Cognitive Psychology: LANGUAGE AND THOUGHT

 LANGUAGE :-

Language is one of the systems through which we communicate, and it typically involves communicating through sounds and written communication with the use of symbols, but it can 

also involve our bodies (body language, how we smile, move, and approach people are all forms up for interpretation in the game of language).

LANGUAGE SKILLS CHART:-

 

THOUGHT:-

According to cognitive science, thoughts are mental representations of information that help you make sense of the world. The thought not only represents something but has the power to make changes in your body.

EXAMPLE :-

The way you think about things affects how you feel and behave. If you have positive, helpful thoughts, you will feel better and more likely to do something that helps you. On the other hand, if you have negative, harmful thoughts, you will feel worse and be more likely to do things that negatively impact your life.

WHAT COMES FIRST:LANGUAGE OR THOUGHT:-

There have been many debates regarding what comes first, language or thought. According to research, thought comes before language. A child is born with the ability to think about objects before they learn language. Although thought comes first, the language an individual speaks influences their mind and ability to interact with the world around them.

COGNITIVE DEVELOPMENT IN LANGUAGE AND THOUGHT:-

Cognitive development is the gradual development of the brain's ability to think and make decisions. In children, cognitive development includes the development of language and thought. Cognitive development begins early in childhood, generally from birth to age 5. During this time, children process information by observing and interacting with others

Language and cognitive skills are strongly related. Although a child cannot form words for several months, they begin to learn language from the first time they hear it. How a child learns language can impact the way they learn throughout life. Strong language skills are often associated with strong cognitive skills. Another way information may be processed is through visual thinking. Visual thinking, also known as picture learning, is the process of organizing thoughts through visual images. This process of learning is common to some degree in many people.

RELATIONSHIP BETWEEN LANGUAGE AND THOUGHT:-

The relationship between thinking and language is what psychologists have been studying for decades. How an individual thinks is directly correlated to their language. Thinking is a cognitive process that allows an individual to make connections and develop meaning for the world around them.

THEORIES OF LANGUAGE AND THOUGHT:-

1.       The two main theories representing different perspectives on language and thought you should know about are Piaget's theory and the Sapir-Whorf hypothesis.

PIAGET’S THEORY OF COGNITIVE DEVELOPMENT:-

2.       According to Piaget's theory, language is preceded by and depends on thought. Before children can use words correctly they need to first develop an understanding of the concepts behind them

This occurs through the development of schemas, a process which precedes language development.

CONCLUSION:-

3.                  The conclusion is that Language and thought have interactive in that language dictates thought whereas thought also influences Language.

As our minds learn language, that language creates a framework that allows our mind to form consistent and conscious thought. Humans are amazingly self-reflective, thinking about ourselves and our experiences and our very existence. Language allows our minds to process this information in a consistent way.

REFERENCES:-

4.                  https://study.com/learn/lesson/relationship-between-thinking-language-facts-studies-importance.html#:~:text=Lesson%20Summary-,Thinking%20is%20a%20cognitive%20process%20that%20allows%20an%20individual%20to,society%2C%20values%2C%20and%20beliefs

5.                  https://www.studysmarter.co.uk/explanations/psychology/social-context-of-behaviour/language-and-thought/

  

Cogniotive Psychology: Syllogism

 

History:

•      Aristotle, an ancient Greek philosopher, was one of the first to discuss syllogisms.

•      Syllogism derives from the Greek word syllogismos, meaning conclusion or inference.

What is syllogism?

A syllogism is a form of deductive reasoning where a conclusion is drawn from two premises. The conclusion is valid only if the premises are true.

Syllogism in cognitive psychology refers to a type of reasoning where a conclusion is drawn from two propositions, known as premises.

Explanation:

A syllogism usually contains a major premise, a minor premise, and a conclusion that can be logically deduced from the premises. The validity of the conclusion depends on the logical relationship between the premises. Syllogisms are often used in research on reasoning, decision-making, problem-solving, and other cognitive processes.

Syllogisms are arguments about the properties of entities. They consist of 2 premises and a conclusion, which can each be in 1 of 4 "moods": All A are B, Some A are B, No A are B, and Some A are not B.

Example:

Premise 1: All men are mortal.

Premise 2: Socrates is a man.

Conclusion: Therefore, Socrates is mortal.

 

This example shows how syllogisms use deductive reasoning to arrive at a conclusion that is logically valid based on two premises. In this case, the conclusion follows logically from the two premises, which are both assumed to be true.

Components of Syllogism:

1.   Premises:

 Syllogism consists of two premises, which are statements that provide information about the relationship between two concepts. For example, "All mammals are animals" and "All elephants are mammals."

 

2.   Conclusion:

The conclusion is the logical inference drawn from the two premises. In the aforementioned example, the conclusion would be "All elephants are animals."

 

3.   Categorical Propositions:

 Syllogisms are expressed in categorical propositions, which are statements about the relationship between categories or classes. These propositions can be either affirmative (e.g., "All elephants are mammals") or negative (e.g., "No elephants are fish").

Types of syllogism:

•        Conditional syllogism

•        Conditional syllogism

•        Disjunctive syllogism

Catagorical syllogism:

The most commonly used type of syllogisms are the categorical syllogisms. The basic for this syllogism type is if A is a part of C, then B is a part of C (A and B are members of C).

Example:

Major premise:  All men are mortal.

Minor premise:  Socrates is a man.

Conclusion:  Socrates is mortal.

Conditional syllogism:

Conditional syllogisms are better known as hypothetical syllogisms, because the arguments used here are not always valid. The basic of this syllogism type is: if A is true then B is true as well.

Example:

Major premise: Richard likes Germany.

Minor premise: Richard likes all German things.

Conclusion: If Richard likes Germany, then he must drive an Audi.

Disjunctive Syllogism :

These syllogism types do not actually state that a certain premise (major or minor) is correct but is does states that one of the premises is correct.The basic type for this syllogism is: Either A or B is true, but they can’t be true at the same time. 

Example:

Major premise:  Either the meeting is at school or at home.

Minor premise:  The meeting is not at home.

Conclusion:  Therefore the meeting is at school.

Rules of Syllogism:

•        Rule One: There must be three terms: the major premise, the minor premise and the conclusion — no more, no less.

•        Rule Two: The minor premise must be distributed in at least one other premise.

•        Rule Three: Any terms distributed in the conclusion must be distributed in the relevant premise.

•        Rule Four: Do not use two negative premises.

•        Rule Five: If one of the two premises is negative, the conclusion must be negative.

•        Rule Six: From two universal premises, no conclusion may be drawn

Conclusion:

Syllogism is a crucial concept in cognitive psychology that helps in understanding the logical reasoning abilities of individuals. It provides a structured framework to evaluate the validity of arguments and conclusions, which is essential in critical thinking. By understanding the different components of syllogism, one can improve their deductive reasoning skills and make informed decisions based on well-supported arguments.

Cognitive Psychology: Reasoning and Conditional Reasoning

 

Introduction:

Cognitive psychology explores how humans process information, make decisions, and reason through various mental processes. Two important concepts within cognitive psychology are reasoning and conditioning reasoning.

Reasoning :

Define:

Reasoning refers to the cognitive process of drawing conclusions or making inferences based on available information or evidence. It involves using logic, critical thinking, and problem-solving skills to arrive at a justified belief or decision.

Types of Reasoning:

·         Deductive Reasoning: Deductive reasoning involves drawing specific conclusions from general principles or premises. It follows a top-down approach and is based on formal logic.

·         Inductive Reasoning: Inductive reasoning involves deriving general principles or conclusions from specific observations or evidence. It follows a bottom-up approach and relies on probability and generalizations.

Role in Cognitive Psychology:

·         Problem Solving:

Reasoning plays a crucial role in problem-solving tasks, allowing individuals to evaluate information, generate solutions, and make decisions.

·         Decision Making:

Reasoning helps individuals weigh pros and cons, consider potential outcomes, and choose the most suitable option in decision-making processes.

·         Cognitive Development:

 Reasoning abilities develop and evolve across the lifespan, influencing cognitive development and the acquisition of knowledge.

Conditioning Reasoning:

Definition:

Conditioning reasoning refers to the cognitive process through which individuals learn to associate specific stimuli with certain outcomes or consequences. It involves forming conditioned responses based on repeated pairings of stimuli and outcomes.

 

 

 

Role in Cognitive Psychology:

 

·         Learning and Behavior Modification:

Conditioning reasoning is essential in understanding how individuals learn new behaviors and modify existing ones.

·         Therapy and Behavior Change:

 Knowledge of conditioning reasoning is applied in therapeutic interventions, such as behavior modification techniques, to treat various psychological disorders.

Conclusion:

Reasoning and conditioning reasoning are important concepts in cognitive psychology. Reasoning enables individuals to draw conclusions and make decisions based on available information, while conditioning reasoning explores the process of learning associations between stimuli and outcomes. Understanding these concepts contributes to a comprehensive understanding of human cognitive processes and behavior.

 

References

·         https://reasoningforthedigitalage.com/conditional-reasoning

·         https://www.britannica.com/science/conditional-reasoning

·         https://link.springer.com/article/10.3758/bf03209259

·         https://www.apa.org/pubs/books/4316133

 

Cognitive Psychology: HEURISTICS AND ALGORITHM

 WHAT ARE HEURISTICS?

A heuristic is a rule of thumb, a trial, a strategy, or an error method of solving problem.  

                                                  OR 

A cognitive shortcut that helps us make decisions and judgements quickly.  

Example: Marketers use heuristics to understand and influence behavior.  

Following your hunch, it can be faster than an algorithm but doesn’t guarantee a solution.  

COMMON USES FOR HEURISTICS:  

Heuristics are used to,

·       Reduce mental effort needed to make decisions  

·       Simplify complex and difficult questions  

·       Help with problem solving  

·       They are fast and accurate way to arrive at a result

TYPES OF HEURISTICS:  

The four common types of heuristics include,  

·       Availability Heuristics  

·       Anchoring Heuristics  

·       Responsiveness Heuristics  

·       Affect Heuristics  

ALGORITHM:  

An algorithm is a systematic step by step, procedure for solving problems.  

Example: solving a complex mathematics problem, bake a cake Following the right instructions, it guarantees a solution.  

WHEN TO USE AN ALGORITHM:  

If complete accuracy is required, it is best to use an algorithm. By using an algorithm, accuracy is increased and potential mistakes are minimized.  

If you are working in a situation where you absolutely need the correct or best possible answer, your best bet to use an algorithm.  

WHEN TO USE HEURISTICS:  

On the other hand, if time is an issue, then it may be best to use a heuristic. Mistakes may occur, but this approach allows for speedy decisions when time is of the essence.  

Heuristics are more commonly used in everyday situations.  

DIFFERENTIATE BETWEEN ALGORITHM AND HEURISTICS:  

Algorithms and heuristics are different approaches to solving problems. Algorithm are comprehensive step-by-step procedures. They are exhaustive and guarantee the correct solution, but may be time-consuming and require a lot of mental effort. In contrast, heuristics are shortcut strategies or rules-of-thumb. Although they may save time and effort, they are not always guaranteed to yield the correct solution.  

CONCLUSION:  

In conclusion, heuristics and algorithms are two techniques to solve problems where, heuristics are used in everyday decisions. They are fast, unconscious and automatic whereas, algorithm is used in complex decisions. They are slow, conscious, effortful and reliable. 

Cognitive Psychology: Problem Solving by Analogy

 

Problem Solving by analogy:

Definition: Problem solving by analogy refers to the process of solving a new problem by drawing upon the knowledge and solutions from a similar, previously solved problem.

Importance of Analogy in Problem Solving:

·         Analogies help us make connections between problems that may appear unrelated at first.

·         They enable us to transfer knowledge and solutions from one domain to another.

·         Analogies stimulate creativity and innovation by providing new perspectives on problem solving.

Steps in Problem Solving by Analogy:

Identify the target problem: Clearly define the problem that needs to be solved.

Find a source problem: Search for a previously solved problem that shares similarities or patterns with the target problem.

Extract the underlying principles: Identify the key principles or strategies used to solve the source problem.

Apply the principles to the target problem: Adapt and apply the principles from the source problem to the target problem.

Evaluate and refine the solution: Assess the effectiveness of the applied principles and refine the solution as needed.

Examples of Problem Solving by Analogy:

1.      Wright Brothers and Bird Flight: The Wright Brothers’ observation and understanding of bird flight helped them design the first successful airplane.

2.      Velcro: The invention of Velcro was inspired by the observation of burrs sticking to clothes and fur.

3.      NASA’s Mars Rovers: NASA engineers used the analogy of remote-controlled cars to design and operate Mars rovers.

Benefits of Problem Solving by Analogy:

·         Enhanced creativity and innovation

·         Accelerated problem-solving process

·         Efficient utilization of existing knowledge and solutions

·         Increased flexibility and adaptability in solving new problems

 

 

Challenges in Problem Solving by Analogy:

·         Identifying appropriate source problems that have relevant similarities to the target problem.

·         Extracting the underlying principles effectively.

·         Adapting the principles to fit the target problem context.

·         Avoiding potential pitfalls of overgeneralization or oversimplification.

 

Tips for Effective Problem Solving by Analogy:

·         Build a diverse knowledge base: The broader your knowledge, the more diverse analogies you can draw upon.

·         Seek inspiration from various domains: Look beyond your immediate field to find relevant analogies.

·         Analyze successful solutions: Understand the underlying principles that led to success in previous problems.

·         Practice and refine your analogy skills: The more you practice, the better you become at recognizing analogies and applying them effectively.

Conclusion: Analogical problem solving is a valuable cognitive tool that can help us overcome challenges and find innovative solutions. By leveraging the power of connections and drawing upon existing knowledge, we can approach problem solving from fresh perspectives and unlock our creative problem-solving potential.

 

References:

https://en.m.wikipedia.org/wiki/Conceptual_metaphor#:~:text

https://www.jstor.org/stable/1129778

https://glossary.sil.org/term/target-domain#:~:text=A%20target%20domain%20is%20a,The%20crime%20rate%20keeps%20rising.

https://www.grin.com/document/276480

YouTube

https://youtu.be/FOXGQC-yawE

https://youtu.be/L7OSy67tzwc

Cognitive Psychology: Mean–End Analysis

 THINKING AND PROBLEM SOLVING

Definition: 

Problem solving and critical thinking refers to the ability to use

knowledge, facts, data to effectively solve the problem. It involves a number of mental activities, such as inferring, reasoning, imagining, judging, problem solving and critical thinking. In psychology problem solving refers to the process of finding solutions to problem encountered in life.

For Example: In customer service you might find a scenario like, “ How would you handle an angry customer?” Or “How do you respond when a customer asks for refund? Practicing how you might handle these scenarios in industry can help you call upon solutions quickly when they arise on the job.

STEPS TOWARDS PROBLEM SOLVING

 Define the problem. What is the problem?

 Clarify the problem

 Identify the root cause of the problem

 Generate alternative solutions or new idea to solve the problem  Implement and evaluate

 Evaluate and follow up on the solutions

   

 STEPS TO IMPROVE YOUR PROBLEM SOLVING SKILLS 

 Understand the causes of problems

 Overcome short-term crises

 Create strategies to solve longer term problems  Turn problems into opportunity

 Have the ability to decide a good solution

 Managing Risk

 Managing Emotions

 Get a good nights sleep

 Use mind maps to help visualise the problem

THE SIX-STEP PROBLEM SOLVING MODEL:

   

 ADVANTAGES  OF SIX-STEP PROBLEM SOLVING

 The Six-Step method provides a focused procedure for the problem solving group

1. It ensures consistency, as everyone understands the approach to be used

2. By using data, it helps eliminate bias opinion

3. It helps to remove divisions and encourages collaborative working

4. It eliminate the confusion caused when people use different problem solving techniques on the same issue.

5. It makes the decision making process easier

6. It provides justifiable solutions

SIX-STEP PROBLEM SOLVING DIAGRAM:

  

 MEAN END-ANALYSIS

 Analysis is a simple tool that helps you to identify the practical steps needed to solve a problem or reach a desired state same as mean end analysis is a problem solving technique used commonly in artificial intelligence for limiting search in AI programs. It is a strategy to control search in problem solving and it solves problems by defining the goals and establishing the right action plan.

  

WHERE IS IT USED? 

 1. Mean end analysis is a creative problem solving technique used in Artificial Intelligence application for a longer period of time. From the search space of possible solution available in the system, AI selects the best possible solution by applying the right search strategy or algorithm. This algorithm deals with an initial state and end state and the action plan and movement in forwarding and backward directions.

• In General Management area, mean end analysis facilitates organisation planning to attain the goals.

• In personal life also one can follow mean end analysis methodology to solve problems or attain specific goal. It helps to understand overwhelming situations by clearly understanding the reasons for current status

• Mean end analysis helps in avoiding frustrations and mental depression and lead to peaceful life.

• These processes are further split into sub-process for effective implementation.

• Mean end analysis used in computer and engineering to help study decision points and actions.

• Mean end analysis works well for projects in any field

 HOW DOES MEAN END ANALYSIS WORK

1. Measures the current state and identifies the problems

2. Defines the goal state to be reached

3. Splits the goals into sub-goals and sub-goals into sub-sub-goals.

For Example: Long term goals can be split into short term goals and further

 

4. Include all intermediate steps, relevant actions to address the issues faced in the current situation

5. Makes these steps detectable and device ways and means to track even small changes in the actual and to be state.

 ALGORITHMS FOR MEAN END ANALYSIS 

• The algorithms provide the best possible solutions to a problem, and it contains the well defined step by step resolution to the given problem. One will have to follow this mathematical template of steps blindly and it is expected to produce the end result.

• These algorithms can be used as input to develop computer programs and implement a solution.

• Algorithms and generally used where accurate result can be expected and the time to complete the activity. Algorithms are deployed in planned activity e.g. (Organisation Planning)

THE ALGORITHM FOR MEAN CONSIST OF THE FOLLOWING STEPS.

   

 STEP 1: Measure the current state of things by doing as it is the study

 STEP 2: Capture the deficiency in the current state for improvement and

define the goal state

 STEP 3: Compare the current state and the goal state and if they are the same level the problem is solved

 STEP 4: List differences between the current state and the goal state at micro and macro level

 STEP 5: Convert the differences into deletions/modifications to current state and new additions

 STEP 6: Define the action to implement the changes as defined in step 5

 STEP 7: Implement the changes and measure the actual results with the

planned goals

 STEP 8: Do course correction and achieve the final goal

CONCLUSION: 

Problem solving and mean end analysis are interrelated to each other because both of them help us in problem solving. Mean end analysis is basically a problem solving technique itself it suggest very useful means of solving the problems a person is facing. Thinking is a basic process of human cognition if a person stays relaxed he is able to think peacefully and solve the problems by analysing the issue through the thought process of problem solving both of these processes have helped people over come any kind of situation which is hard for them to face. A problem can not be solved with analysing it so for that both of the processes play a vital role in the thought process of a person.

 

REFERENCES 

https://asq.org/quality-resources/problem-solving https://cmoe.com/blog/10-ways-to-improve-problem-solving-skills/ https://business.tutsplus.com/tutorials/what-is-a-means-end-analysis--cms-40649

https://www.indeed.com/career-advice/resumes-cover-letters/problem-solving- skills#:~:text=For%20example%2C%20in%20customer%20service,they%20arise %20on%20the%20job.

https://www.uapb.edu/sites/www/Uploads/Assessment/webinar/session%204/Exa mple%20of%20generic%20assignment%20for%20Problem%20Solving_02.pdf

https://www.toolshero.com/problem-solving/ https://kepner-tregoe.com/blogs/what-is-problem-solving-and-why-is-it-important/ https://m.youtube.com/watch?v=4IC3T_IiywM https://m.youtube.com/watch?v=lSCGOmzQm8I

Cognitive Psychology: Types of Interference and Fan Effect

 

Introduction:

Interference is one theory to explain how and why forgetting occurs in  long -term memory. Interference is a memory phenomenon in which some memories interfere with the retrieval of other memories.

Types of Interference:

There are two basic types of interference:

·         Proactive interference

·         Retroactive interference

Retroactive interference:

Retroactive interference refers to the tendency for new learning to inhibit retrieval of old learning. The sleeping college students remembered more because retroactive interference was held to a minimum.

Proactive interference:

Proactive interference, the second form of interference, is the tendency for old memories to interfere with the retrieval of newer memories.

Fan Effects:

The fan effect is a psychological phenomenon under the branch of cognitive psychology where recognition times or error rate for a particular concept increases as more information about the concept is acquired. The word “fan” refers to the number of associations correlated with the concept.

The origin of fan effects:

The fan effect first appeared in a series of experiments conducted by John R. Anderson, a cognitive psychologist, in 1974. The three experiments he conducted involved participants learning 26 sentences that paired a person with a location. Additionally, they were asked to determine whether or not a particular sentence that was given to them belonged to the 26 they were asked to study. An example of a sentence Anderson used in his experiment was: “A hippie is in the park.

Implications of fan effects:

·         Cognitive Load: Fan effects suggest that memory retrieval is subject to cognitive load. As the number of related items increases, the cognitive load associated with retrieving the target information also increases. This has implications for tasks that require memory retrieval under high cognitive load, such as decision making or problem solving. It highlights the importance of managing cognitive load to optimize cognitive performance.

·         Semantics network: The fan effects is consistent with the idea of semantic network in memory. According to this theory related concepts are organized in a network like structure in memory. When multiple related items are active the retrieval process becomes more complex as the activation spreads across the network, increasing the difficulty of accessing a specific target item.

Conclusion: interference and fan effects play significant roles in cognitive psychology, specifically in the realm of memory and information processing. Interference can impair memory recall by introducing competition or similarity between information, while the fan effects demonstrate how the organization and complexity of cognitive network affect the retrieval of information. Understanding these phenomena can help researchers, education and individual optimize memory performance and develop effective learning strategies.

 

 Reference

·         https://www.verywellmind.com/interference-definition-4587808

·         https://images.app.goo.gl/XmYDTUr1eHYikBj58

·         https://www.ifioque.com/psyche/interference

·         https://en.m.wikipedia.org/wiki/Fan_effect

·         https://chat.openai.com/?model=text-davinci-002-render-sha