Introduction to Intelligence Testing
Early Intelligence Tests and Concepts:
Alfred Binet: Designed the first intelligence test for children.
Focused on mental age to determine if children were developing on pace or slowly.
Primarily concerned with children developing slowly, aiming for early intervention.
Mental age compared a child's problem-solving abilities to other children their same chronological age.
Binet believed intelligence was not permanent, viewing his test as a "snapshot in time."
Lewis Terman: Revised Binet's test.
Developed the Stanford-Binet Intelligence Test, which was widely used for a long time.
Introduced the term IQ (Intelligent Quotient), which is still in use today.
Terman believed intelligence could be measured across multiple domains, not just a single factor.
His idea was to assign a numerical score after the test.
Early Applications and Biases of Intelligence Tests:
World War I: The U.S. Army needed to group recruits based on learning skills.
Stanford helped by adapting the Stanford-Binet test into two versions:
Army Alpha: A written test.
Army Beta: An oral test for soldiers who could not read or write.
While it worked reasonably well and measured perceived intelligence, it was not perfect.
Immigrant Testing (Ellis Island, 1917):
Immigrants were tested in English, a language many did not speak.
Tests included cultural biases, such as a picture of children burying a rabbit.
American interpretation: Burying a pet, sad.
Immigrant interpretation (from countries with food scarcity): Preparing for supper, digging a hole for a fire to cook the rabbit.
These answers were marked incorrect, despite being logical based on the immigrants' experiences.
This highlights significant bias in testing due to differences in thought processes and backgrounds.
Historical Bias and Misinterpretation:
An expert, influenced by these biased test results, claimed that 80\% of Hungarians, 79\% of Italians, and 87\% of Russians were "feeble-minded." This was a direct result of their poor performance on culturally biased tests, not actual intellectual deficit.
Modern Intelligence Tests:
Wechsler Tests: Currently used, revised multiple times.
WAIS (Wechsler Adult Intelligence Scale): For adults (currently on the Fourth Edition).
WISC (Wechsler Intelligence Scale for Children): For younger children.
These tests are designed for specific age groups and focus on age-appropriate learning and decision-making (e.g., WISC focuses on experiential learning, memory, rather than questions about owning a house).
Types of Psychological Tests:
Achievement Tests: Measure what you have already learned or your knowledge in a specific area.
Example: Most academic tests taken in school.
Aptitude Tests: Assess your potential or ability to learn a new skill or subject, without requiring prior knowledge.
Example: ASVAB (Armed Services Vocational Aptitude Battery), used by the military to assign roles based on aptitude (e.g., mechanics, computer skills).
Key Principles of Good Test Design:
Standardization:
The test can be generalized across populations.
Enough people have been tested (normed) for scores to be reliably compared.
Ensures everyone has the same opportunity to score well.
Examples: ACTs, SATs, GREs.
Reliability:
The test measures the same thing consistently every time.
Multiple versions of the same test should yield roughly the same score for an individual.
Example: Taking five different versions of the ACT should result in similar scores.
Validity:
The test measures what it claims to measure.
A test can be reliable but not valid (e.g., a math test given in a psychology class might reliably measure math skills but is not valid for a psychology course).
A test cannot be valid unless it is also reliable; it must consistently measure what it's supposed to measure.
IQ Distribution and Interpretation:
Normal Distribution: IQ scores typically follow a bell curve.
Standard Deviation: For IQ, it is 15 points.
Average Score: 100.
Classifications of Intelligence:
Scores between 90 and 110 are considered within the normal range.
A score of 125 is one full standard deviation above normal, indicating significantly higher abilities.
IQ Calculation Example: If a 10-year-old (chronological age) scores like a 13-year-old (mental age), their IQ is \frac{\text{Mental Age}}{\text{Chronological Age}} \times 100 = \frac{13}{10} \times 100 = 130.
Stability over Time: IQ scores generally remain stable over a person's life, with some minor variations.
Population Distribution:
Approximately 68\% of people score between 85 and 115 (within one standard deviation of the mean).
Approximately 95\% of people score between 70 and 130 (within two standard deviations of the mean).
The remaining 5\% are outliers at the extremes.
Theories of Intelligence:
Charles Spearman (Two-Factor Theory):
First person to describe intelligence as a g factor (general intelligence), a basic overall intellectual ability.
Did not significantly advance the idea beyond this general concept.
Howard Gardner (Theory of Multiple Intelligences):
Believed there are multiple, distinct intelligences, not just a single g factor.
Proposed at least eight intelligences for a comprehensive understanding of IQ, including:
Bodily-kinesthetic intelligence (e.g., athletes).
Musical intelligence.
Art (e.g., artistic ability).
Argued that any area where one shows strong aptitude should be considered an intelligence.
Received some support but also criticism due to the difficulty in objectively measuring many of these intelligences.
Robert Sternberg (Triarchic Theory of Intelligence):
Proposed three interdependent areas of intelligence:
Analytic Intelligence: Problem-solving, general learning, extracting information, creating plans (e.g., traditional IQ test questions).
Creative Intelligence: Dealing with novel situations, thinking outside the box, applying existing knowledge in new ways to solve new problems.
Practical Intelligence: "Street smarts," navigating real-world situations, common sense, adapting to practical demands (e.g., navigating a new city safely).
Integrating Theories: Some researchers aim to combine these ideas to better link how intelligence is understood with how it is applied and measured in the real world, though this is still a work in progress.
Extremes of Intelligence:
Intellectual Disability: Diagnosed when an IQ score is 70 or below (two standard deviations below average).
Individuals typically require some level of support to navigate the world independently.
High Intelligence: Charles Terman's study (1921)
Followed 1,500 children with IQs above 140 throughout their lives.
Found that as adults, their income tended to be higher than average.
However, not all were successful; success was more strongly predicted by personality traits such as perseverance, self-confidence, and a positive response to failure, rather than IQ alone.
Nature vs. Nurture in IQ:
Genetics: Plays a role in determining a general range of IQ, not a specific score.
Children of intelligent parents are likely to have higher IQs due to genetic predisposition.
Environment (Epigenetics): Significantly influences the expression of genetic potential.
Positive Environmental Factors: Exposure to books and language early in life, educational opportunities (camps, gifted programs) can lead to higher IQ expression.
Negative Environmental Factors: Lack of intellectual stimulation (e.g., limited conversation, no books, discouragement of education) can result in lower IQ expression.
Twin Studies (Correlational): Provide insight into genetic and environmental influences.
Identical twins raised in the same environment: Share identical DNA and environment, showing the most similar IQ scores (correlation of about 0.86).
Identical twins raised separately: Still show a high correlation (about 0.76), indicating a strong genetic component to IQ, even when environments differ.
It is crucial to remember these are correlational studies, not causation; IQ differences have both genetic and environmental components.
Diversity and Bias in Test Creation:
Historically, IQ tests were often created by a narrow demographic (e.g., white, middle-aged men).
This lack of diversity leads to cultural bias (reiterating the immigrant testing example and introducing new ones).
Example: "Scissors" vs. "Shears": A test might count "shears" as incorrect for a picture of scissors, unaware that "shears" is a common Southern term, thereby unfairly lowering scores for individuals from that region.
To accurately assess everyone, test creators need a variety of backgrounds and perspectives (diverse ages, cultures, regions) to anticipate and account for different valid responses and cultural understandings.
Stereotype Threat:
The phenomenon where individuals, aware of a negative stereotype about their group, perform poorly on tests that highlight that stereotype.
Example: Women and Math Tests (1990s research):
Women scored lower on math tests when tested in a room full of men, especially when aware of the stereotype that women are not good at math.
The same women scored significantly higher when tested with other women and informed that the test was designed for "how women learn math." This removed the stereotype threat.
Mechanism: Stereotype threat causes physiological arousal (e.g., accelerated heart rate), diverting cognitive resources away from the task and leading to poorer performance.
Cultural IQ Differences (Extended Example):
Burakumi of Japan: A group within Japan that is not racially or genetically different from other Japanese citizens, yet has faced significant societal discrimination and prejudice.
Despite similar genetics, Burakumi individuals score 10 to 15 points lower on IQ tests compared to other Japanese citizens.
This demonstrates that societal discrimination and prejudice, rather than genetic factors, can significantly impact measured IQ scores.
The Flynn Effect:
Observation that IQ scores in developed nations have increased over the last four generations.
Each successive generation scores slightly higher than previous ones.
Hypothesized Reasons: Increased educational access, better nutrition, more stimulating environments, and generational building upon previous knowledge.
Future Outlook: Developmentalists suggest a potential shift or regression in the Flynn effect due to factors like increased screen time and reliance on technology, which could impact learning styles and cognitive abilities. This remains a subject of ongoing research and prediction.