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Reasoning & Decision Making Contents: (part 1) Reasoning – definition Deductive Reasoning...

Reasoning & Decision Making Contents: (part 1) Reasoning – definition Deductive Reasoning Thinking categorically Thinking conditionally Inductive Reasoning Four Types of Heuristics that cause errors in Reasoning KMF 1023 Availability Heuristic, Illusory correlations, Representative Heuristic & COGNITIVE PSYCHOLOGY Confirmation bias Decision Making Lecturer: Norehan Zulkiply The utility approach FSKPM, Universiti Malaysia Sarawak Reasoning & the Brain Reasoning Decision Making Reasoning Cognitive processes by which Making choices between alternatives people start with information and come to conclusions that go beyond original Eg. Buying an apartment, buying the perfect information ice cream, gambling E.g. Heuristics in perception, Memory Can involve both deductive and inductive construction reasoning Two types of Reasoning Deductive: a conclusion logically follows from premises Inductive: arrive at conclusions that are probably true, based on evidence Deductive Reasoning Deductive Reasoning Basic form of deductive reasoning: Syllogisms (general to specific) Syllogism = 2 statements called premises followed by third statement called conclusion Categorical Syllogism Conditional Syllogism 1  Deductive Reasoning (categorical syllogisms) Categorical Syllogisms Eg. -Has 2 premises and 1 Two approaches to study categorical conclusion. syllogisms: Premises: Normative approach- indicate which forms of All As are Bs -Premises & Conclusion syllogisms are valid and which are not (uses logic describe the relation thinking) All Bs are Cs between 2 categories by using statements that begin Conclusion: with some, no, or all Descriptive approach – how well people can All As are Cs evaluate whether a syllogism is valid (uses -Syllogism is valid if psychology) conclusion follows logically from its two premises Normative Approach Normative approach premise 1:All As are Bs 2 main principles: premise 2:All Bs are Cs Principle 1: If the premises are true, the conclusion of a valid syllogism must be true Conclusion: All As are Cs premise 1: All As are Bs True Although artificial, provides a good way premise 2: All Bs are Cs True of testing how well people are at Conclusion: All As are Cs True determining validity This is valid because the conclusion logically follows from the premises Normative approach Descriptive Approach Principle 2: The validity of a syllogism is The normative specifies the correct answers determined only by its form, not its content The descriptive approach is concerned with Syllogism 1 Syllogism 2 how well people can actually judge validity of a syllogism (uses psychology) premise 1: All As are Bs All Birds are Ants premise 2: All Bs are Cs All Ants have 4 legs So syllogism 2 is not valid if it is determined -------------------------------- -------------------------------- further by Descriptive approach. Conclusion: All As are Cs Conclusion: All Birds have 4 legs Question :So how do we determine further it’s validity? 2 Sources of error in syllogism Atmosphere Effect: qualifiers (all, some, no) create People make errors in syllogisms. an overall mood that influences the evaluation/production of the conclusion Two common source of errors Two All’s generally suggests an All conclusion (Syllogism 1 Atmosphere effect in your textbook) One or two No’s suggest a No conclusion Belief bias One or two Some’s suggest a Some conclusion (Syllogism 4 in your textbook) All of the students are tired Some tired people are irritable Some of the students are irritable  This syllogism is invalid if it is judged using descriptive approach. The truth of the conclusion can be argued) However….Atmosphere effect would lead to us to say that this invalid syllogism is valid. Deductive Reasoning (thinking conditionally) Belief Bias: if a syllogism’s conclusion is true or Conditional Syllogisms: agrees with a person’s beliefs the syllogism will be Have two premises and a conclusion too…but judged as valid the first premise has the form “If…..then..” All of the students are tired Some tired people are irritable Eg. Some of the students are irritable (believable) Premise 1: If I study smart for KMF 1023 mid term exam, then I will get a good grade Premise 2: I studied smart for the KMF 1023 mid- It seems possible that “Some of the students are term irritable” (could be true) Conclusion: I got a good grade So if the syllogism’s conclusion is parallel with your belief ….then you will judge it as valid. This type of deductive reasoning is common in everyday life Basic type of conditional syllogisms Deductive Reasoning First Premise: If I study (p) then I’ll get a good grade (q), is the same in all four cases Types of Conditional Syllogisms No. Second premise Conclusion Type Valid? %Correct p = antecedent (‘if’) 1. p Therefore q affirming the antecedent (modus ponens) Yes 97% q = consequent (‘then’) I study Therefore, I’ll get a good P is affirmed grade  If p..then q 2. Not q Therefore, not p Denying the consequent Yes 60% (modus tollens) I didn’t get a Therefore, I didn’t study q is negated good grade 3. Q Therefore p Affirming the consequent No 40% “If I don’t submit my assignment on time I got a good Therefore, I studied then my marks will be deducted. ” q is affirmed grade 4. Not p Therefore not q Denying the antecedent No 40% I didn’t study Therefore, I didn’t get a p is negated good grade Source: from Evans et al., 1993 3  Reasoning & Decision Making (part 2) Deductive reasoning – moving from general to specific (reach to a conclusion that is logically follows from premises) Inductive reasoning – moving from specific to general (arrive at a conclusion that is probably true, based on evidence) Inductive Reasoning Make a conclusion based on evidences (observations) Inductive reasoning Premises are based on observation of one or more specific (Specific to general) cases Generalize from cases to a more general conclusion In deductive reasoning, premise is stated as a fact. In inductive reasoning, premises are based on observation(s). Consider this arguments Observation: There are lots of vultures overhead, I’m in a desert with no water, Conclusion : I’m pretty sure they’re waiting for me to die. Inductive Reasoning Another example: Deductive reasoning = validity of syllogism Observations: There are lots of students in the cafeteria in the afternoon, I saw some students eat Inductive reasoning = strength of hungrily, and the waiters are walking back arguments and forth to serve the ordered foods to the students Conclusion : I’m pretty sure that these students are really hungry. 4  Inductive vs. Deductive Reasoning -- Inductive Reasoning Fundamental Difference Criteria for inductive reasoning: Deductive reasoning is dependent on its premises Through pure logic, the conclusion is derived based on a Number of observations: I’ve often seen few premises vultures circling above thirsty people wandering deserts in old movies... Representativeness of observations: All the Inductive reasoning creates laws based on the vultures I know of are scavengers, and I’m observation of the facts to be scavenged... The premises of an argument are believed to support the conclusion but do not ensure it. Quality of evidence: It is statistically unlikely I’ll survive in a desert without water... Inductive Reasoning Inductive Reasoning Inductive reasoning used in Science & Four Types of Heuristics that cause everyday life errors in Reasoning: Basic procedure for making discoveries 1. Availability Heuristic used in generalization of results Illusory correlations 2. Simple assurance 3. Representative Heuristic Economical (identify certain trends) Conjunction Rule 4. Confirmation bias Inductive Reasoning 1. Availability Heuristic Heuristics: Tversky & Kahneman’s (1973) study: Which is more common: words beginning with r or ‘computational short-cut’ that saves us words with r as the third letter? time and is easy to use and results in correct answers most of the time but not Results: People tend to say words beginning all the time with r But There are 3x more r s in third position Things that are more easily remembered are judged to be more common 5  2. Illusory correlations 3. Representative Heuristic Illusory correlation – occurs when a correlation between two Representative Heuristic – occurs when people make events appears to exist, but in reality the correlation actually judgements based on how much one event resembles does not (or is much weaker than you assume it to be) another event Eg. Stereotypes (oversimplied generalization about a group of The probability that an event A comes from class B can be determined by how well A resembles the properties of class B. people that often focuses on the negative) All effeminate men are homosexuals All Asians cannot speak English Consider this example: All coloured people are stupid Robert is a male in the US, wears glasses, speaks quietly, and reads a All chinese are businessmen lot. Which is more likely? Robert is a librarian or Robert is a farmer? Results: people tend to choose librarian as Robert match people’s can occur when we expect two things to be related, so we fool idea of a typical librarian ourselves into thinking they are related even when they are not Why? Because they are influenced by the representative heuristic and base their judgment on how closely Robert’s characteristics (A) match those of a typical librarian (B) Representative Heuristic Representative Heuristic The likelihood that event A comes from class B depends on how close A resembles or represents B In a group of 100 people, there are But this means they ignore another important source 70 lawyers and 30 engineers. If Jack is picked of information – base rates randomly from that group, what is the chance Base rates – relative proportion of different classes that he is an engineer? of population In this example of Robert, statistically there were Results: people will pick the correct answer more male farmers than male librarians in the US, so when base rates such as the above are given this base rate shows that it is more likely that Robert is a farmer Representative Heuristic Representative Heuristic For some of the participants, this description is added.. People disregard base rate information Jack is a 45-year-old man. He is married and has 4 children. He is when they are given descriptive generally conservative, careful, and ambitious. He shows no information interest in political and social issues and spends most of his free time on his many hobbies, which include home carpentry, sailing, In many cases often this cause errors in and mathematical puzzles. reasoning. Is Jack more likely to be an engineer or a lawyer? People tend to choose engineer even when the earlier base rate shows 30% of chance that he is an engineer When the descriptive info. is given, participants increase their estimate that Jack is an engineer. They disregard base rate (in fact, only 30% chance of picking Jack as an engineer). 6  Representative Heuristic Representative Heuristic Another example: The correct answer is A but 85 % of Linda is 31-years-old, single, outspoken, and very bright. She majored in philosophy. As a student, she participants chose B because they were was deeply concerned with issues of discrimination and influenced by the representative social justice, and also participated in antinuclear heuristic. demonstrations. Linda’s description fits people’s idea of a typical feminist Which of the following alternatives is more likely to describe Linda? But in doing so they have violated the A) Linda is a bank teller Conjunction rule B) Linda is a bank teller and is active in the feminist movement Conjunction Rule Representative Heuristic P(A&B) P(A) By using the representative heuristic people incorrectly estimate the probability of an The probability of a conjunction of two events (A and event occurring based on the extent the B) cannot be higher than the probability of the event is a representative of a particular single event (A alone or B alone). category There are fewer feminist bank tellers than bank tellers Bank teller (A) Feminist & bank teller (A&B) 4. Confirmation Bias Confirmation bias - our tendency to selectively look for information that conforms to our hypothesis Decision Making Lord and coworkers ( 1979)- He identified one group of participants in favor of capital punishment, and another group against it. Then he presented the participants with descriptions of research studies on capital punishment (some showed a deterrent effect on murder, others provided no deterrent effect) Participants reaction on the studies reflected the attitudes they had at the beginning of the experiment. 7 Decision Making Decision Making Making choices between alternatives The Utility Approach Utility = useful or profitable Eg. Making decision to ensure the outcome will benefit Buying an apartment you the most or will be most useful or profitable to Choosing the “right” university for your you Economics utility theory undergraduate studies People are basically rational, so if they have all of the relevant Deciding which job offers you would want information, they will make a decision which results in the maximum expected utility to accept. Decision based on monetary value However, in reality people do not always make decisions that maximize their monetary outcome. Not because they are irrational, but they find value in things other than money Decision Making Reasoning & the Brain Decision based on monetary value Prefrontal Cortex (PFC): important The realities: Casinos- people still gamble even though it may in reasoning, problem solving & working not get them rich just for the fun of it memory Some outcomes cannot be calculated- people do not necessarily act to maximize monetary value, eg. Paying expensive airfare to go home to see a loved one Incorrect mental simulations – models that people create about what will happen based on decisions that they make, eg attending a particular university, winning the lottery Summary Summary Inductive vs Deductive Reasoning 1. Availability Heuristic Inductive – based on the strength of 2. Illusory correlations your argument (specific to general) 3. Representative Heuristic Conjunction Rule 4 types of heuristics that cause errors in 4. Confirmation bias inductive reasoning: 8 Summary Decision making based on the utility approach- make decisions in terms of monetary gain But there are problems with this approach Reasoning and decision making abilities – prefrontal cortex of the brain 9  Problem Solving In today’s lectures, we will discuss:  What is Problem solving?  Approaches to problem solving:  Problem solving involving restructuring  Problem solving involving search  Problem solving using analogies  Experts and non-experts approach to problem solving KMF 1023  Creative cognition COGNITIVE PSYCHOLOGY  Metacognition in Problem Solving Lecturer: Norehan Zulkiply FSKPM, Universiti Malaysia Sarawak  The brain and problem solving What is a problem?  Problem  Involves some difficulty and has a solution that is What is Problem Solving? not immediately obvious  We solve problems everyday  A problem happens when there is an obstacle between a present state and a goal and it is not immediately obvious how to get around the obstacle (Lovett, 2002) What is a problem? Problem Solving  Another definition……  The situation people face when they want something but do not know right away what to do to get it (Newell and Simon, 1972) 1  Three Approaches in Problem solving involving Problem Solving Restructuring Problem solving involving restructuring Problem Solving as Restructuring  Proposed by Gestalt Psychologists  Example:  Problem solving for them was about:  The Circle Problem  1. How people represented a problem in their  Circle with radius r. mind,  How long is x?  2. How solving a problem involves a reorganisation or restructuring of this r representation Problem Solving as Re-representation Insight in Problem Solving  Solution: x = r  Problem Solving :  Problem  Insight : sudden realisation of a problem’s perception solution (‘Aha!’ experience)  Representing the problem in a different way Restructuring  Solution to circle problem requires (perceptual) insight 2 Insight in Problem Solving Insight in Problem Solving  Another example of  Insight problem insight problem:  Solution to the triangle problem: (a) Triangle problem: Move 3 pins so that the triangle faces downwards.  arrows indicate movement;  colored circles indicate new positions Insight in Problem Solving Obstacles to Problem Solving  Are insight problems qualitatively different from  Experience can help or hinder problem other problems? solving…  Non-insight problems : involve participants to work a)Functional Fixedness on a more methodical process, in which they have some b)Mental Set knowledge that they are getting closer to the situation Functional fixedness : familiarity with an  Examples of non-insight problems: object’s function can inhibit other possible uses  Solve for x: (1/5) x + 10 = 25  Factor 16y2 – 40yz + 25z2  Toothbrush? Hanger? Belt? (algebra problems) Obstacles to Problem Solving Solution to the Candle Problem Functional Fixedness  Necessary ‘insight’:  The match box must be seen as a support, rather than Duncker (1945)’s candle problem a container.  Two groups of participants:  Results:  group 1 was presented with all the items in a small  Group 1 found the problem more difficult that did the cardboard box Group 2.  Group 2 was presented with the same materials but outside the box. 3  Results of the Candle Problem  Adamson’s (1952) replication- Functional Fixedness obtained the same results as Duncker’s.  Maier’s (1931) two-string problem:  Presentation mode  Using only a chair and matters: empty boxes pliers tie together the two less likely to be viewed ends of these strings only as containers.  Solution: the pliers can be used as a weights to create  Functional fixedness : a pendulum to swing the familiarity with an strings object’s function can inhibit other possible uses Maier’s (1931) two-string problem. As hard as Sebastian tries, he can’t grab the second string. How can he tie the two strings together? Mental set Mental Set Luchin’s (1942):  Mental Set Mental set and Water- jug problems  a person’s tendency to respond in a certain manner based on past experiences Each problem specifies the capacities of jugs A, B, and C, and a final desired quantity.  Functional Fixedness creates mental set by The task is to use the jugs to measure out the final causing the person to focus on a particular quantity. function of an object. The solution to problem 1 is  E.g., “a box can only function as a container” shown. All of the other (Mental set) problems can be solved using the same pattern of pouring, but there are more efficient B – A – 2C = desired quantity solutions to problems 7 and 8. Mental Set Mental Set  Comparing solutions of participants with vs.  A simple solution to Luchin’s (1942) problem 7: without mental set for Problem 7 All of the participants who began the Luchin’s water- jug problem with problem 7 used the shorter solution for problem 7 (right bar) But less than a quarter who had established a mental set by beginning with problem 1 used the shorter solution to solve problem 7 (left bar) A + C = desired quantity 4  Summary: Gestalt Approach to P.S. Problem Solving involving Search Modern Approaches: Problem solving involving Search Modern Approaches: Problem (The information processing approach) solving involving Search  Newell and Simon  Initial state – condition at the beginning of the problem (1956, 1972):  Goal state – condition at the end of the problem  Intermediate states – conditions that exist along the  A problem space consists way between the initial and goal states of:  Operators- permissible moves between states to 1. Initial state achieve the goal 2. Goal state 3. Intermediate states  Problem solving = searching the problem space 4. Operators Modern Approaches: Problem solving involving Search The Tower of Hanoi (ToH)  Example of problem :  Rules (or operators)  The Tower of Hanoi (ToH) problem  Starting with the three rings of different sizes on 1.you can only move one ring at a time, peg A your task is to move all of the rings to peg C 2.you may not place any large ring on top of a smaller ring, and, Initial state Goal state ?? 3.rings may only be placed on pegs and not on, for example, the table or the floor 5 The Tower of Hanoi (ToH) Solving the ToH  Use means –end – analysis strategy  Aim is to reduce the difference between the initial and goal states by creating subgoals – goals that create intermediate states that are closer to the goal Initial steps in solving the (a) Initial and goal states for the Tower of Hanoi problem. Tower of Hanoi problem, (b) Operators that govern the Tower of Hanoi problem. showing how the problem can be broken down into subgoals. Means-ends Analysis approach in Problem Solving Means-ends analysis  Goal: to reduce the difference between the initial  Another Example: writing a compare-and- and goal states, by creating subgoals contrast essay. 1. Identify the goal state (the position you want to  Steps: defend)  1. Set up a (global) goal or (local) subgoal 2. Break down the paper into smaller problems (e.g.:  2. Judge difference between current and goal/subgoal state introduction, comparison of evidence, conclusion)  3. Look for an operator that will reduce or eliminate 3. Proceed through the paper one section at a time. the difference  4. Apply the operator  5. Apply steps 2 to 4 repeatedly until goal has been achieved Problem Solving using  Means-ends analysis is successful for many problems but not suited for problems that are difficult Analogies to specify a clear goal state or specific operators  Also not suited for insight problems  Many problems are ill-defined (e.g., vague initial or final states, flexible operators…)  Eg. Whom should I marry? Should I go to graduate school? Which university should I attend? 6  A classic experiment on analogical Problem Solving using Analogies problem solving  Analogies :  Occur when they are parallels between two different  Duncker’s (1945) Radiation Problem: situations. (structural similarity between situations or events) “A man has an inoperable stomach tumor. A technique which can help him is to use laser  Eg:‘floats like a butterfly, stings like a bee’ (Muhammed Ali) rays which can destroy organic tissue at sufficient intensity.  Analogical problem solving = a solution to one problem is presented that is analogous (similar) to the solution of another problem that we are trying to How can he get rid of the tumor using these solve. rays and at the same time avoid destroying the healthy tissue which surrounds it?” Duncker’s (1945) Radiation Problem Duncker’s (1945) Radiation Problem Consider the story of “The General” who wanted to overthrow a strong dictator who ruled a country Solution to the radiation problem: Bombarding the tumor, shown in the center, with a number of low-intensity rays from different directions destroys the tumor without damaging the tissue it passes through. How the general solved the problem of how to capture the fortress. The Process of Analogical Duncker’s (1945) Radiation Problem P.S. Note: Solution to radiation problem is actually used in modern radiosurgery Gick & Holyoak (1980): 1. Noticing parallels – Most difficult step! 2. Mapping corresponding elements 3. Applying the mapping to generate a solution According to Gick and Holyoak (c) Radiosurgery, a modern medical technique for irradiating brain (1980), the process of tumors with a number of beams of gamma rays, uses the same analogical problem solving principle.. involves these three steps. 7  Experts and Non-experts Expert vs. Novice Problem Solvers approach to problem  Experts := ~ 10 years of domain experience. solving  Examples: Chess, Physics, Music, Computer Gaming…  Fact: Experts exhibit better (faster & more accurate) problem solving. Expert vs. Novice Problem Solvers Expert vs. Novice Problem Solvers Experts have … more knowledge Experts … Spend more time analyzing, rather than solving differently organized knowledge a problem Chi et al. (1982): Experts spend more time at the beginning of In Categorizing problems, problem solving process to identify and represent Experts the problem compared with novices, so spend  Represent problems at a deeper level considerably less time choosing appropriate  Focus more of their solution strategy once the problem had clarified attention on the underlying structure of the problem RATHER THAN on superficial surface features The kinds of physics problems that were grouped together by novices (left) and experts (right) (Chi et al, 1981). Some more…. Expert vs. Novice Problem Solvers  Faster than novices  at processing meaningful information – search and represent problem efficiently (e.g. expert mathematician) But: Expertise is domain specific  at performing skills of their domain, and quickly solve problems with little error due to  They have many skills in a domain practiced to the point of Experts are no better than novices outside their field automatization of expertise  Many problem for them are no longer problems that require  Expertise is domain specific -- experts are no better able to searching for a solution – rather a solution has been stored solve problems in unfamiliar domain than novices  E.g. Compare Political scientist vs. expert chemist -  Monitor their performance better solving a problem about political science. The result is  Experts are aware of how they are doing as they work on a sophisticated analysis vs. simplistic solution tasks in their domain of competence  Such domain-specific expertise does not transfer far,  More likely to generate alternative hypotheses before solving however a problem and are quicker to reject inappropriate solutions during problem solving  Judge the difficulty of problems more accurately than Caveat: Expertise can result in functional fixedness novices and ask more appropriate questions at all stages of (blindness to creative alternatives) the problem-solving process 8  Process information in large units  Organize information more efficient than novices – chunking Creative cognition information into larger recognizable units that a novice might use.  E.g. chess expert view complex chess configurations for as little as five seconds yet remember them in remarkable detail; novices remembered very little of what they saw.  Hold more information in STM and LTM  The biology capacity underlying STM is no greater for experts than novices -- the difference is that, experts have many skills and strategies automatized.Being automatic allows experts to use their STM and LTM in a more efficient way, compared with novices Creative & Divergent Thinking Creative Cognition  Convergent vs. divergent thinking  So far we have seen P.S. by restructuring, Convergent thinking searching, and by analogy   Thinking that works towards finding a solution to a specific problem that usually has a correct answer.  Problem converges onto the correct answer  What about creativity?  Divergent thinking ( Creative Cognition)  Creative Problem Solving  Thinking that is open-ended  There are a many potential solutions and no correct answer ….having the ability to think and (although some might work better than others)  Can lead to the creation of many ideas create something new (characterized by originality and expressiveness)  Tests of Creativity Task: Think of multiple uses for familiar objects. Metacognition in Problem Solving  Metacognition  the knowledge that people Problem Solving and have about their own thought processes the Brain (thinking about thinking)  In P.S., one can use metacognition:  To identify the “actual problem” that needs to be solved  To identify when you do not understand a problem  To recognize which parts of the problem were difficult  To monitor your own performance (e.g., progress in P.S.) 9 Problem Solving & the Brain Problem Solving & the Brain  Yes, the brain is involved….  Many brain areas involved in P.S. (due to different types of task), but one particularly crucial area in P.S. is Prefrontal Cortex  Prefrontal Cortex (PFC):  Important for planning (multistep tasks), and executing strategies, reasoning and making connections among different parts of a problem or a story. Areas of the brain that are activated by playing chess – evidence from PET Summary Summary  What is a problem?  Four key differences between experts and  Three approaches to problem solving novice in problem solving:  Experts possess more knowledge about their  Restructuring (Gestalt) fields  Search (Newell & Simon)  Experts’ knowledge is organised differently from  Analogy (Gick & Holyoak) novices’  Experts spend more time analysing problems  Experts are no better than novices when given problems outside of their field 10  Language Contents Definition & characteristics Language and the brain – Aphasia Broca’s aphasia Wernicke’s aphasia KMF 1023 Understanding words COGNITIVE PSYCHOLOGY – Effects of words: Word-superiority effect Lecturer: Norehan Zulkiply – Effects of words in sentences: the role of FSKPM, Universiti Malaysia Sarawak frequency & context Word-frequency effect Contents Definition and Properties Understanding Sentences Language : a system of communication through which we code and express our feelings, thoughts, – Parsing sentences ideas, and experiences. Syntax first approach One of several means of communication. Semantics Interactionist approach Important properties of language – a hierarchical structure and that is governed by rules - allows creation of unique sentences, communicate Language and culture whatever we want to express … Hierarchical –words, phrases, sentences to a large text/story – Culture can influence one’s use of Rules – I eat bread and cheese this morning (permissible) language but Cheese eats this morning bread (not permissible) Functions of Language: What do Milestones in the Study of L you use language for? Wilhelm Wundt (1980) – Language : mechanism of transforming thoughts into to communicate sentences. – to memorize (rehearse, encode…) Language – one of the earliest cognitive capacities to – to compare and categorize be studied physiologically (by Paul Broca and Carl Wernicke) which give insights into brain function: – to identify (e.g., inner states, feelings…) – to enjoy (e.g., arts, poetry…) – to think about something – to discover new ideas or viewpoints Frontal lobe Temporal lobe 1 Milestones in the Study of L Understanding Words The modern era of language research began in 1950s: – B.F.Skinner (1957) – in Verbal behavior, proposed that language is learned through the mechanism of reinforcement Children learn language by being rewarded for using correct Impressive acquisition rate: language, being punished for using incorrect language From 0 — 18years old: 75,000 (~12.1 words – Noam Chomsky (1957) – proposed that human are genetically per day) programmed to acquire and use language Person’s lexicon - all understandable words Studying language is a way to study properties of the mind. Disagree with the behaviorist ideas that the mind is not valid of a person topic of study in psychology Perceiving letters and words 1970s/1980s: Chomsky’s criticism of behaviorism led to the emerging – Phoneme- the shortest segment of speech, if ‘Psycholinguistics’- the field concerns with psychological study of changed, changes the meaning of a word language (speech sound) 1990s/today: Enormous specialization: E.g. bit : /b/, /i/, and /t/ – Language acquisition Replacing /b/ with /s/..becomes sit – Comprehension: Syntax vs. Semantics Replacing /i/ with /u/..becomes but – Speech production Perceiving letters and words Perceiving letters and words Phonemic restoration effect – “Fill in” missing phonemes based on context of sentence and portion of word presented Questions to consider: E.g. You hear this sentence  I want to go to the – How does a letter’s presence in a word hospital to do medical check-up. affect our ability to identify it? – if while hearing the sentence, a phoneme /s/ is – How do we perceive separate words within masked by a noise (e.g., cough), you can still a sentence. make sense of the word “hospital). These help: 1) The context produce by the sentence Answers to both involve meaning 2) The portion of the word that was presented 3) The meaning of the words that follow the missing phoneme. Perceiving Letters and Words The Word-Superiority Effect Are letters in words processed serially or in parallel? Word-superiority effect (Reicher, 1969; Wheeler, 1970) – – Participants sees a stimulus- either a word, a single letter or a Letters are perceived more easily in string of letters that do not create a word – flashed for 25-40 words than when they are in isolation msecs or in non words Letters in words are not processed Masking stimulus Decision task: Which of the two letter by letter but are affected by its letters has been appeared before? surrounding (context) = processed in Results: parallel (selari) (a) Faster and more accurate than (b) and (c) letters are perceived more easily in words (based on context) – parallel processing 2 Perceiving Words in Sentences Perceiving Words in Sentences Speech segmentation: the process of perceiving individual words from the continuous flow of the Perceiving separate words you read on paper is speech signals easy- each word is separated by a space, so easy to The problem of speech segmentation: tell one word from another – No clear breaks between words in physical speech signal. However when we hear words in conversational – Difficult to tell where one word ends and the other begins speech, these words are not separated by spaces, pauses, even though they may sound like they are. When we look at the record of the physical energy produced by conversational speech, we see that speech signal is continuous, with either no physical breaks in the signal or breaks that do not correspond to the breaks we perceive between words Mice eat oats and does not eat oats and with lambs eat ivy Accessing Words: Frequency Accessing/Understanding Words Effects What factors influence our ability to Demonstration: Lexical Decision Task access or understand words Carroll (1999): Word or non-word? (Say ‘yes’/’no’): – List 1: Gambastya, revery, voitle, chard, wefe, cratily, decoy, – Frequency effects puldow, faflot, oriole, voluble, boovle, chalt, awry, signet, – Context effects trave, crock, cryptic, ewe, himpola. – List 2: Mulvow, governor, bless, tuglety, gare, relieve, ruftily, history, pindle, develop, grdot, norve, busy, effort, garvola, match, sard, pleasant, coin, maisle. Result: – people read lists of common words (many in List 2) faster than lists of less common words (many in List 1) – Word-frequency effect - High-frequency words are recognized and read faster than low- frequency words Accessing Words: Frequency Accessing Words: Context Effect Effects Easier to understand words that fit the meaning of a sentence. Rayner et al. (2003): Eye-movements during reading Example (Marslen-Wilson, 1990): – ‘Sam wore the horrid coat though his pretty girlfriend complained.’ 1.‘The Eskimos were frightened by the walrus.’ – ‘Sam wore the horrid coat though his demure girlfriend 2. ‘The bankers were frightened by the walrus.’ complained.’ – Walrus is understandable easier in 1st sentence Result: Fixation is shorter at high frequency words – Fixation time : High frequency word (pretty) Context helps to disambiguate (to clear up lexical < low frequency word (demure) ambiguity, though perhaps not straight away) – Example: ‘My mother is bugging me.’ ( Bugging ~ refer to my mother is annoying me, rather installing a hidden listening device in my room) 3 Accessing Words: Context Effects David Swinney (1979) –Presented participants with tape recording of a sentence. ‘Rumor had it that, for years, the government building had been Understanding Sentences plagued with problems. The man was not surprised when he found several spiders, roaches, and other bugs in the corner of the room.’ Lexical-decision task at ‘bug’: After hearing the word bug, participants How do we understand sentences? were shown a word or nonword onto the screen and asked to indicate whether it’s a word or nonword. Measured RT for ANT, SPY & SKY. – Semantics Result: Participants accessed faster to the 2 meanings of an – Syntax ambiguous word “bug” – ANT and SPY (as indicated by significant RTs) – but select rapidly the one that fit the sentence – Parsing a sentence Semantics vs. Syntax Understanding Sentences Physiological distinction in ERP (Osterhut et al., 1997): To understand sentences, need to distinguish the two properties of sentences: – Syntax: grammatical rules of combining words into well-formed sentences. – Semantics: meaning of words and sentences. (a)The N400 wave of the ERP is affected by semantics. It becomes larger (dark line) when the meaning of a word does not fit the rest of the sentence. (b) The P600 wave of the ERP is affected by syntax. It becomes larger (dark line) when syntax is incorrect. Parsing a Sentence Parsing : the mental grouping of words in Parsing a Sentence a sentence into phrases – One of the central process for determining meaning. 3 approaches to parsing a sentence: Demonstration: Syntax first approach – The spy saw the man with the binoculars. Semantics – Flying planes can be dangerous. Interactionist approach – He read the paper that he received yesterday. => Syntactic ambiguity : due to multiple possible parsers (sentence-analyzing mechanism) that determine the various meanings of the sentence (based on how the phrases are grouped) How does the parser work? 4  Parsing: The Syntax-First Approach Parsing: The Syntax-First Eg. “Because he always jogs a mile seems like a Approach short distance to him”. Parsingis primarily determined by syntax and syntax-based rules. Syntax-based rules: – Late Closure : when a person encounters a new word, the parser assumes that this word is part of the current phrase. These sentences are also called “garden-path sentences” because the sentences have led the reader “ down the garden path” (down a path that seems right, but turns out to be wrong) Semantic Influences on Parsing Semantic Influences on Parsing: Daniel Slobin (1966) compared the speed of participants to The meaning of one word can affect the ability to understand these 2 sentences by presenting a picture along with each sentences – say TRUE if the sentence below the picture described understand the entire sentence: Eg: it or FALSE if it did not. “The man recognized by the spy took off down the street.” It takes longer to understand(verify) reversible sentences as in (a). Need to identify the doer (who took the action) and the done to (who received the action) Semantic Influences on Parsing: The Interactionist Approach Parsing: Claim: Syntax and semantics interact during parsing, i.e., syntax affects early processing. Another example: – Semantics come into play as a sentence is being read “The van recognized by the spy took off down the street”. Evidence: Eye-tracking studies (measuring the fixation-durations. – Trueswell et al. (1994): – In his eye-movement study, he determined the amount of time the participants’ eyes spent on different parts of sentences 1 and 2. 1. ‘The defendant examined by the lawyer turned out to be reliable’ 2. ‘The evidence examined by the lawyer turned out to be reliable’ 5  Parsing: The Interactionist Approach Parsing: The Interactionist Approach Results of Trueswell at al.’s (1994):Semantics immediately affect Tannehaus et al.(1995) use another approach of eye movements processing to study how people process information in sentences – He presented a picture that illustrate the objects mentioned in a sentence, and to determine where participants look while they listen to and trying to understand the sentence “ Put the apple on the towel in the box” 1-apple: where? 2-apple: which? Readers spent more time on the phrase “by the lawyer” for sentence 1 (“The defendant….”) than for sentence 2 (“The evidence…”). Why? Sentence 1 > ambiguous than sentence 2 – Defendant could examine something or be examined by someone else – Environmental context helps to disambiguate – Evidence, can only be examined immediately Inferences in Text Comprehension 3 types: Anaphoric, Instrumental and Causal Inferences How do we understand Text or Anaphoric Inferences – connect an object/person in Stories? one sentence to object/person in another sentence Using inferences 1. Beatrice arrived. She was wearing the shirt, that her friend had made. It was awful. 2.“… on our vacation time [we] go down to our ranch (…) There are lots of ponds and I take the kids out and we fish. And then of course, we grill them.” – quoted from George Foreman Instrumental Inferences- inferences about tools/methods Why is human language unique? 1. “He was pounding the nail when his father came out…” (Was he using a hammer?) Once you learn a human language, you can use it to say absolutely anything 2. “Shakespeare wrote Hamlet at his desk.” (Was it a quill pen that he used for writing? Did he use a whether you have heard it before or not. laptop computer?) Infinity capacity – You can construct a short sentence or Causal Inferences – inferences about causal-effect 1.She took an aspirin. Her headache went away. sentence as long as a dictionary (we infer that aspirin caused the headache to go It is stimulus independent away) – What you say is not necessary tied to what 2.She took a shower. Her headache went away. (we happens to you infer that shower caused the headache to go away) 6  Language and Culture: How does thinking (cognition) affected by How does culture affects Language Language? Yum (1991): Japanese more indirect than US Americans. – “It is cold today” vs. “The door is open” (to mean “please shut the door”) Fernald & Morikawa (1993)- observed interactions between Which two of the objects mother and her 6-19 month children – American mothers uses twice as many object labels Would you place together? e.g: “that’s a car. See that car? You like it? It’s got nice wheels.” – Japanese mothers were twice as likely to talk about relationships & how to be polite. e.g: “Here!It’s a vroom vroom. I give it to you. Now you give this to me. Yes!Thank you.” => Cultural orientation & the way parents talk to their children Objects like the ones Chiu (1972) used to determine which objects influence attention and perception of adults Chinese and American children group together. Language & Cognition (cont’d) Summary Definition of Language Understanding words – Effects of words: Word-superiority effect – Effects of words in sentences: the role of frequency & context Word-frequency effect Understanding Sentences – Parsing sentences Syntax first approach The results make sense: Americans are more object-oriented and Semantics Asians are more relationship-oriented Interactionist approach Summary Language and culture – Culture can influence one’s use of language Language and the brain – Aphasia Broca’s aphasia Wernicke’s aphasia 7  Visual Imagery In today’s lectures, we will discuss: What is Mental Imagery? What is Visual Imagery? The Imagery Debate Spatial vs Propositional representations in the mind Imagery & Perception Imagery & Memory Imagery & the Brain KMF 1023 COGNITIVE PSYCHOLOGY Lecturer: Norehan Zulkiply FSKPM, Universiti Malaysia Sarawak What is imagery? Mental imagery: forming images in your mind even though the actual stimulus that you are The Imagery Debate: imagining is not present experiencing a sensory impression in the absence Spatial vs Propositional of a sensory input representations Visual imagery: “seeing” in the absence of a visual stimulus (eg. counting the number of windows in your home, describe your mother’s face.) Applies to other senses too, eg: smell, taste, touch Visual Imagery Visual Imagery Shepard & Metzler (1971)’s Results: experiment on Mental Rotation Linear relationship Participants were asked to look at the two pictures and decide quickly between reaction whether they represent two different time(RT) and angle of views of the same object OR two orientation different objects Showed that Measured the time taken to participants were rotate abstract objects rotating image of the RT for (b) > RT for (a) objects in their mind It took longer to compare 2 objects during the that are separated by a large angle, experiment then it took to compare 2 objects that are separated by a smaller angle Prove the existence of Mental Rotation 1  Visual Imagery Shepard & Metzler (1971)’s experiment on Mental Rotation was so influential Imagery & Perception – do they share the Demonstrated a parallel between imagery and same mechanism in the brain? perception Imagery is not vivid/long lasting BUT shares many We see an object moving through space when we properties with Perception see a real object rotating, and that we have Linear trend in rotation...suggests spatial similar experience of movement through space correspondence when we rotate an object in our mind The spatial experience for both imagery and perception match the layout of the actual SEE (perceive) object rotates & IMAGINE object stimulus. rotates Further support from Steven Kosslyn – image scanning experiment Participants create mental images and then scan Do they share the same mechanism? them in their minds Visual Imagery: Image Experimental evidence for image Scanning scanning Stephen Kosslyn (1980, 1994) To investigate the time it takes to Visual imagery is spatial in scan between two locations on a nature mental image (spatial = involving space)  a representation in which different parts of an image can be described as corresponding to specific locations in space It should take longer to find things within imagery that are further apart Experimental evidence for Experimental evidence for image scanning You are Here image scanning Participants are shown a map of an Results: island containing a The farther apart the two objects were, the greater hut, a tree, a rock, the reaction time a well, a lake, sand, and grass When people operate on mental images they appear to Learn the map of the go through a process analogous to actually operating island then imagine on a physical object the whole map Although they did not have the actual map in their Participants were then heads, they were going through a process similar to asked to mentally the physical operation travel between the various locations on the island and be the time it takes to scan between objects in a mental aware of about how image is a function of distance between the objects. long it took to move between the locations 2 Image scanning : Associated data Visual Imagery Linear relationship Support for visual imagery as a spatial between distance and representation: response time Mental rotation (remember mental Mental scanning rotation) Further support Is there another explanation to the that imagery is spatial in nature mental rotation and scanning data? The Imagery Debate Propositional nature of Imagery The imagery debate... Pylyshyn: Just because we experience imagery spatially,doesn’t mean the underlying representation Zenon Pylyshyn (1973): is spatial Proposed that imagery is related to Imagery has a propositional representation – in mechanisms associated with language which relationships can be represented by symbols. use words to represent objects and relationship between Imagery is propositional in nature objects instead of visual / spatial as suggested by eg. In (dog, bathtub) Kosslyn A spatial (depictive) representation of “in(dog, bathtub)” would look something like this... Propositional nature of Imagery Propositional nature of Imagery Spatial (depictive) Proposition