from study guide

10.1 introduction: the difficulty of defining intelligence

• Definition of intelligence:

  • Intelligence is a multifaceted concept that encompasses various abilities and skills, including problem-solving, reasoning, memory, creativity, and emotional intelligence.

  • While commonly associated with traits like being smart, brainy, or knowledgeable, intelligence is also influenced by factors such as adaptability, practicality, and social understanding.

• IQ and standardized testing:

  • Intelligence quotient (IQ) tests are commonly used to measure certain cognitive abilities, but they have limitations in capturing the full spectrum of human intelligence.

  • Traditional IQ tests assess skills like pattern completion, memory, and analogy comprehension, but they may not fully capture practical intelligence or emotional intelligence.

• Average IQ score and self-perception:

  • The average IQ score in the population is 100, with a standard deviation of 15. Individuals may have varying reactions to discovering their IQ scores.

  • For some, being below or above average may affect self-esteem and confidence, while others may not place much significance on their IQ scores.

• Consequences of knowing IQ score:

  • Knowing one's precise IQ score can have both positive and negative implications.

  • A higher-than-expected score may boost confidence and provide validation, while a lower-than-expected score could lead to self-doubt and feelings of inadequacy.

  • Additionally, negative labels associated with low intelligence may impact self-perception and opportunities.

• Representation in literature:

  • Literature, such as Daniel Keyes' "Flowers for Algernon," explores themes of intelligence, identity, and societal treatment.

  • The story highlights the impact of intelligence on opportunities, social status, and quality of life, as well as the complexities of identity and self-worth.

• Causes of intellectual disabilities:

  • Intellectual disabilities can have various causes, including preventable factors such as fetal alcohol syndrome, birth trauma, and severe child abuse, as well as genetic or chromosomal differences like Down syndrome, fragile X syndrome, and PKU.

  • While there are no cures for these conditions, understanding their origins can inform preventive measures and interventions.

10.2.1 early measures of intelligence

• Early Intelligence Measurement:

  • Before written tests, intelligence was assessed using physiological measures, which were believed to correlate with cognitive abilities. However, these measures lacked psychometric validity and reliability.

  • The concept of measuring intelligence using written forms was first introduced in the early 1900s

• Sir Francis Galton's Contributions:

  • In the late 1800s, Sir Francis Galton, a psychologist and statistician (among other specialties), focused on measuring varied abilities of people using empirical methods to ensure precise assessment.

  • He hypothesized that one’s general cognitive ability (g) was the product of heredity, and believed that intelligence was related to how well one used one’s senses.

  • Galton tried to equate physical measures of the body with mental measurement

  • Profession and Interests:

    • Galton was a psychologist, statistician, and polymath interested in measuring human abilities.

  • Laboratory and Tests:

    • In 1884, he opened a laboratory in England where he charged patrons to undergo physiological tests measuring traits like hair and eye color, as well as sensory sensitivity tests such as weight discrimination and pitch sensitivity.

  • Hypothesis on Intelligence:

    • Galton believed that intelligence was hereditary and linked to sensory acuity. He attempted to predict intelligence and academic performance through physical and sensory tests.

  • Outcome of Galton's Measures:

    • Despite his efforts, Galton's physiological tests did not show valid correlations with school performance, as evidenced by Clark Wissler's study in 1901, which demonstrated no significant relationship between these physiological measures and expected academic outcomes.

• Statistical Innovations by Galton:

  • Analysis of Ability Measures:

    • Galton was one of the pioneers in applying statistical methods to study human characteristics. He demonstrated that the abilities he measured followed a normal distribution, a key concept in statistics.

  • Normal Distribution:

    • Galton observed that most physiological and ability measures tended to cluster around a central value with fewer occurrences toward the extremes. This pattern is known as a normal distribution, or bell-shaped curve.

  • Central Tendency:

    • In a normal distribution, central tendency can be described using the mean (average of all scores), median (middle score when all scores are ranked), and mode (most frequently occurring score). In a perfect normal distribution, these three measures of central tendency coincide.

  • Legacy of Galton's Work:

    • Although Galton's initial hypotheses about physiological measures of intelligence were not supported, his work laid the groundwork for later developments in psychometrics and the statistical analysis of human traits.

    • His exploration of the normal distribution and central tendencies remains fundamental in psychological research and statistics.

example,

• if we measured the heights of 100 men, we would find that most of our results would be heights of 5’7”, 5’8”, 5’9”, and 5’10". - We would find far fewer results of values that are lower or higher than these four values, and the farther we go below or above these central values the rarer the results become.

• Recall from Chapter 2: Methods, psychologists use statistical tools to measure the central tendency.

• One measure of central tendency is the mean, which is the average of all the results obtained. Other forms of central tendency include

  • the median, which is the middle score,

  • the  mode (the most commonly occurring score).

    • With a normal distribution (some may have heard of it described as a bell-shaped curve), the mean, median, and mode are the same value. 

Understanding Variability and Standard Deviation (SD):

• Variability:

  • This concept refers to the degree of spread or dispersion of scores around the mean in a dataset. Variability indicates how much individual data points differ from the average.

• Standard Deviation:

  • SD is a statistical measure that quantifies the amount of variation or dispersion of a set of data values. A low standard deviation means that the data points tend to be close to the mean, while a high standard deviation indicates that the data points are spread out over a wider range of values.

• Application to Biological Characteristics:

  • Normal Distribution in Biology:

    • Many biological characteristics, such as height, weight, and even intelligence scores, tend to follow a normal distribution in the general population.

  • Example of Height:

    • Height is a biological characteristic that is not learned and displays a normal distribution. This means most people's heights cluster around a central average, with fewer people being extremely short or extremely tall.

• Galton's Conclusion on Intelligence:

  • Galton's Hypothesis:

    • Influenced by his findings that many biological characteristics, including intelligence (as measured by the tools at his disposal), formed a normal distribution, Sir Francis Galton (late 1800s) hypothesized that intelligence was biologically innate.

  • Flaw in Logic:

    • Galton equated the distribution pattern of intelligence to those of innate biological characteristics like height, concluding that because intelligence displayed a normal distribution, it must also be innate. This is a logical fallacy; just because two characteristics share a statistical pattern does not mean they share the same biological nature.

  • Analogy for Flawed Logic:

    • Galton's reasoning is analogous to saying all mammals are cats because all cats are mammals, which is a categorical error.

• Importance of these Concepts:

  • Statistical Analysis:

    • Understanding how traits like intelligence can be normally distributed helps in the development of tests and measures in psychology.

  • Biological vs. Learned Traits:

    • While some traits are indeed biologically determined, others, such as intelligence, involve a complex interplay of genetic, environmental, and educational factors. Galton's early work spurred further research into differentiating these factors.

galton

• Galton’s Methods and Results:

  • Context and Time: Late 1800s, England. Sir Francis Galton developed a series of tests based on sensory measurements, such as weight discrimination and pitch sensitivity.

  • Outcome of Galton’s Tests: These tests failed to show a predictive relationship with each other (low concurrent validity) and did not predict academic performance (low predictive validity). This suggested that these tests measured disparate abilities, not a unified construct of intelligence.

• Validity Definitions:

  • Concurrent Validity: This form of validity examines whether one test correlates well with the results from a standard test performed at the same time. Galton's measures lacked this, as they did not correlate with each other, indicating they were not measuring the same construct.

  • Predictive Validity: Refers to the extent to which a score on a scale or test predicts future performance on a related outcome. Galton's tests failed in this aspect, as they did not predict academic success, casting doubt on their utility as measures of intelligence.

• Implications of Galton’s Findings:

  • Critique and Learning: The failure of Galton’s physiological measures to predict academic outcomes led to significant skepticism about the effectiveness of such tests in measuring intelligence. It highlighted the complexity of intelligence as a construct that cannot be directly inferred from simple sensory tasks.

  • Shift in Research Focus: Galton’s initial failures laid the groundwork for future psychologists to reconsider how intelligence should be measured, eventually leading to the development of more abstract reasoning and problem-solving assessments.

• Resurgence in Modern Neuroscience:

  • Neuroscience and Intelligence: With advances in technology, particularly in neuroimaging techniques like functional Magnetic Resonance Imaging (fMRI), researchers have revisited the idea of physiological correlates of intelligence. These tools allow for the observation of brain activity in real-time, providing insights into which brain areas are involved in tasks that require cognitive processing.

  • Continued Debate: Despite these advances, the precise physiological measurement of intelligence remains complex and contested. Neuroscience has deepened understanding but also shown the vast intricacies of brain functions related to intelligence.

10.2.2 binet and simon’s intelligence test

• Context and Motivation:

  • Year: 1904 in France, amidst widespread institutionalization of public education.

  • Purpose: Developed to assist in educational placements by identifying students' intellectual capabilities and thereby allocating educational resources more effectively.

• Conceptualization of Intelligence:

  • Definition: Intelligence was defined by Binet and Simon as the ability to "judge well, to comprehend well, to reason well."

  • Key Abilities: They identified three fundamental abilities crucial to intelligence:

    • Direction: Knowing what to do and how to do it.

    • Adaptation: The ability to devise and implement strategies and monitor their progress.

    • Criticism: The capacity to evaluate and identify errors in one's reasoning.

• Development of the Binet-Simon Scale:

  • Year: Initial scale developed in 1904 and revised until 1916.

  • Approach: The scale consisted of tasks designed for different age levels, reflecting what an average child at each age should be capable of performing. Tasks ranged from simple physical responses to complex cognitive challenges like defining words and understanding analogies.

  • Mental Age Concept: Children's performance was assessed against age-specific standards. A child performing at the level of the typical norms for older children was considered to have a higher mental age, implying higher intelligence.

• Impact and Standardization:

  • Standardization of Intelligence Testing: Binet and Simon's methodology allowed for consistent measurement across different contexts, which is crucial for comparing results across studies and advancing research hypotheses.

  • Legacy: Their work laid the groundwork for future intelligence tests, including the Stanford-Binet test, which adapted their scale for use in the United States.

10.3 the use and misuse of intelligence testing

1. Historical Context and Consequences:

   • Purpose of Binet-Simon Test: Originally designed to help French educators make informed decisions about student placement in educational programs, impacting children's academic paths and future opportunities.

   • Misuse of IQ Tests: Across various contexts, intelligence testing has been misused to justify discriminatory practices, including eugenics and systemic racism.

2. Eugenics and its Influence:

   • Originator: Sir Francis Galton, late 1800s to early 1900s.

   • Definition: Eugenics is the belief in improving human populations through controlled breeding for desirable inheritable traits. It proposed that social worth is hereditary and advocated for reproductive control among "superior" and "inferior" groups.

   • Adoption and Advocacy: Popularized in the United States in the early 1900s and later influencing Nazi ideology.

   • Key Proponent: Lewis Terman adapted the Binet-Simon test into the Stanford-Binet test and was a significant figure in promoting eugenics in the U.S., arguing for sterilization policies to prevent reproduction among those deemed less intelligent.

3. Social Darwinism:

   • Concept: An ideological application of Darwin's evolutionary theory to human societies, claiming that social order is influenced by the survival of the fittest, a misinterpretation of Darwin's work.

   • Impact: Used to justify racial and class superiority theories, providing a pseudo-scientific basis for discrimination and eugenics.

   • Critique: Oversimplified Darwin's theory and misapplied biological concepts to social and cultural contexts.

4. Bias in Intelligence Testing:

   • Issues with Terman's Approach:

     • Language and Cultural Bias: Tests were often not culturally or linguistically neutral, disadvantaging non-English speakers and those unfamiliar with American culture.

     • Consequences: Led to systematically lower scores for immigrants and non-white populations, reinforcing stereotypes and supporting discriminatory policies.

     • Outcome: Biased results were used to argue for racial hierarchies and social policies that favored certain groups over others.

5. Legislation Influenced by Eugenic Ideals:

   • Implementation: Eugenics-based policies were enacted in 30 U.S. states and two Canadian provinces, including forced sterilizations and restrictive reproductive laws.

   • Impact on Nazi Policies: The American eugenics movement significantly influenced Nazi racial policies, including the justification of genocide.

10.3.1 intelligence testing across groups

1. Assumptions in Early Intelligence Testing:

   • Lewis Terman assumed that intelligence tests measured innate intelligence without being influenced by external factors such as language or cultural knowledge.

   • Flawed Assumptions: Terman believed that the distribution of IQ scores validated his tests as measures of innate intelligence, ignoring potential confounding factors like education level, socioeconomic status, and cultural bias.

2. Impact of Socioeconomic Status on IQ Testing:

   • Educational Opportunities: People from higher socioeconomic backgrounds often have better education and are more likely to perform well on IQ tests due to a broader vocabulary and more exposure to the concepts tested.

   • Cultural Bias: Early intelligence tests favored those familiar with American culture and the English language, disadvantaging non-native speakers and those from different cultural backgrounds.

3. Continued Debates on Racial Differences in IQ:

   • Development of Neutral Tests: Tests such as Raven’s Progressive Matrices were developed to minimize cultural and language biases in testing.

   • Rushton & Jensen (2005): Found persistent, though small, racial differences in IQ even with more culturally neutral tests.

   • Limitations: Such tests still cannot fully account for structural inequities like disparities in wealth, education, and healthcare access.

4. Stereotype Threat and Intelligence Testing:

   • Definition: The theory that the anxiety of confirming negative stereotypes about one’s group can impair test performance.

   • Researchers: Claude Steele (1997) and others documented how stereotype threat could lead to poorer outcomes on intelligence tests by increasing anxiety and dividing attention during tests.

5. Mindset and Intelligence:

   • Fixed vs. Malleable Intelligence: Research by Carol Dweck (2002) shows that people who view intelligence as fixed are less likely to engage in challenging tasks, while those who see it as malleable are more resilient in the face of failure.

   • Impact on Performance: Those primed to think of intelligence as fixed may avoid challenges that could expose their perceived limitations, whereas those who see intelligence as malleable might embrace such challenges.

6. Long-term Interventions and Intelligence:

   • Mindfulness Practices: Studies (Tang et al., 2007; Gard et al., 2014) have shown that mindfulness can potentially improve functions related to intelligence, such as working memory and attention, and can help mitigate the cognitive decline associated with aging.

7. Cultural and Scientific Context of Racial Groupings:

   • Non-Genetic Distinctions: Scholars like Smedley & Smedley (2005) argue that racial categories do not correspond to distinct genetic populations and are not scientifically meaningful. Instead, they are culturally constructed based on mutable criteria.

10.4 the nature of intelligences introducing G and S

Charles Spearman (1863-1945) and the Concept of General Cognitive Ability ("g")

• Key Observation: Spearman noted positive correlations among schoolchildren's grades across different academic subjects. This observation led him to propose the existence of a general cognitive ability that influences performance across varied domains.

• Example: A student who excels in mathematics is likely to perform well in other subjects such as science, history, and literature, indicating a common underlying ability.

Introduction of Factor Analysis in Intelligence Testing

• Methodology: Factor analysis is a statistical method used to explore the interrelationships among various variables and to group variables that are highly correlated into clusters, termed as "factors."

• Application Example: If students’ performance in the high jump, long jump, hurdles, and sprinting shows high correlations, these activities would be grouped under a single factor, like "track and field athletics." This factor is distinctly different from another set of activities such as swimming, which shows no correlation with the track and field tasks.

• Purpose: Factor analysis helps in identifying underlying factors (like "g") that explain the pattern of correlations among different cognitive tasks.

Difference Between Factor Analysis and Component Analysis

• Factor Analysis: Focuses on clustering highly correlated variables to identify underlying latent variables (factors) that explain the pattern of correlations. It is used to determine the shared variance among variables.

• Component Analysis: Often used interchangeably with principal component analysis (PCA), it aims to reduce the dimensionality of the dataset, summarizing information with fewer variables. It focuses on total variance in the data.

Significance of Spearman's Work

• Spearman's identification of "g" as a factor underlying diverse cognitive abilities has profound implications for educational psychology and cognitive assessment, influencing how intelligence is measured and understood.

• His methodologies, especially the use of factor analysis, have paved the way for more sophisticated statistical techniques in psychology and other social sciences.

Charles Spearman and General Intelligence ("g")

• Concept: Spearman proposed the existence of a general factor of intelligence, denoted as "g," which represents a higher-order cognitive ability.

• Two Levels of Intelligence: Spearman suggested that intelligence comprises two levels: a higher-order general intelligence (g) and lower-order specific abilities (s) that are domain-specific.

• Example: Verbal intelligence, a specific ability, measures performance on verbal-based tasks, while general intelligence (g) reflects the ability to learn and solve problems across various contexts.

• Predictive Power: Measures of general intelligence (g) have been found to predict various outcomes, including academic performance, career success, and even mortality rates.

• Explanations of g: Spearman proposed two explanations for general intelligence: apprehension of one's own experience and the education of relations and correlates, and the notion of mental energy available throughout the cortex.

Louis Thurstone and Primary Mental Abilities

• Theory: Thurstone's theory contradicted Spearman's concept of a single general intelligence factor (g). Instead, he proposed that intelligence consists of seven distinct primary mental abilities.

• Factors: Thurstone identified these primary mental abilities as word fluency, verbal comprehension, numeric abilities, spatial visualization, memory, perceptual speed, and reasoning.

• Factor Analysis: Thurstone used factor analysis to identify these seven factors, suggesting that intelligence is not unitary but multidimensional.

Significance and Criticisms

• Spearman's theory of general intelligence (g) laid the foundation for understanding intelligence as a hierarchical construct with a general factor underlying specific abilities.

• Thurstone's theory challenged the notion of a single general intelligence factor, proposing a more multifaceted view of intelligence.

• Critics argue that both theories have limitations: Spearman's g may oversimplify the complexity of intelligence, while Thurstone's approach may overlook the existence of a general cognitive capacity that influences performance across different domains.

10.4.1 the debate about general intelligence

Raymond Cattell's Hierarchical Model of Intelligence

• Concept: Cattell's model aims to reconcile Spearman's theory of general intelligence (g) with Thurstone's theory of primary mental abilities by introducing a hierarchical structure of intelligence.

• Top Level: At the top of the hierarchy is general intelligence (g), which comprises two major factors at the intermediary level: fluid general intelligence (Gf) and crystallized general intelligence (Gc).

• Fluid Intelligence (Gf): Refers to the ability to think flexibly and handle complex and novel situations. It involves problem-solving abilities that are not based primarily on pre-existing knowledge.

• Crystallized Intelligence (Gc): Refers to the ability to solve problems by applying previously accumulated knowledge. It involves the application of learned information and skills to new situations.

• Influence: Cattell's distinction between fluid and crystallized intelligence has had a significant impact on psychology, providing a framework for understanding different aspects of cognitive functioning.

Developmental Relationship

• Initial Correlation: Fluid and crystallized intelligence are highly correlated during early development when individuals are acquiring both problem-solving skills and knowledge.

• Divergence in Adulthood: However, as individuals age, fluid and crystallized intelligence diverge, with fluid intelligence typically declining more rapidly than crystallized intelligence.

• The Wisdom Paradox: Neuropsychologist Elkhonon Goldberg proposes that the increasing reliance on pattern recognition and effortless problem-solving as individuals age helps explain the paradox of wisdom despite cognitive decline in some areas.

Significance and Criticisms

• Cattell's hierarchical model provides a comprehensive framework for understanding different aspects of intelligence, acknowledging the role of both problem-solving abilities and accumulated knowledge.

• Critics argue that the distinction between fluid and crystallized intelligence may oversimplify the complexity of cognitive functioning and overlook other important factors influencing intelligence.

10.5.1 emotional intelligence

Emotional Intelligence (EI)

• Origins: Proposed by Mayer and colleagues (Mayer et al., 1990; Salovey & Mayer, 1990) and popularized by Daniel Goleman (1995).

• Components: EI consists of four components:

  1. Ability to perceive emotions accurately.

  2. Ability to use emotions to facilitate thought.

  3. Ability to understand emotions.

  4. Ability to manage emotions.

• Concepts: Includes concepts like sympathy and empathy, which are crucial for effective social interactions.

• Assessment: Development of valid measures of EI to assess emotional aptitude.

Debate on EI as Intelligence

• Meta-Analysis: van der Linden et al. (2017) conducted a meta-analysis concluding that EI is more likely a measure of the personality trait "social effectiveness" than a form of intelligence.

• Continued Debate: Whether EI qualifies as a distinct form of intelligence is still debated among scholars.

• Widely Accepted Concept: Despite debates, EI is widely accepted as a means of differentiating "people smarts" from traditional measures of "book smarts."

Significance of EI

• Role in Behavior: Assumptions, emotional intelligence, and cognition play important roles in behavior.

• Study by Damasio: Damasio (1994) studied individuals with damage to emotion centers but intact areas associated with standard measures of intelligence. Found that while they performed normally on IQ tests, they struggled with decision-making when emotions were involved.

• Emotions and Intelligence: Emotions contribute significantly to intelligence by helping individuals focus on relevant information and make effective decisions.

10.5.2 other forms of intelligence

• Sternberg's Triarchic Intelligence

  • Origin: Proposed by Robert Sternberg in 1998.

  • Components:

    1. Analytical Intelligence: Applied to problems found in standard IQ tests, emphasizing abstract reasoning.

    2. Creative Intelligence: Applied to unfamiliar situations where novelty is important, focusing on generating novel ideas and solutions.

    3. Practical Intelligence: Applied to real-world settings, involving the ability to adapt to and solve everyday problems effectively.

  • Successful Intelligence: Involves the appropriate use of all three components to perform well in diverse contexts.

  Significance of Sternberg's Theory

  • Emphasis on Real-Life Problems: Sternberg's theory highlights the importance of addressing real-life problems and novel situations, in addition to standardized testing scenarios.

  • Criticism: Brody (2003a, 2003b) noted strong correlations between all three intelligences, suggesting potential overlap.

  • Criticism: Gottfredson (2003) and Jensen (1993) questioned the distinctiveness of practical intelligence from general intelligence (g).

  • Need for Further Clarification: While Sternberg's theory offers valuable insights, more research is needed to clarify the relationship between creativity, problem-solving abilities, and general intelligence.

  
  10.6 the biology and culture of intelligence

• Genetics vs. Environment in Intelligence

  • Complex Relationship (Date: Ongoing): Intelligence is influenced by both genetic and environmental factors, with their interaction being highly intricate.

  • No "Gene for Intelligence" (Date: Ongoing): Intelligence is likely influenced by multiple genes rather than a single gene, and their expression can be influenced by environmental factors.

  • Dynamic Coupling (Date: Ongoing): Traits, including intelligence, result from the dynamic interplay between genetic activity and environmental conditions. This dynamic coupling emphasizes the complexity of intelligence determination.

  • Heritability of Intelligence (Date: Ongoing): Psychologists study the heritability of intelligence to understand the extent to which genetic factors contribute to individual differences in intelligence.

  • Family Studies (Date: Plomin & Spinath, 2004): Comparative analysis of intelligence levels among biologically related individuals to assess heritability. These studies consistently show that intelligence level is heritable.

  • Twin Studies (Date: Plomin & Spinath, 2004): Comparison of identical twins raised apart to fraternal twins raised together to distinguish genetic and environmental influences. This method provides evidence for genetic factors in intelligence.

  • Caution Needed in Twin Studies (Date: Ongoing): Findings from twin studies need careful interpretation due to potential confounding factors like similar environments, socioeconomic status, and other environmental factors.

  • Nature and Nurture Interaction (Date: Ongoing): Intelligence is a result of both nature (genetics) and nurture (environment), with neither factor acting in isolation. The interaction between genes and environment is crucial in understanding intelligence.

  • Critical Role of Environment (Date: Ongoing): Environmental factors, especially during critical periods of brain development, significantly impact cognitive development and intelligence. Enriched environments support brain development, while sensory-deprived environments can adversely affect it.

• Examples and Processes:

  • Family Studies (Plomin & Spinath, 2004): Comparative analysis of intelligence levels among biologically related individuals to assess heritability.

  • Twin Studies (Plomin & Spinath, 2004): Comparison of identical twins raised apart to fraternal twins raised together to distinguish genetic and environmental influences.

  • Brain Development: The growth and changes in the brain during gestation and early childhood, influenced by environmental stimuli, play a crucial role in intelligence development.

  • Sensory-Deprived Environment: Lack of environmental stimulation adversely affects brain development and intelligence, observed in both humans and animals.