PSYC 3334 Chapter 8 Notes

8.1

Knowledge: What we have learned about the world around us

• information is obtained thru perception, refined thru reasoning, and stored in memory

  • we learn thru our sensory abilities and beyond our immediate surroundings → acquire more info from other ppl like school, books, media

Knowledge is tightly linked to perception

• imagery relies on perceptual mechanisms in the brain

• recalling memory activates the brain areas involved in perceiving the original event

Embodied cognition/grounded cognition: theory that shared representations are used for perception, action, and knowledge and that the body and physical experience help shape cognition

• argues that shared (common) representations are used for perception, action, and knowledge

  • EX: a pen involves the same cognitive and brain representations as those used when seeing a pen or writing with a pen

Categorization: processing of grouping items or ideas together and distinguishing them from other items or ideas

• can also be understood as concepts: mental representations that correspond to objects or ideas in the world (can be concrete like books or abstract like fairness and happiness)

  • EX: object recognition, chick is a chick, boat is a boat.

Categorization is useful for at least 3 reasons

• categorization facilitates communication → allowing to convey ideas to others effectively

  • categories allow us to summarize multiple properties of an object using a single label

    • EX: telling friend that you saw a bamboo-eating, black-white animal that weighs up 250 pounds, WHEN you can just say you saw a panda bear

• Categories permit inference, which allows you to generalize from prior experience to understand a new object or event

  • can use categorization to infer or assume properties of an object, even invisible features, which enables you to predict properties of a new instance based on what you know about its category

    • EX: if you learned a robin has sesamoid bones (tiny bones like sesame seed), then you may infer that other birds have sesamoid bones too

• Categories facilitate perception, decision, and predictions

  • people are more sensitive to perceptual differences between objects from different category than when they are from the same category

    • heightened sensitivity to categorical differences can also be seen in brain responses

      • EX: you’re taking a new class and want to do well in it. You know from other classes you should read the books on time and attend lecture

How to form and distinguish categories?

• one idea is to agree on definitions for different categories

  • EX: a rectangle is an object that has 4 sides. If new object (sqaure) appears, you may ask if it’s a rectangle bc it satisfies the definition of a rectangle

    • definition approach breaks down quickly when considering it’s frequently impossible to develop a comprehensive definition that works in the real world

  • concept of game is well understood but challenging to define

    • game: activity engaged in for diversion or amusement

      • applies well to games like hide-and-go-seek or Minecraft → but what about recreational running or the deed? Would you call that a game?

• Feature-based categorization: categorization where categories are defined according to a set of characteristic features

  • Key feature of once you possess a category, you can place new examples/prototypes into it based on the similarity or resemblance to other members of the category

    • EX: category of bird consists of robins, sparrows, and hawks → all have wings and lay eggs → wings and laying eggs are features of this category

      • Children do well in readily extending learned names for unfamiliar objects based on similarity in shape

  • Family resemblance: items in a category tend to share features (some variation is tolerable)

    • defining features are probabilistic but usually not absolute

      • EX: can fly may be a common feature for birds, but it’s not a necessary feature required to be a bird (like ostriches)

• Exemplar-based categorization: theory of categorization proposing that we store numerous, previously encountered exemplars from a category in mind and then match new instances to the stored representations when deciding whether they belong

  • items within a category being similar to each other

    • exemplar approach appears to actual specimens of a category instead of relying on average instances or ideal prototypes

  • exemplar models suggest that we store all the specific examples shown in our mind, while prototype models propose that we store an average instance in our mind

    • when a new instance is observed, our mind matches it against all the stored examples

      • EX: when you see new movie in science fiction genre, prototype models assume you’ll categorize it in comparison to one generic representation in mind that averages across all science fiction movies

        • Exemplar models propose that you compare it to all the specific science fiction movies that you know, like Star Wars, Transformer

Exemplar models predict many findings used in support prototype models

• including typicality effects that allow us to quickly categorize common category examples (apple vs kumquat)

  • can predict bc the imply that there will be more examples of common objects in mind (don’t need to store all experienced examples)

• Exemplar models work better for outliers that deviate from typical category members (ostrich) → very different from bird prototype but ca be categorized bc we store it as an exemplar

• exemplar and prototype models don’t exclude each other

  • most researchers believe that both models exist in the mind to form our concepts and categories

• Ad Hoc Categories: categories defined in terms of goals or themes

  • problem of it’s hard to find a great way to describe defining features that encompasses outliers

    • some categories cannot be defined with features

      • EX: if category of bachelor is defined as “unmarried man,” the pope would fit in this category → but some ppl might be uncomfortable to say a pope is a bachelor

• EX: things to take on a camping trip → tent, sleeping bag, stove etc…

  • ppl readily group them together even though they look very different from each other

    • unifying feature is the goal to support an outdoor trip, not some shared set of perceptible characteristics like size or shape

Experiment: asked ppl what would they save from their house if on fire

• result: no one required much time to come up with a coherent list (children, pet, family photos, etc)

  • these category items are not perceptually similar to each other in a way that they could be categorized based on appearance

    • suggest that ppl can make goal-based categories very quickly

How to form categories cont.

• Prototypes: a typical or ideal member of a category

  • a prototype or typical member of a category is usually an average of the examples that a person has encountered → ppl categorizes things according to how closely they match a category’s prototype

    • EX: often encounter birds (seeing them in the yard), but rarely encounter penguins

      • robin is a prototypical example of a bird, where a penguin is not

Prototype Experiment: exposed ppl to numerous dot patterns

• half of patterns were variations of one prototype (forming a category), other half was variation of another prototype (forming another category)

  • ppl learn to distinguish these new artificial categories formed around an underlying average pattern, even if the prototype itself (triangle pattern) was not shown in their training

• Result: ppl not only learn prototypes well, but also tend to prefer them over individual examples of a category

  • from multiple examples of a category, ppl learn the average common pattern (prototype) underlying them

• Real-life example: a robin is prototypical bc it shares common features with most birds, whereas penguin is not prototypical bc it looks and acts differently from average bird

Typicality effect: how some members of a category are more representative than others

• if you ask ppl to name examples from a category, prototypes come up first

  • EX: ask ppl name dogs, Labrador retriever is frequently named bc it is the most popular breed of dog in US

Sentence verification task: an experimental task where ppl are asked to verify statements like “a crow is a bird” or “an ostrich is a bird,” they are quicker to affirm examples that are more typical

• reveals graded membership: some items are closer to their category prototypes than others are → items that are frequently encountered within a category are rated as more typical

In sum:

• categories can be defined and used in different ways, depending on the category and task at hand

  • likely that multiple, qualitatively distinct systems perform categorization, each dependent on different neural circuit

• Rule-based tasks may recruit circuits used for working memory and executive control, whereas prototype tasks may rely on visual areas for perceptual learning

Knowledge representation: the study of how categorizes are organized in the mind

• categories are typically in a hierarchical relationship (general to specific) with each other

  • categories can have other categories within them or may be part of larger categories

• Hierarchical structure raises question of what is the most useful lvl of categorization in everyday life?

  • most common categorization lvl is basic-level category

    • level of category that typically comes easily to most ppl’s mind (car) in contrast with superordinate category (vehicle) and subordinate category (Toyota Camry)

      • ppl use basic-level categories in naming tasks, and learning these concepts is an important part of learning language

        • when you see a dog, you will usually call it a dog rather than the specific name of species (subordinate) or animal (superordinate)

Superordinate: categories that contain subcategories

Subordinate: categories that fit within larger categories

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Hierarchical semantic network: organization of knowledge into nodes (pieces of info) and links (the connections between nodes) using a hierarchical structure

• Properties of categories are stored at higher lvl properties so that they can be generalized to categories underneath them (subcategories), which helps avoid duplication

  • Specific properties that are unique to certain categories are stored at lower lvls

• this structure minimizes redundancy in organization of knowledge

  • EX: don’t need to separately specify that each of these specific examples of pine, oak, rose, and daisy all have roots → just need to specify the feature of having roots in the superordinate plant node (bc they are all plants)

Spreading activation: idea that word meaning and concept link to each other in a mental web

• Activation of words within this web spread and activate related words

  • info travels across connections between nodes → the longer the connection, or the more nodes that need to be traversed, the more time it will take to answer questions about the two nodes

    • Analogy: airplane flying routes between airports

Structure of knowledge can be probed by measuring the speed of spreading activation

• Experiment: sentence verification tasks

  • ppl need to quickly answer whether simple statements are true or false → “A canary is yellow” or “A canary is an animal”

• Result: “A canary is yellow” is the faster response (shorter connection and activation between nodes)

  • these measurements can be used to sketch the structure of hierarchical semantic networks

    • facts that are quick to verify are closer together in the network model than facts that are slow to verify

Connectionism / neural nets / parallel distributed processing

• the representation of knowledge in a distributed manner across connections between multiple nodes

• similar to hierarchical semantic network approach, connectionist models have nodes and links

  • but facts in connectionist models are not stored in single nodes but are more widely distributed across nodes, influencing each other in parallel

• Active nodes spread their activity to other connected nodes with links that have different strengths (aka connection weights)

  • no single node represents a pen or pencil

    • instead, any given node or connection may be involved in the representation of multiple concepts, and it’s the unique pattern across activated nodes and links that differentiates them

Connectionism mimics principles of brain processing

• ppl are better than machines at perceiving the word bc of its design

  • neurons are massively connected and process information in parallel → helping brain to handle imperfect info better and allowing the “simultaneous consideration of many pieces of info or constraints”

• parallel processing is important in variety of tasks (from reach out a pen while avoiding shape corner of desk to recognizing words in natural language)

EX: Ink Blotches → makes letters ambiguous

• but meaning of the words and presence of clear letter help ppl read these words without problem

  • parallel processing can resolve ambiguous or noisy info bc it simultaneously considers context and other info

Process of reading (applying parallel distributed processing model)

• start with nodes that detect visual features distinguishing letters in different positions in a word

  • seemingly complex but conceptually simple

• Have a layer of different visual features on the “bottom”

• different combinations activate different concepts in the word layer at the “top”

Imagine model is viewing letter T as input

• horizontal and vertical lines of T will activate the first two nodes (units) in the feature layer, which then activates the T in the letter layer

  • these connections are excitatory (connections between features or neurons in which activating one raises the likelihood of activating the other)

    • represented with arrows, meaning that feature units make it more likely that the receiving letter unit will be activated

• At the letter layer, when T is active, it should try to reduce the chances that other letter will be active → has inhibitory connections with other letters

  • inhibitory: connections between features or neurons in which activating one decreases the likelihood of activating the other

• When T is activated in the first letter position, it will increase the chances that words like TRAP, TRIP, TAKE, and TIME will be active, while reducing activation of ABLE and CART since those words don’t start with T

Cognitive Architecture: theories and models that explain how knowledge is learned, organized, and used to perform cognitive tasks

• EX: adaptive control of thought - rational (ACT-R) theory

  • math and programming framework that performs cognitive tasks and produce intelligent behavior

    • ACR-R can predict performance time, accuracy, and neural activations, comparing favorably with human empirical data

ACT-R has different modules (independent parts) that perform distinct functions

• include perceptual-motor modules, which interface with the world, memory modules which include a declarative memory module for acts, and a procedural memory module for skills

  • these modules interact simultaneously to perform cog tasks that involve understanding a situation or problem, then choosing the appropriate action or solution for it

    • EX: ACT-R tutors can assess the difficulties a student may have in learning math and provide tailored assistance

Cog Architectures are important (like ACT-R)

• apply to a broad range of cog tasks like skill learning, categorization, and factual memory retrieval

• they ground the development of better AI systems

• ACT-R enables smart tutoring applications that can be nearly good as humans

Neural representation of concepts

• organization of brain’s data folders can be inferred from pt data and from neuroimaging data

• Ppl with prosopagnosia (face blindness) have selective deficits for face processing, and object processing remains intact

  • some ppl show normal face processing but are selectively impaired at object recognition → ruling out possibility that face processing is a more difficult form of object recognition

    • brain imaging has confirmed separate cortical areas for face and object recognition

How are concepts organized in brain?

• can search for categories that show selective impairments and brain activation (animal, food and artifacts are stored separately in the brain)

  • EX: representation of living things and human-made artifacts appear to be segregated in the brain

    • some ppl are unable to label living things and good, but can identify inanimate objects and vice versa

    • another pt was not able to name animals but is good at naming nonanimals, also can’t name animals based on their typical sounds

      • suggesting deficit is not visual agnosia but a deeper semantic problem

Deficits suggest that brain stores info categorically (separate folders for animals, nonanimals, living thing, tools etc)

• accidentally deleting or misplacing one folder will make an entire category inaccessible

  • Domain specific hypothesis: throughout course of evolution, certain categories of objects gained privileged processing in the brain, leading to specialized circuitry and brain areas

    • Like face processing, scenes and places, body parts, and living vs nonliving things

Why brain treat animate and inanimate categories differently?

• Sensory-functional account: idea that object concepts are grounded in perception and action

  • semantic knowledge is not just symbolic or abstract, but also stored according to whether it is primarily sensory or primarily functional

    • objects and their properties (how they look or used) are stored in sensory and motor systems activated by that object

  • ability to name living things (snakes) is based on sensory info on how snakes look

    • but ability to name tools and artifacts (hammer and nail) depends more on motor actions involved with grasping and performing actions with these objects

• Related to embodied cognition theory, in line with idea that object concepts are grounded in perception and action

Supporting studies

• revealed separate cortical activations for naming ppl, tools, and animals (similar to those areas that are damaged in pts)

  • naming pics of animals activates regions that are important for processing perceptual features, whereas naming tools activates brain regions that are involved in action

    • even answering questions about animals and tools activate corresponding brain areas

• Experiment: ppl were showed achromatic (uncolored) object pic or word names (wagon) and asked to generate action words associated with the object (pull) or colors related (red)

  • the word task activated areas related to action and motion, whereas color task activated regions associated with sensory and color processing

• Different study → the verb EAT produced activity in brain area involved in gustatory responses, where the verb RUN activated activity in brain area involved in perception of biological motion

Not all categories have specialized brain areas

• most categories like shoes and purses don’t have dedicated brain areas that can be isolated by brain imaging or that lead to specific deficits when those areas are damaged in pts

  • their representations are more distributed and intermingled with other categories

• rarely see a pt with a selective deficit for bikes but not for vehicles in general

  • most of our knowledge is represented in distributed and interconnected networks spanning different areas of the brain

Categories and knowledge distributed across NEED to have ways to connect related facts back together

• without the ability to connect info, ppl can encounter problems

  • EX: Mr. M with semantic dementia (gradual deterioration of semantic knowledge) → what are sheeps? Can’t recall sheeps are source of the wool jacket he was wearing or roast lamp he ate

• Pt like Mr. M shows the need for a separate hub area of the brain, proposed to be in the anterior temporal lobe

  • the hub links knowledge distributed across the brain, allowing one to assess the connections between concepts that are perceptually and functionally different

    • in Mr. M’s case, sheep, wool, and roast lamb are all related facts. But they are all stored across different brain regions, and he was unable to associate them with each other

8.2

Intelligence: ability to reason, solve problems, and gain new knowledge

• definition is broad enough to elicit agreement from most intelligence researchers and experts

  • but attempts to create a more concrete definition have been less successful

    • EX: when two dozen theorists were asked to define the term, they gave two dozen answers

Intelligence research attempts to understand the degree of individual differences in cognitive ability

• there are variations among people that contribute to intelligence

• Is intelligence fixed or malleable?

  • some ppl define intelligence as “mental energy” → might contribute to a person’s raw info-processing power

    • but expertise, practice, determination, and other characteristics shape how such power translate into real-world outcomes

• Differences in how we define intelligence can cloud attempts to answer questions about what shapes it and whether it can be improved thru training and education

Psychometric approach: in the study of intelligence, an approach that seeks to measure intelligence quantitatively

• researchers try to understand the neurocognitive processes that are involved in intelligent behavior

  • can explain how much of intelligence is heritable and how it can be predicted from brain activity and other biological differences

    • also considers how intelligence is correlated with other cognitive skills (speed of processing, working memory, and executive control)

Intelligence research

• Alfred Binet & Theophile Simon: develop a test that would aid in placing schoolchildren in the appropriate classes

  • created system for identifying how intelligent a child is relative to others

• items were designed to tap into mental abilities that contribute to academic aptitude and success

  • one of test’s strengths was its ability to compare children based on their (age lvl whose average performance matches the test-taker’s score)

    • If a 6 year old’s score equaled of the average 7 year old, then the 6 year old would have a mental age of 7

Items on test

• EX: questions that asked children to repeat 3 numbers, state facts, think of rhymes for a given world and critique absurd statements

Standford Binet intelligence scales: a widely used test of intelligence and the score of the term intelligence quotient (IQ)

• adapted by Lewis Terman from Binet and Simon

• IQ: calculated by dividing a person’s mental age by their chronological age and mulitplying by 100

  • Important to note: this method is only meaningful to children and teenagers → it doesn’t make sense to compare (not much difference between average 35 and 38 year old)

Termon’s discovery

• found positive correlation between children’s IQ measured by tests and the degree to which teachers rated their intelligence → helped the Standard-Binet test become widely adopted

  • US military used it bc of involvement in WW 1 → pressing need to make efficient recruit assignment

    • intelligence testing was then modified so they can administer to many people at once

Wechsler scales: widely used contemporary tests of several subscales of intelligence in adults and children (21st century)

• aimed to measure the global capacity of a person to act purposefully, to think rationally, and to deal effectively with their environment

• provided a significant advance for the psychometric approach by attempting to minimize the degree to which intelligence scores were shaped by linguistics and cultural differences

• Have 2 tests for age groups

  • Wechsler Adult Intelligence scale (age 16 or older)

  • Wechsler Intelligence Scale for Children

Wechsler scales assess performance on several scales

• some rely on verbal response from test takers and some require them to perform visuospatial tasks

  • verbal items assess general knowledge, vocab, comprehension, and math performance

  • nonverbal (or visuospatial) tasks include arranging a series of pictures into an appropriate sequence, completing unfinished pics correctly, and piecing together segments of an object into a whole

Subscales on Wechsler scale

• Verbal Comprehension Index: include tests of vocab, factual knowledge and etc → ask test takers to recognize similarities

• Perceptual Reasoning Index: block design and matric reasoning, nonverbal abstract problem-solving and picture completion

• Processing Speed Index: include speeded visual search tests and tests of visual-motor coordination

• Working Memory Index: tests digit span, mental manipulation of math problems, and combined tests of attention and working memory

Concept of IQ also changed with the Wechsler test

• IQ is derived by placing an individual’s score on a frequency distribution relative to other same-age test takers

  • bell curve, normal distribution

What do Intelligence scores predict?

• good predictors of academic performance

  • general intelligence measured at 11 was associated with later educational achievement on national exams at 16

• But IQ only accounts for one portion of variance among students

  • other factors include motivation to study and persistence

    • EX: an unengaged student with high IQ won’t perform better than a student who is passionate, persistent, and dedicated

Study: broad review examined what predicts a university student’s GPA

• Result: largest correlate was performance self-efficacy

  • an individual’s belief in their ability to succeed based on their experience with similar challenges

• believing that one has the ability to succeed academically and having an accurate perception of one’s academic performance capability are strong predictors of college grades

Relationship of intelligence scores and academic outcome

• can be affected by factors like teaching practices and cultural values

  • Chinese and Japanese children score better in math than American kids, even when having the same IQ scores

• scores received in early elementary school years also appear to predict how many years a child will stay in school

  • might also reflect the influence of social factors → children who achieve higher test scores are likely to receive greater amount of encouragement from teachers

Relationship of intelligence scores and life outcomes (job performance)

• gifted children (selected from top 0.01% of math and verbal ability at 13) then tracked for more than 2 decades shows that they achieve excellence and leadership in business, healthcare, law and etc

  • not to say that only test-based intellectual ability matters, but its one early way to identify future potential

• Can predict how long a person is likely to live

  • study: women who scored at least 1SD below average in IQ when 11 were 75% more likely to only live to 76

    • reason can be bc the longevity depends partly on learning, planning, and problem-solving skills that are useful in avoiding accidents and adhering to complicated treatment regimens (skills that are related to intelligence)

  • efficiency of info processing (measured by simple or choice reaction time) → account for finding that ppl with higher IQs live longer on average

General Intelligence (g): idea of intelligence as a source of individual variation that causes some ppl to score higher than others on a broad range of cog measures

• Spearman found that ppl who perform highly on one subscale tend to perform highly on another scale (not perfectly correlated)

• suggests that although there is variation across many measures, single g factor accounts for a large degree of variation among ppl

  • maybe should be accounted as a fundamental principle of cog science?

    • other claims argued that variation among ppl can be best accounted for by assuming the existence of multiple dimensions of intelligence

Specific Intelligence (s): intellectual abilities that are specific (EX: math) rather than general (EX: all subjects in school)

Two-factor theory of intelligence: theory that intelligence is a combination of a general ability combined with specific abilities

• distinctions between general and specific ability are similar to those that can be found in many domains

  • EX: pro tennis player might excel at hitting powerful swings, but can be less reliable in volleyball

    • the tennis pro’s general ability will still be higher than average recreational players tho

Crystallized intelligence (Gc): Knowledge as reflected in tests of vocabulary and facts about the world

Fluid Intelligence (Gf): content-independent analytical processes that come into play when discerning patterns in the environment, understanding analogies, and drawing inferences

• measures of fluid intelligence attempt to index this ability independent of experiences and knowledge

  • sometimes regarded as central to general intelligence

    • EX: professor is likely to have the most crystallized intelligence in terms of knowledge about the subject matter, but some professor is not necessarily better than their students at solving puzzles or other fluid intelligence tasks

How to measure fluid intelligence separately?

• approach is to test ppl’s abilities to perceive and learn patterns involving unfamiliar stimuli → done in several Wechsler scales or Raven’s Progressive Matrices

  • a measure of fluid intelligence where ppl see configurations of an undisclosed pattern and must pick the next one in the sequence

Most intelligence research focuses on the individual or on what makes some particularly intelligent but ppl often find themselves working together in groups

• Collective intelligence: the intelligence exhibited when individuals work together and make sound decisions in groups

  • appear to be unrelated to average or highest individual intelligence score within a given group or to factors like group cohesion, motivation, or satisfaction

3 factors that account for collective intelligence of groups

• average social sensitivity of group members was positively correlated with collective intelligence → measured via reading the mind in eyes test, where ppl attempted to identify facial expressions of emotions when seeing only eyes

• groups where members contributed relatively equally to the conversations tended to score high on collective intelligence → groups where convo was dominated by few ppl exhibited lower collective intelligence

• groups with higher proportion of female members scored higher in collective intelligence → suggested result might have been driven by the female participant's’ higher scores in social sensitivity

One intelligence or Many?

• competing view of intelligence is better viewed as a collection of different competencies

  • Aristotle suggested ppl could exhibit theoretical intelligence (ability to learn nuances of math, science, and complex reasoning) → different from practical intelligence (ability to govern one’s actions wisely)

    • suggested ppl could be characterized in terms of their productive intelligence (ability to create and make things)

Triarchic theory of intelligence: theory that differentiates among analytical, practical, and creative intelligences

• been criticized that different forms of intelligence correlate with each other, questioning the assertion that they are separable

  • Analytical intelligence maps roughly onto IQ measures and is most linked with traditional notions of general intelligence

  • Creative intelligence involves ppl’s abilities to reason in novel, or “nonentrenched” ways

  • Practical intelligence pertains to ppl’s abilities to meet the challenges they encounter in everyday life

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Thurstone (1938) argued against notion of g

• suggested that evidence favored existence of seven separate intelligences

  • Verbal fluency, comprehension, numerical computation, spatial ability, associative memory, reasoning, perceptual speed

• used factor analysis: a stat procedure that takes several independently measured variables and determines the number of underlying factors that best explains the data variance

  • EX: factor analysis of all the courses college students take would likely result in quantitative courses loading onto one factor

    • lit courses loading onto another factor and etc

Carroll (1993) suggested three lvls of factors

• overarching general intelligence, middle lvl of factors similar to those identified by Thurstone, and a lower lvl made up of basic processes such as visual processing speed

Multiple Intelligences Theory (Gardner): intelligence is not a general ability but a collection of abilities that ppl use to solve problems or produce useful creations (argues against notion of general intelligence)

• musical, bodily/kinesthetic, spatial, verbal, logical/mathematical, intrapersonal, interpersonal, ability to understand patterns in the environment

Key Observation of multiple intelligence theory:

• ppl can be profoundly impaired in some mental skills while retaining impressive skills in another domains

  • Savant Syndrome: condition characterized by having impressive skill in a particular domain despite having what appears to be generally low intelligence as traditionally measured

    • EX: Kim Peek has low IQ, but knew all area and zip codes in US and could name all tv stations that transmitted to those regions (impressive memory)

• influential in school settings, where it speaks to teachers’ experiences working with 100s of children everyday

  • Howard Gardner School in Virigina where it provides curriculum that accommodates children who learn the best thru nontraditional means

    • critics of whether it is well supported by objective data

Information-Processing Approach

• understanding of how cognitive and neural processes contribute to intelligence

  • measures of executive function, cog control, and working memory correlate with g

Galton (1911)

• regarded intelligence as relatively fixed, biological driven capacity

• inspired by Darwin, published Hereditary Genius

  • suggested that intellectual ability was biologically inherited and transmitted from generation to generation

• Hypothesized that properties of neural transmission contributing to intelligence also enhance perceptual, sensory, and motor abilities

  • guided his attempt to measure intelligence

• his studies found no relationship between reaction time and sensory acuity and criteria that he regarded as being influenced by intelligence (like social status)

Modern evidence of IQ score being correlated with speed of processing

• Inspection time: shortest exposure at which ppl can render accurate judgement

  • Experiment: ppl viewed brief displays of 2 parallel lines and tried to determine which was longer

    • result: inspection time correlates with measures of both fluid and crystalized intelligence

Working memory and Executive function

• given that working memory is central to holding and manipulating information, increased working memory may be associated with higher IQ → shows moderately high to high correlations with fluid intelligence

  • Experiment: three-back test correlates highly with fluid intelligence

    • ppl must indicate when a presented item is the same as the item they saw or heard three items previously → requires ppl not only to keep a number of items in mind, but also constantly update their store so they add a new item and etc

  • Experiment: active-span task

    • alternating between different types of questions

      • EX: might be asked to judge if a math question is true and then read a word aloud (these two tasks switching across trials)

        • these WM tasks correlate with reasoning ability, reading comprehension, and IQ

Limitation of intelligence

• criticize bc different cultures value different traits and skills, and bc the challenges they face can vary

  • cultural biases can shape ideas about what outcomes and skills are most central to concept of intelligence

• assumption about correct predictive outcomes guide the development of the measured employed → only natural for ppl who score high in IQ test to go on and enjoy success, leading some to say “intelligence is what the tests test”

Individual difference is not the only determining factor

• traditional approaches fail to consider ppl’s ability to recognize and manage emotions aka Emotional intelligence

  • Emotional intelligence is measurable set of skills that involve perceiving emotions accurately, using emotion to facilitate thoughts, understanding emotions, and managing emotion

    • predicts both more positive social relationships and less deviant behavior → useful for both educational and workplace settings

  • Study on companies showed that emotionally intelligent employees received greater merit increases and held higher company rank than their counterparts

Real world outcomes

• interventions been shown to improve educational outcomes

  • Mindset: person’s beliefs about whether their abilities are hardwired or malleable can be a greater predictor of achievement than scores on intelligence tests

    • Fixed mindset: belief that qualities such as intelligence are unchanging

    • Growth mindset: belief that intelligence is something that can improve with practice and hard work

  • Studies: students with growth mindset performed better in school than those who believe intelligence is fixed

    • better to praise children’s efforts than to praise their intelligence bc praising intelligence promotes a fixed mindset that leads to less persistence, less enjoyment, and lower performance

Group differences between gender or race

• focus on whether any report of group differences are valid

  • if they are valid, then can they be attributed to innate biological differences or sociological factors like bias and injustice?

• stronger evidence for socioeconomic influences on IQ over genetic explanation → useful to remember that individual differences in IQ are much greater than any purposed group differences

• many perspectives also ignore creativity (ability to arrive at new solutions and creations

  • ppl are able to do lots of different tasks, can solve different problesm, and have creativity to come up with new solutions when traditional ones don’t work

8.3

Nature: skills that develop regardless of experience

• suggest that specialized learning systems are present or native at birth (nativism)

• Plato and Descartes argued that knowledge is more than learned associations

  • human infants are born to learn certain types of info like language, physics, numbers, and psychology → all examples of specialized domain that children elaborate and refine over course of development called core knowledge

    • these core cog systems equip children to acquire language, understand science, and socialize with their caregivers

Nurture (Empiricist view): human knowledge is built up by forming associations thru experiences w/o innate predispositions

• Berkely and Hume described development in terms of general learning, viewing infants as having very little innate bias toward particular kinds of info → infants lack core knowledge

Both nature and nurture shape development

• most knowledge is learned from experiences

  • but infants appear to come into the world with innate capabilities and biases (core knowledge) that help them learn more effectively

• studying the development of knowledge illuminates these innate and learned capabilities, and also gives us insight to mature cognition

  • study of cog development has direct implications for social policy and education

Heritability: the extent that genetics can explain variation (differences) among ppl → intelligence is highly heritable (example of nature)

• heritability coefficient: variance due to genes / total variance

  • the more variation in intelligence can be attributed to genes, the closer the IQs of close relatives should be

    • one challenge is siblings often grow up in same environment → hard to determine what the relative contribute of genes and environment are

IQ among Twins

• compared IQs among identical and fraternal twins raised together and identical items who were raised apart

  • heritability can be estimated by comparing the degree which the IQs of identical twins are correlated with how much those of fraternal twins are correlated

    • degree which IQs of identical twins correlate more strongly helps estimate genetic (heritable) influences

  • Suggest contribution of genetics play a larger role among adults than among children and adolescents

    • some characteristics (like height) develop more fully as ppl mature, and as adult set out on their own, they and their siblings experience less of a shared environment

Genotyping: investigation of the presence or absence of particular genes using biological samples

• researchers have been able to look more directly at the role of genes in shaping IQ

  • several hundred genomic loci and genes have now been linked to variation in intelligence, neural development, synaptic structure, and health-related outcomes like Alzheimer’s and ADHD

Epigenetics: nature and nurture interact, such that environment can modulate the expression of genetic influences

• heritability of IQ is affected by socioeconomic status

  • EX: Impoverished environments seem to lessen genetic disparities among ppl

    • Analogy: innate difference in musical playing ability don’t count for much if no one has access to an instrument or training

Evidence

• structural and functional brain-imaging studies how brain differences that vary with intelligence across ppl

  • result: ppl who score high in fluid intelligence exhibited greater activation in lateral frontal and parietal cortex when engaging in difficult verbal and nonverbal working memory tasks, relative to ppl with low scores

  • Result: revealed that activation of frontal lobes might contribute to individual differences in g → frontal areas associated with working memory were highly responsive across both visual and verbal general intelligence tasks

Intelligence might also reflect coordinated activity across areas of brain

• measuring how different brain regions are in synchrony or out of synchrony with each other

  • using fMRI of these synchrony patterns (functional connectivity), researchers can estimate a person’s IQ

Cog development across life span

• cog abilities improve with age and then decline in later years

  • different cog abilities mature at different rates → peak at different ages

    • EX: vocab continues to improve throughout adulthood, whereas visual working memory seems to peak in mid-to-late 20s

• cog development is closely tied to brain development

  • brain areas for sensory and motor processes mature first, then temporal and parietal brain area with language and spatial attention

    • higher order association areas for executive control of behavior mature last

      • this sequence corresponds to maturation of different cog capabilities over time

• Age-related changes including brain functions emerging that had not existed before anywhere across the brain, staying consistent over time, or reorganizing (moving) from one brain region to another

  • brain development follows a well-defined progression such that from scans of brain connectivity, researchers can determine a person’s brain age

How children learn about the world?

• Piaget viewed children as active explorers who develop across a sequence of distinct periods, with qualitative leaps in abilities occurring between them

  • proposed that, within each period, children acquire new ways of understanding the world, which trigger a transformation that leads to the progression to the next period → each period is necessary for the next one

• Piaget emphasized the importance of active exploration and engagement

  • most children are not passive or blank canvas → similar to “intuitive scientists” that proactively learn about the world around them and construct knowledge through everyday interactions

• modern researchers continue to believe in the value of play and exploration (as long as caregivers provide guidance)

Sensorimotor Period (infancy): a developmental period from birth to about 2 years, during which infants and toddlers learn about the physicality of objects

• object permanence: understanding that objects persist and are stable even when they are out of sight → proposed developmental milestone

  • infants lack object permanence

    • observation: infants won’t look for objects placed out of view (hidden) → out of sight, out of mind

Infant's’ knowledge about physical world is much richer

• Screen Swing experiment: infants watched a screen swing back and forth, reaching the table on either side of swinging motion (habitual event)

  • Possible event condition: when there is a box on the far side of screen, the screen will stop when it swings to the box

  • Impossible event: screen continues to swing even with the box here

• Testing of if infants will look longer at possible or impossible event

  • Result: infants looked longer at the impossible event bc they understand that the screen shouldn’t have been able to swing all the way down to the table → shows infants’ knowledge of object solidity

Preferential looking method: experimental method based on the fact that infants sook longer at events that they find interesting or surprising

Habituation: familiarity or boredom that results from repetition

• infants tend to look at each repetition for shorter amount of time until a new stimulus shows up

  • Dishabituation: re-emergence of a behavioral response that had previously diminished (over time or with repeats)

By measuring preferential looking and habituation, researchers demonstrated that visual acuity, color perception, and depth perception improve over time

• face perception is important for social interactions → newborns prefer intact faces over nonsense faces that have same features (scrambled face)

  • perceptual narrowing: a developmental process which environmental experiences enhance perceptual sensitivity to frequently encountered features while reducing sensitivity to infrequently encountered ones

Infants’ understanding of number concepts and basic arithmetic

• infants can certainly distinguish a display of three objects vs two objects

  • but may be simply bc the array look perceptually different

• infants are sensitive to numerosity → infants can add and subtract

  • Experiment: placing two duckies in a box (can either add or take away a duckie) and either showing only one or two duckies when screen goes down

    • Result: infants looked longer at the unexpected conditions (one duckie left on stage) → can be interpreted as violation of the baby’s expectation

      • suggests that infants can add and subtract

Infants learn to categorize objects → helps to form their knowledge of concepts

• infants categorize at more superordinate levels (not basic lvls)

  • group together animals instead of dogs from fish

    • If shown few boxes with certain objects inside, then they expect other boxes of that type to have objects with similar characteristics

• From early age, infants have strong tendency to search for the hidden features of things (beyond the obvious)

Infants show cognitive understanding of inferred features (intention and helpfulness)

• evidence for core knowledge is important for social interactions

  • when infants observed an actor repeatedly reaching for one of two toys on stage, they look longer when the actor grabs the other toy (a change in goal and intent)

    • no longer looked when an inanimate object performs the same action

• using a variation of common false-belief tasks, 15 month infants demonstrated an understanding of an actor’s true or false beliefs about a toy’s hiding place, demonstrating theory of mind

Preoperational period (childhood): developmental period from age 2 to 7 when children start to think in terms of symbols, allowing them to represent ideas → language is a major hallmark of this period

• believed that young children lacked the ability to think abstractly

  • EX: note a ball of dough gets wider when flattened with rolling pin, but same child would fail at a conservation task with liquid or coin

    • tests how physical properties remain conserved (don’t change) even when their appearance is changed

      • coin experiment: compare number of coins in each line, then experimenter spreads coins apart.

        • Result: child say the longer line has more coins → failure of conservation

• But when experiment is changed to a teddy bear messing up the coins or liquid, preschoolers say the number of objects didn’t change

  • now young children are known to have good conservation skills

Understanding of space

• young children are egocentric → perceiving spatial relations from their own POV, and are less adept at allocentric frames of reference (based on external environment and not focused on own location)

• Experiment: child sitting with doll on opposite side with mountain in the middle

  • Result: children younger than 7 are egocentric → not able to demonstrate how the scene look from POV of doll (different from their own)

    • although shows children’s lack of theory of mind, their failure in spatial tasks is likely due to ambiguities

      • EX: if asked child to place a doll where it could hide from a police officer, then children are more successful in this task

Symbolic representation or models (age 2-3)

• test if young children understand that a model can represent the real world (similar to adults using maps)

  • Experiment: shows children a small model of room and hides an object → children are then introduced to a big room (real-life) and asked to fine the object

    • Result: 3 year old can do the task but not 2.5 year old

      • age 2.5 likely struggled bc they can’t make the connection between the dollhouse and real room (mapping representation to reality)

  • But when introduced a “shrinking machine” that shown the shrink of larger real room into the small dollhouse room

    • Result: younger children performed much better at using the dollhouse to find the object in the bigger room

      • likely bc this info better linked the dollhouse room as a representation of the real room

Concrete operational period: when children acquire thinking and reasoning abilities that allow them to understand conservation of properties even as objects change (acquired mental operators around age 7)

• children can perform the coin and liquid conservation tasks

  • no longer egocentric in spatial tasks, and they demonstrate theory of mind

    • broader understanding that other have different perspectives and thoughts than their own

Formal operational period: developmental period when scientific thinking skills being to emerge (beginning around age 12, adolescence)

• period when a person develops their ability to regulate their emotions and behavior according to long-term goals and consequences

  • learn to make good rewarding decisions, and not impulsive/risky ones

    • behavioral patterns can be explained with respect to ongoing brain development bc prefrontal cortex areas (important for inhibition, impulse control, and etc) do not reach adult lvl maturity until after age 20

• formal operational skills allow child to isolate variables and see how they change when the variables are systematically manipulated one at a time

  • children w/o formal operational skills will vary things randomly

    • EX: when testing what determines the time for a pendulum to swing back and forth, you can manipulate different aspects of the pendulum one at a time to see

      • but children who are in the concrete operational period will not vary those aspects systematically one at a time

• not all children achieve full competence in formal operations

Adulthood

• working memory skills mature and peak at one’s 20s and 30s, whereas vocab continues to develop throughout adulthood

  • as one get older than 70, all cog functions start to show age-related decline

• bc the rate of age-related decline is different across ppl, lots of research is devoted to understanding what allows for resilience across aging, brain damage, and degradation

Development of intelligence and cognition

• early experiences shape cog abilities throughout adulthood

  • quality of home environment and schooling are strong predictors of health and economic well-being

School and Environment

• school education is the "most consistent, robust, and durable method yet to be identified for raising intelligence”

  • intelligence scores tend to drop over summer vacation

• education leads to real-world success

  • study: Perry Preschool Program (longitudinal study) to determine whether disadvantaged children (age 3-4) would benefit from educational interventions

    • Result: Perry group demonstrated higher achievement test scores and higher rate of HS graduation, higher salaries, and higher percentages of home ownership (when tested at 40)

• number of years of schooling is positively associated with academic performance, cog abilities throughout adulthood and old age, higher earnings, and employment rates

  • early interventions to benefit disadvantaged kids should begin at younger ages bc they produce higher returns than later interventions

Environment

• usually talking about environmental quality of socioeconomic status (SES), which considers educational lvl, income, and occupational status of child’s parents

  • lower childhood SES is associated with lower IQ, lower cog achievement, and lower cog brain function (especially for lang processing and vocab, apparent at 18 months old)

  • children from low SES receive less cognitive stimulation in forms of books, lessons, or trips to libraries and museums

    • two years of school had larger effect on intelligence than the lifetime consequences of SES or gene-based inequalities

Severely adverse environments (maltreatment, maternal separation, orphanage)

• associated with lower IQ and delayed cognitive and socioemotional development

  • these negative childhood experiences affect brain development → increasing risk for problems throughout life

    • higher risk for dementia at later ages

How to improve cog performance outside of school/home?

• action video games → improved perceptual skills, attention, and spatial cognition

  • raising hope that computer games can be adapted for use in education and in areas like science, math, and second-language learning

• musical education → provides broader benefits for intelligence and academic performance

  • doubts of study design and analysis

    • musical education should be pursued as valuable in its own right, not a tool to boost intelligence or nonmusical class grades