrepancy between quick, heuristic-based judgments and slower, algorithmic solutions, highlighting potential biases in heuristics. | Fast judgment vs. detailed calculation. |
| 14 | What is a 'problem space' in problem solving? | Problem space is the set of all possible states or configurations that can be reached while solving a problem, including initial, intermediate, and goal states. | Think of it as the universe of possible solutions. |
| 15 | Define 'functional fixedness' and its effect on problem solving. | Functional fixedness is a cognitive bias that limits a person to using an object only in the way it is traditionally used, hindering creative problem solving. | Difficulty seeing alternative uses for an object. |
| 16 | What is the role of 'problem representation' in problem solving? | Effective problem representation involves mentally framing the problem clearly, which facilitates solution generation and evaluation. | How you see the problem influences your approach. |
| 17 | Describe the 'problem-solving heuristics' commonly used. | Common heuristics include the availability heuristic, representativeness heuristic, and anchoring and adjustment heuristic, which simplify decisions but can introduce biases. | Shortcuts that can mislead. |
| 18 | What is the 'confirmation bias' in decision-making? | Confirmation bias is the tendency to seek, interpret, and remember information that confirms pre-existing beliefs, which can hinder objective problem solving. | Looking for evidence that supports your opinion. |
| 19 | How does the 'problem-solving approach' differ in clinical versus everyday contexts? | In clinical contexts, problem solving often involves systematic assessment and tailored interventions, while in everyday life, it tends to be more heuristic and intuitive. | Structured vs. spontaneous decision processes. |
| 20 | What is 'decision fatigue' and how does it affect problem solving? | Decision fatigue refers to the deteriorating quality of decisions after a long session of decision making, leading to impulsivity or avoidance. | You make poorer choices the longer you decide. |
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