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Description
Figure 7.20 Heritability of Intelligence across 11,000 Twin Pairs
To estimate the role of genetic factors, let’s compare people who share a similar
environment but differ in genetic relatedness. Three comparisons are worth noting:
(a) Identical twins who are reared together (in fact, even those reared apart) are more
similar than fraternal twins also reared together; (b) siblings who grow up together are
more similar than unrelated individuals who grow up in the same home (even
biological siblings reared apart show some degree of similarity); and (c) children are
more similar to their biological parents than to adoptive parents. Additional research
ties the genetic knot around IQ even tighter. Longitudinal studies show that the
similarities do not diminish as blood relatives grow older but, rather, get stronger
(Haworth & Plomin, 2011)—and that the similarities exist in verbal, mathematical, and
spatial abilities; school grades; and vocational interests (McCartney, Harris, &
Bernieri, 1990; Plomin, 1988). There is also far more similarity among biological twins
than among “virtual twins”—unrelated siblings of the same age who grew up together
as a result of adoption (Segal, 2000).
However, as Plomin and Deary (2015) put it, “all traits show substantial
environmental influence, in that heritability is not 100% for any trait” (p. 98). This pronurture conclusion is based on comparisons of people who have the same genetic
relatedness but who live in different environments.
Wait. Don’t these results, which suggest a primary influence of heredity, contradict
the finding described at the start of this chapter, that IQ scores all over the world have
risen sharply and consistently since 1920? Human genes cannot change from one
decade to the next, so the increased IQ presumably reflects changes in the
environment—such as better nutrition, more schooling, and advances in technology
that increase access to information.
William Dickens and James Flynn (2001) proposed a theory that helps to
reconcile the apparent discrepancy in the powers of nature and nurture. Dickens and
Flynn argue that genetic dispositions and environments are not independent, as
illustrated in Figure 7.21. According to their theory, children who are brighter than
average at birth will have initial success in school, which will bring praise from
caregivers and teachers, motivate them to work hard, draw them to peers who are
studious, and encourage them to prepare for college, all of which breeds intellectual
success. In contrast, children who are not as bright at birth will have less initial
success, receive less praise, care less about schoolwork, and affiliate with other
weak students, all of which breeds failure. In other words, genes create
environments, which in turn multiply the influence of genes. This theory explains how
identical twins separated at birth can live in different homes but experience similar
environments. It also explains the consistent but puzzling finding that genetic
influences on intelligence seem to increase, not decrease, with age.
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Description
Figure 7.21 How Environments Magnify Genetic Influences
Clearly, environments influence intelligence. So, what environmental factors in
particular are important? The possibilities are numerous: prenatal care, exposure to
alcohol and other toxins, birth complications, malnutrition in the first few months of
life, intellectual stimulation at home, stress, high-quality education, reliable Internet
access, sufficient technology for online learning, and so on. Even the sheer amount of
time spent in school is important (Ceci, 1991; Liu, Lee, & Gershenson, 2020), raising
serious concerns during the coronavirus pandemic. Julie Frazier and Frederick
Morrison (1998) compared kindergarten children at two closely matched schools, one
of which was experimenting with an extended-year program consisting of 210 school
days instead of the usual 180 (in other words, a shortened summer vacation). All the
children were tested in the fall of their kindergarten year, again in the spring, and a
third time in the fall of the first grade. The result: By first grade, children coming off
the extended school year outpaced the others on all measures. Simply put, more time
in school produced better students.
As mentioned previously, parents can also influence intelligence. One example
that has been popular to discuss (The Economist, 2017; Vedantam, 2017) is the
parental expectations in Chinese culture. In Chinese culture, it is believed that
children born during the Dragon year have the highest chances of success
(Goodkind, 1991; Vere, 2008). Therefore, parents strive to have their children during
Dragon years. This belief is of interest to economists like Naci Mocan and Han Yu. In
their research, Mocan and Yu (2017) look at trends in birth rate, financial success,
education, and test scores among Dragon-year children. They have found that
marriage rates increase two years prior to Dragon years and, in turn, that birth rates
increase during Dragon years. With such a boom in childbirth, it could be postulated
that increased demand on resources would have a negative impact on success due
to greater competition (Sim, 2015). However, Mocan and Yu’s initial work has
demonstrated that the Dragon offspring have higher university entrance examination
scores and are more likely to earn a college education than offspring not born during
Dragon years. Does this mean that the cultural belief is actually a fact? Not quite.
For a moment, think about how this cultural belief would influence parents’
behavior toward their Dragon-year children. Mocan and Yu (2017) also thought about
parental expectations and thus looked at parental contributions to, and perceptions
of, their children’s potential. Mocan and Yu found that parents of Dragon-year children
have higher expectations than parents of non-Dragon-year children. They also found
that Dragon children receive more pocket money and are required to do significantly
fewer chores than non-Dragon children. What happens when parental contribution
and perceptions are removed? Mocan and Yu used statistics to mathematically
subtract the impact parents have on Dragon children’s performance to determine if
their scores would decrease. Sure enough, Dragon children’s performance advantage
disappeared. Mocan and Yu’s research suggests that the belief our parents have in
our success and the environments our parents surround us with really can influence
our educational pursuits and performance.
The Racial Gap
One reason the nature versus nurture debate is so filled with emotion is that
certain racial and cultural groups score higher than others on measures of ability and
achievement, and these differences ignite blunt claims concerning genetic superiority
and inferiority. Let’s start with an empirical fact based on nationwide math SAT data
from 2015. Black Americans and Latinx Americans had average math SAT scores of
428 and 457, respectively; and White Americans and Asian Americans had average
scores of 534 and 598, respectively, as illustrated in Figure 7.22.
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Description
Figure 7.22 Mean SAT Scores by Ethnicity Source: Data from National Center for
Education Statistics
Why has this gap occurred? If heredity contributes to variations among
individuals, does it also account for differences found among groups? No, not
necessarily. To be sure, a few psychologists have speculated that differing
evolutionary pressures in Europe, Asia, and Africa have, over time, produced
measurable differences among humans in brain size and intelligence (Rushton &
Ankney, 1996). But as critics of The Bell Curve (Hernnstein & Murray, 1994) were
correct to note, genetic variation among individuals within a group does not mean that
differences among groups are genetically based. Compared to the average Black
American, White Americans grow up in more affluent homes and with better
educational opportunities. Attending and graduating college is one such educational
opportunity that can account for the IQ gap, as illustrated in Figure 7.23.
Description
Figure 7.23 Education: The Great Equalizer
Three sets of research findings support this point. The first is from a study that
asked what would happen to the IQ scores of Black American children adopted into
White American middle-class homes. Sandra Scarr and Richard Weinberg (1976)
studied 99 such cases in Minneapolis and found that the average IQ score was 110—
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well above the Black American average and comparable to that of White American
children from similar families. When the adoptees were retested 10 years later,
similar results were found (Weinberg, Scarr, & Waldman, 1992).
The second set of findings involves cross-cultural comparisons and historical
trends. The cultural perspective reveals that the racial gap in IQ within the United
States is not unique. Low scores in disadvantaged groups are found all over the
world, including the Maori of New Zealand, the “untouchables” in India, non-European
Jews in Israel, and the Burakumin in Japan (Ogbu, 1978). From a historical
perspective, it’s clear that as a result of school desegregation and social programs
such as Head Start, Black Americans have had more educational doors opened in
recent years than in the past. Paralleling these new opportunities, the racial gap is
closing. Dickens and Flynn (2006) determined that Black Americans have gained 4 to
7 IQ points on White Americans across a span of 30 years.
A third, and particularly important, research finding concerns the effect of a
college education on the racial gap in IQ. Joel Myerson and others (1998) examined
data from a longitudinal study that tracked thousands of young men and women from
the ages of 14 to 21. Specifically focusing on Black American and White American
college graduates, these researchers analyzed the scores these students had
received on tests taken after the 8th (pre–high school) through 12th (post–high
school) and “16th” (post–college) grades. If the racial gap in IQ was immutable, as
Herrnstein and Murray suggested in The Bell Curve, then the difference in
standardized test scores would be little affected by a level educational playing field.
Yet it was. Review Figure 7.23, and you’ll notice that although the racial gap
remained through high school, and even widened somewhat, it was substantially
narrowed by the time the students were finished with college. Everyone gained from
the experience, but the Black students gained more—and cut the gap in half.
Math may be an intimidating subject to some, but not to Lenny Ng. Lenny, a son of
Chinese immigrants, scored 800 on the math SAT at age 10. At age 16, he entered
Harvard University. Julian Stanley, who founded the Center for Talented Youth at
Johns Hopkins University, called him “the most brilliant math prodigy I’ve ever met.”
Lenny is now a highly successful mathematician, who is a full professor at Duke
University.
iStock.com/ridvan_celik
Gender Differences
When intelligence tests are constructed, a concerted effort is made to remove
questions that prove more difficult for one sex than for the other—or at least to
balance items favoring one sex with items favoring the other. The result is that total
IQ scores are comparable for females and males. But what about specific abilities? Is
there any truth to traditional gender stereotypes that depict math and spatial relations
as masculine enterprises and language as the art of women? Several years ago,
Eleanor Maccoby and Carol Jacklin (1974) reviewed the research and found that it
supported the stereotype. According to Kurtzleben (2014), among high school
students who take Advanced Placement exams, males outnumber female test-takers
4 to 1 in computer science, more than 2.5 to 1 in physics, and 1.5 to 1 on calculus,
whereas females outnumber male test-takers in languages, English literature, and
related fields.
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Because the issue of gender differences has profound implications for how
parents treat their sons and daughters—and for how teachers treat male and female
students—psychologists have been eager to understand the nature and extent of
these differences. Here is what we know at this point:
Verbal abilities. On verbal aptitude tests, Janet Hyde and Marcia Linn (1988)
analyzed data from millions of students tested between 1947 and 1980 and
found that girls outscored boys but that the gender gap had narrowed. As of
2015, males had higher verbal SAT scores by 4 points but lower writing SAT
scores by 10 points (College Board, 2015). Reed and colleagues (2017)
performed neuroimaging studies on young adults and found that males had
higher verbal working memory performance than females. However, as depicted
in Figure 7.24 (Guiso, Monte, Sapienza, & Zingales, 2008), girls score slightly
higher than boys on tests of reading comprehension and foreign languages
(Hedges & Nowell, 1995; Stumpf & Stanley, 1996).
Mathematical abilities. Girls are better at arithmetic in elementary school,
but boys surpass them in junior high school—a difference that continues past
college except those in more gender-equal cultures (review Figure 7.24; Guiso,
Monte, Sapienza, & Zingales, 2008). According to Mark Perry (2016), males had
a 31-point edge on the math SAT in 2016 (the male and female averages were
527 and 469, respectively). This gap is most evident among the highest-level
math students (Benbow, 1988; Hyde, Fennema, & Lamon, 1990) and on
unconventional problems that require flexible problem-solving strategies
(Gallagher et al., 2000). This difference may underlie the fact that males score
higher on high school achievement tests in physics, chemistry, and computer
science (Stumpf & Stanley, 1996).
Spatial abilities. It has been argued that males outperform females on
spatial tasks such as mentally rotating objects to determine what they look like
from another perspective (as illustrated in the accompanying Try This! activity)
and tracking moving objects in space (Linn & Petersen, 1985; Master, 1998).
Sanchis-Segura and colleagues (2018) argue “that the common statement
‘males have superior mental rotation abilities’ simplifies a much more complex
reality and might promote stereotypes which, in turn, might induce artefactual
performance differences between females and males in such tasks” (p. 1).
Hoffman and colleagues’ (2011) research supports this complex reality. They
wondered if these differences in spatial ability were not simply due to biological
differences and, thus, investigated nurture’s role. Across 1,300 participants who
completed a spatial-ability task, gender differences disappeared when the
participants were divided not just by male or female, but also by their society—
patrilineal or matrilineal. For those raised and living in a matrilineal society,
spatial task performance had no male or female advantage.
Description
Figure 7.24 Math and Reading Gender Gaps Republished with permission of
American Association for the Advancement of Science, from Guiso, Luigi & Monte,
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Ferdinando & Sapienza, Paola & Zingales, Luigi. (2008). Culture, Gender, and Math.
Science 30 May 2008:Vol. 320, Issue 5880, pp. 1164-1165; permission conveyed
through Copyright Clearance Center, Inc.
In games meant to challenge and develop mental rotation skills, players use
spatial intelligence to predict degrees of rotation needed to orient different shapes.
Studies show that as little as 10 hours of experience with these types of games
increases spatial test scores—for girls as well as boys.
iStock.com/akinbostanci
TRY THIS!
Spatial Effects
Rooted in the right hemisphere of the brain, spatial intelligence is one of the seven
multiple intelligences theorized by Howard Gardner. Spatial skills, such as the ability
to visualize objects from a different perspective, are particularly useful in occupations
such as airplane pilot or mechanical engineer.
To challenge your own spatial abilities, TRY THIS: Which of the pairs of geometric
shapes in Figure 7.25 depict the same or different shapes. (Answers are below the
figure.) How did you do? Are you more or less likely to pursue an occupation that
uses spatial skills as a result of this exercise? What tests can you suggest to test
levels of Gardner’s six other multiple intelligences?
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Description
Figure 7.25 Spatial Effects (Answers: a. same; b. same; c. different.)
Education
Ever since Binet’s work in the schools of Paris, many psychologists have had
uneasy feelings about the link between their conceptions of intelligence and
education. There are two principal questions. First, by focusing on the prediction of
academic performance, have we adopted too narrow a conception of intelligence?
Many influential theorists think so. Gardner complains that IQ tests completely ignore
and devalue the musical, bodily-kinesthetic, and personal intelligences. The second
question concerns the impact of IQ testing on the quality of education. Once a child is
identified as a fast, slow, or average learner, what next? Do those with unusually high
or low IQ scores benefit from being identified as “special”? What are the educational
implications? Because schools rely heavily on IQ tests to sort children into academic
categories, it’s important to raise these kinds of critical questions.
The Self-Fulfilling Prophecy
In 1948, sociologist Robert Merton told a story about Cartwright Millingville,
president of the Last National Bank during the Depression. Although the bank was
solvent, a rumor began to spread that it was floundering. Within hours, hundreds of
depositors lined up to withdraw their savings, until there was no money left. The
rumor was false, but the bank eventually failed. Using stories such as this, Merton
proposed that a person’s expectation can actually lead to its own fulfillment—a
phenomenon known as the self-fulfilling prophecy. As we’ll learn, this can influence
the educational process in two ways.
self-fulfilling prophecy. The idea that a person’s expectation can lead to its own
fulfillment (as in the effect of teacher expectations on student performance).
Teacher Expectancies
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Using Merton’s hypothesis, Robert Rosenthal and Lenore Jacobson (1968)
wondered about the possible harmful effects of IQ testing. What happens to the
educational experience of the child who receives a low score? Would it leave a
permanent mark on his or her record, arouse negative expectations on the part of the
teacher, and impair future performance? To examine the possible outcomes,
Rosenthal and Jacobson told teachers in a San Francisco elementary school that
certain pupils were on the verge of an intellectual growth spurt. The results of an IQ
test were cited, but in fact the pupils were randomly selected. Rosenthal and
Jacobson administered real tests eight months later and found that the so-called late
bloomers (but not children assigned to a control group) had actually improved their
scores and were evaluated more favorably by their classroom teachers.
When this study was published, it was greeted with chagrin. If high teacher
expectations can increase student performance, can low expectations have the
opposite effect? Could it be that children who get high scores are destined for
success, whereas those who get low scores are doomed to failure, in part because
educators hold different expectations of them? To this day, many researchers have
been critical of the study and skeptical about the generality of the results (Spitz,
1999). But the phenomenon is potentially too important to be swept under the
proverbial rug. After reviewing other tests of the hypothesis, Rosenthal (1985)
concluded that teacher expectations significantly predicted student performance 36
percent of the time. Mercifully, the predictive value of teacher expectancies seems to
wear off, not accumulate, as children advance from one grade to the next (Smith,
Thompson, Raczynski, & Hilner, 1999).
Teacher expectations can affect student performance.
iStock.com/Marco VDM
How might teacher expectations be transformed into reality? There are two points
of view. According to Rosenthal, the self-fulfilling prophecy can be viewed as a threestep process. First, the teacher forms an impression of the student early in the school
year. This impression may be based on IQ-test scores or other information. Second,
the teacher behaves in ways that are consistent with that first impression. If the
expectations are high rather than low, the teacher gives the student more praise,
attention, and challenging homework. Third, the student unwittingly adjusts their own
behavior according to the teacher’s actions. If the signals are positive, the student
may become energized. If negative, they may lose interest and self-confidence. As
depicted in Figure 7.26, the cycle is thus complete and the teacher’s expectations
confirmed. Importantly, self-fulfilling prophecies like this are at work in many settings
—not only in schools but in a range of organizational settings, including the military
(McNatt, 2000).
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Description
Figure 7.26 Three-Step Model of a Self-Fulfilling Prophecy
Stereotype Threat
There’s a second way in which expectations can set in motion a self-fulfilling
prophecy, which is known as stereotype threat. According to Claude Steele (1997),
African Americans are painfully aware of the negative stereotypes people hold
regarding their intelligence. As a result, scholastic test situations make African
American students feel threatened by the stereotype and anxious about performance.
To make matters worse, notes Steele, this threat can eventually become chronic,
causing African American students to tune out and “disidentify” from academic
pursuits.
stereotype threat. The tendency for positive and negative performance
stereotypes about a group to influence its members when they are tested in the
stereotyped domain.
Steele and Aronson (1995) administered a 30-item verbal test to African American
and White college students. Half the subjects were told that the items were merely a
device that psychologists use to study the way people solve problems—a
“nondiagnostic” instruction that was given to underplay the testlike nature of the task.
The other half were told that the same items measured verbal-reasoning ability—a
“diagnostic” instruction designed to make stereotype-threatened subjects anxious. As
shown in Figure 7.27, African American and White subjects did not differ much when
given the low-key nondiagnostic instruction (their scores were statistically adjusted
according to each subject’s past verbal SAT score in order to equalize initial
differences in their abilities). In the diagnostic condition, however, the African
American subjects exhibited a decrease in their own performance. With the task
defined as an ability test, those feeling vulnerable to the stereotype, sadly, helped to
confirm it. How can this happen?
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Description
Figure 7.27 Stereotype Threat Effect on Test Performance Source: Adapted from
Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test
performance of African Americans. Journal of Personality and Social Psychology,
69(5), 797–811.
One possibility is suggested by a psychophysiological study showing that African
Americans in the “diagnostic” condition exhibit an increase in blood pressure during
and after the test (Blascovich, Spencer, Quinn, & Steele, 2001). However, as
previously mentioned, and apparent in Figure 7.27, scores were adjusted based on
verbal SAT scores. Therefore, many researchers argue that the scores do not truly
depict the real average test scores for subjects (Jussim, Crawford, Anglin, Stevens, &
Duarte, 2016; Sackett, Hardison, & Cullen, 2004). Knowing what you know now about
SAT score differences and race, do you think that adjusting test scores was
necessary, and as a result, more reflective of African American and White test
performance? Flore and Wicherts (2015) were interested in uncovering whether
stereotype threat research demonstrated actual female performance changes across
stereotyped domains. They conducted a review of stereotype threat research with
female adolescents and children. They found that, across several studies, stereotype
threat among school-aged girls was not evident. Why did stereotype threat
disappear? Amy Wax (2009) believes that stereotype threat might exist but only for a
select set of people in unique settings.
Other research indicates that stereotype threat effects do exist, are general, and
can interfere with other groups and other domains of ability. Imagine the following
scenario: You walk into class and your teacher tells you that a new genetic
researcher has discovered a marker for intelligence, and that marker demonstrates
itself via eye color—the darker the eyes, the greater the intelligence. You sit there,
stunned, and look around the room at others like you who have light eyes. You think,
How is this possible? This science has to be flawed! But you keep your mouth shut,
and snap out of your disbelief as your teacher, Dr. Elliott, announces she is going to
demonstrate the validity of the science in the classroom today with the use of collars.
The light-eyed students—including you—walk up, grab a collar, and fasten the button
to hold it in place. Already you feel singled-out. The dark-eyed students, by contrast,
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