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code📚 Cognitive Psychology ├── 📖 Chapter 1: Defining Problems and the Gestalt Approach │ ├── 🔹 What is a Problem? │ ├── 🔹 Representing a Problem in the Mind │ ├── 🔹 Insight in Problem Solving │ └── 🔹 Obstacles to Problem Solving ├── 📖 Chapter 2: The Information-Processing Approach │ ├── 🔹 Problem Space Theory │ ├── 🔹 Means-End Analysis │ └── 🔹 Think-Aloud Protocol ├── 📖 Chapter 3: Using Analogies to Solve Problems │ ├── 🔹 Analogical Transfer │ ├── 🔹 Factors Affecting Analogical Transfer │ ├── 🔹 Analogical Encoding │ └── 🔹 Analogy in the Real World ├── 📖 Chapter 4: Expertise and Problem Solving │ ├── 🔹 Characteristics of Expertise │ ├── 🔹 Differences in Knowledge Organization │ └── 🔹 Disadvantages of Expertise └── 📖 Chapter 5: Creative Problem Solving ├── 🔹 Defining Creativity ├── 🔹 Practical Creativity and Analogical Thinking ├── 🔹 Generating Ideas and Brainstorming ├── 🔹 Creative Cognition └── 🔹 Brain Networks and Creativity
What this chapter covers: This chapter introduces the concept of a problem from a psychological perspective, emphasizing the role of representation and restructuring in problem-solving. It explores the Gestalt approach, focusing on insight and obstacles like functional fixedness and mental set. Understanding these concepts is crucial for effective problem-solving.
| Concept/Principle | Definition/Explanation | Applications | Exam Relevance |
|---|---|---|---|
| Problem | An obstacle between a present state and a desired goal where the solution is not immediately obvious. | Solving math problems, resolving conflicts. | Identifying problem components, defining challenges. |
| Representation | How a problem is mentally structured, including givens, goals, and obstacles. | Visualizing a puzzle, outlining project requirements. | Understanding problem framing, restructuring for solutions. |
| Insight | The sudden realization of a problem's solution, often involving restructuring. | Solving riddles, "aha!" moments in research. | Recognizing insight problems, differentiating from non-insight. |
| Functional Fixedness | Cognitive bias limiting object use to traditional functions. | Overcoming limitations in the candle problem. | Identifying obstacles to problem-solving, promoting flexible thinking. |
Type A: Insight Problems
Setup: "When you encounter a problem requiring a sudden 'aha!' moment" Method: "Try restructuring the problem representation, consider different perspectives, and avoid fixating on initial assumptions." Example: The two-string problem - tie pliers to one string to create a pendulum.
Type B: Overcoming Functional Fixedness
Setup: "If given a problem where objects have a seemingly fixed use" Method: "Actively try to think of alternative uses for the objects provided. Break free from conventional thinking." Example: The candle problem - using the box as a platform instead of just a container.
Problem: You have two ropes. Each takes exactly one hour to burn completely, but they don't burn at a constant rate. How can you measure exactly 45 minutes?
Given: Two ropes, each burning for one hour.
Steps:
"✅Answer: 45 minutes.
❌ Mistake 1: Failing to restructure the problem representation. ✅ How to avoid: Actively seek alternative perspectives and challenge initial assumptions.
❌ Mistake 2: Getting stuck on functional fixedness. ✅ How to avoid: Brainstorm alternative uses for objects and consider unconventional solutions.
Practice solving various insight problems to improve your ability to restructure problem representations and generate creative solutions.
What this chapter covers: This chapter explores the information-processing approach to problem-solving, focusing on problem space theory and means-end analysis. It explains how problems are solved by searching a problem space and using strategies to reduce the difference between the current state and the goal state. The think-aloud protocol is also introduced as a research method.
| Concept/Principle | Definition/Explanation | Applications | Exam Relevance |
|---|---|---|---|
| Problem Space | The initial state, goal state, and all possible intermediate states in problem-solving. | Planning a trip, designing a software program. | Identifying states and operators, understanding problem complexity. |
| Operators | Actions that transform one state into another within the problem space. | Moving pieces in a puzzle, executing code in programming. | Applying operators effectively, optimizing solution paths. |
| Means-End Analysis | A problem-solving strategy that involves reducing the difference between the current state and the goal state. | Solving the Tower of Hanoi, troubleshooting a computer. | Breaking down problems into subgoals, reducing differences. |
| Think-Aloud Protocol | A research method where participants verbalize their thoughts while solving a problem. | Studying problem-solving strategies, understanding cognitive processes. | Analyzing problem-solving approaches, identifying effective strategies. |
Type A: Means-End Analysis
Setup: "When faced with a complex problem with a clear goal state" Method: "Identify the largest difference between the current state and the goal state, set a subgoal to reduce that difference, and find an operator to achieve the subgoal." Example: Solving the Tower of Hanoi puzzle.
Type B: Mapping Problem Space
Setup: "If given a problem where the possible states and actions are well-defined" Method: "Map out the problem space, including the initial state, goal state, and all possible intermediate states. Identify the operators that can be used to move between states." Example: Solving a maze.
Problem: Solve the Tower of Hanoi puzzle with 3 disks.
Given: Three disks of different sizes and three pegs.
Steps:
"✅Answer: The puzzle is solved in 7 steps.
❌ Mistake 1: Failing to define the problem space clearly. ✅ How to avoid: Identify the initial state, goal state, and possible intermediate states before attempting to solve the problem.
❌ Mistake 2: Not breaking down the problem into subgoals. ✅ How to avoid: Use means-end analysis to identify the largest difference between the current state and the goal state and set subgoals to reduce that difference.
Practice using means-end analysis on various problems to improve your ability to break down complex problems into manageable subgoals.
What this chapter covers: This chapter explores the use of analogies in problem-solving, focusing on analogical transfer, factors affecting it, and analogical encoding. It examines how solutions from similar problems can be applied to new ones and the cognitive processes involved in recognizing and mapping analogies. Real-world applications of analogy are also discussed.
| Concept/Principle | Definition/Explanation | Applications | Exam Relevance |
|---|---|---|---|
| Analogical Transfer | Using the solution from a source problem to solve a target problem. | Applying a mathematical formula to a new problem, using a business strategy in a different market. | Recognizing analogous relationships, mapping elements between problems. |
| Surface Features | Superficial similarities between problems that can hinder analogical transfer. | Focusing on the specific objects in a problem rather than the underlying structure. | Identifying distractions, focusing on structural similarities. |
| Structural Features | Underlying principles and relationships between problems that facilitate analogical transfer. | Recognizing that two problems involve the same mathematical formula or logical structure. | Identifying core principles, applying knowledge across contexts. |
| Analogical Encoding | Comparing two cases to determine similarities, improving analogical transfer. | Analyzing negotiation strategies, identifying common elements in scientific theories. | Focusing on underlying principles, improving problem-solving skills. |
Type A: Identifying Analogous Problems
Setup: "When given a target problem and several potential source problems" Method: "Identify the underlying structural features of the target problem and look for source problems with similar structural features. Ignore surface features that are not relevant to the underlying structure." Example: Using the Russian marriage problem to solve the mutilated checkerboard problem.
Type B: Applying Analogical Encoding
Setup: "If given two cases that illustrate a common principle" Method: "Compare the two cases and identify the underlying similarities. Then, apply the principle to solve a new problem." Example: Comparing trade-off and contingency negotiation strategies.
Problem: Solve Duncker's radiation problem using the fortress story as an analogy.
Given: Duncker's radiation problem and the fortress story.
Steps:
"✅Answer: Bombard the tumor with multiple low-intensity rays from different directions.
❌ Mistake 1: Focusing on surface features rather than structural features. ✅ How to avoid: Identify the underlying principles and relationships between problems.
❌ Mistake 2: Failing to map the elements of the source problem onto the target problem correctly. ✅ How to avoid: Carefully analyze the relationship between the two problems and ensure that the elements are mapped accurately.
Practice identifying analogous relationships between different types of problems to improve your analogical transfer skills.
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