Gender Bias and Different Intellectual Abilities Between Men and Women

Gender Bias and Different Intellectual Abilities Between Men and Women

The problem we decided to investigate for our Field Project was the differences
found among males and females within their intellectual abilities. The main concentration
of our problem dealt with gender and the strengths and weaknesses found within oneís
brain. Our hypothesis focuses more on societal factors, rather than biological, because we
felt these were more fit to be tested through experimental design. We feel, because of
different developmental functions of the brain between genders, it makes our society
biased and effects many aspects of our daily life. We are going to test gender bias through
two generations in order to see how our society has changed over the years. We plan to
interpret the data we collect from our experiments by relating the results to our
hypothesis. We are hoping our experiments give us clear results that will help us draw
accurate conclusions concerning the connection between our society and gender biases.
The reason we chose this topic to further research is because we are both
education majors. From our education courses, we have briefly discussed how males and
females learn differently in the classroom. We have also heard how males tend to excel in
particular subject areas that differ from those in which women are strong. We were both
curious about these statements concerning gender in our schools and decided it would be
interesting, as well as beneficial, to investigate the differences found among intellectual
abilities and gender. We wanted to test the reliability and accuracy of these statements
and find whether or not society plays a factor in creating these differences. As future
teachers, we hope to use the information gathered from this project for the betterment of
our classrooms and the students learning within them.

It is clear that there are many ways in which men and women are different.
Psychological, biological and social factors are all involved in maintaining these
differences. However, we feel that biological factors are extremely important to
understand in order to realize how stereotypes develop and stay within an individual and
within a society. There are a couple of theories that give some explanation of the effect of
biological reasons for gender different intellectual abilities. They are the
cognitive-crowding hypothesis, the sex hormone hypothesis, and the bent-twig hypothesis.
According to the cognitive-crowding hypothesis, most males have verbal abilities
lateralized in the left hemisphere and visual-spatial abilities lateralized in the right
hemisphere, but neural space devoted to verbal abilities is found in both hemispheres. If
this theory is correct, it is possible that females excel in verbal abilities because they have
more neural area devoted to these abilities, and visual-spatial abilities suffer for females
because visual-spatial get crowded out by having to share space with verbal abilities. As
you will see later, we test this hypothesis through a survey given to college students, both
male and female.
Not only does lateralization play a role in different intellectual abilities in men and
women, but prenatal hormones are also involved in brain development. Research has
shown that these sex hormones play an important role in intellectual abilities at puberty.
There is little difference between the skills of boys and girls in math or science at a young
age in school. However, studies show that once boys hit puberty, the testosterone greatly
increases their ability to exhibit visual-spatial skills and thus, generally, increasing the gap
between men and women in math and science abilities in school. In high school, girls
generally receive less encouragement to excel in mathematics is a male-stereotyped
intellectual subject and females report that mathematics is not as important for their career
goals as it is for males. Gender bias is easily developed through these kinds of attitudes,
however, now that more and more women are competing with men in the same career
positions, it is necessary to later examine how attitudes have changed about gender roles.
The final hypothesis, the bent-twig hypothesis, comes from an old adage that states
that as the twig is bent, so the tree shall grow. According to this hypothesis, people adjust
and select their life experiences so that they are in accord with their natural propensities
and strengths. For example, if males are somewhat better as visual-spatial tasks for
biological reasons, they are more likely to seek activities that are spatial in nature, and the
gender difference will become even larger than it initially was. Similarly, if females are, on
the average, better at reading, then they will read more often and further develop their
reading skills relative to males. Therefore, biological reasons affect social actions which in
turn lead to social beliefs and stereotypes. Biological reasons clearly play an important
role in different intellectual abilities between men and women. As you can see, different
abilities easily lead to stereotypes and a world that is gender biased.
A womanís role in society has changed dramatically. The Womenís Movement
began in the middle of the twentieth century and continues into the twenty-first century.
Women began to speak out against the stereotypes that were labeled on them and began
to demand more equal opportunities. By the 1980s, women were no longer expected to
become a homemaker and care for their husbandís and childrenís needs, but were rather
expected to start a career before settling down to start a family. However, now that
women are encouraged to hold the same positions as men, is gender bias in our world
decreasing? Biological reasons might be able to separate men and women in intellectual
abilities and cause certain social actions to develop stereotypes, thus producing gender
bias people, but could new attitudes about women overcome the biological differences and
cause gender bias in society to decrease. We wanted to test males and females from our
generation and the generation before us to see if there is any significant difference in the
level of gender bias.
Through this mini-experiment, we may be able to actually see the effects of a social
movement. Although we are testing the effects of the Womenís Movement, in particular,
we will also gain knowledge of how new attitudes and beliefs can change stereotypes and
give a society a new perspective, which in this case, could decrease gender bias over a
short period of two generations.
In order to test our hypothesis, we conducted two main experiments. We wanted
to first see if there was any association between males and right-brained activities and
females and left-brained activities. We did this test through a survey of forty people,
twenty from each sex. There were ten multiple choice questions which distinguished each
person as possessing either left-or right-brain characteristics. Each person who took the
survey and had a choice between a or b. A -represented a left-brained characteristic while
b-represented a right-brain characteristic. We separated those who got more than six
right-brain characteristics from those who got more than six left-brain characteristics.
Then we counted how many males were in the right-brain pile compared to female and
vice versa. The class participated in this survey first in order to give us an idea if the
results of the survey were comparable to our hypothesis so that we could give it out to
more people to get more thorough results. It actually did give us those results, therefore,
we included the survey in our experiment and distributed them to more students around
campus. We chose only students because they were easily accessible and we were only
wanted to test different brain skills of females and males, therefore, it was not necessary
that we include other ages. However, in our next experiment it will be necessary to
include specific ages.
In our second experiment we wanted to test our hypothesis on gender bias
between generations. There are obviously social stereotypes between men and women in
our society, however we wanted to give a test that could measure the level of oneís
stereotypical tendencies. We tested people over the age of thirty and under the age of
thirty, in order to see if there was a difference in gender bias between generations. The
test was located on the Internet and was called The Implicit Association Test, therefore,
people taking the test needed to be able to use a computer. It was very easily accessible,
all we had to do was give out the address and our participants could give us their results.
This test took about five minutes, however the computer timed the reaction time on each
person who took the test. It was important that our participants went as fast as they could
in order to get accurate results, however, we actually had some participants who received
inconclusive results because they did not go fast enough. We included a sample page from
the test on the Internet and highlighted in blue the actual result of the person taking the
test. The test scored each person in seven possible outcomes in percentages- 1-Strong
automatic association between male and science-2- Moderate automatic association
between male and science-3-Slight automatic association between male and
science-4-Little or no automatic association gender association with science or liberal
arts-5-Slight automatic association between female and science-6-Moderate automatic
association between female and science-7-Strong automatic association between female
and science.

Time Line:
February 14- 18th: We began brainstorming and researching different topics for
our subject.
February 21-25th: More researching on specific topic of different intellectual
abilities
March 6-10th: Creation of poster and first survey
March 21st: Presentation of Poster, more feedback from class- Chris gave us new
material to work with- Internet gender bias website.
March 27-April 15: Distributed experiments..
April 24-28: Constructed data and tables and graphs. Expanded on proposal and
completed writing.
From our surveys, we decided to display our results in two separate types of
graphs. The results of our left-versus right-brained connection with gender survey are
exhibited in a bar graph. We chose a bar graph because we felt this would be the best
method in comparing our findings. A bar graph was a clear, simple and efficient way to
compare the results of this particular survey.
The second graph we chose to use was a pie graph. We decided to create two pie
graphs to show the results of the online Implicit Association Tests that we conducted.
The reason we chose pie graphs was because it gives us a complete breakdown of the
different result categories and their percentages. Having our results presented in this way
allowed us to interpret our data and draw conclusions from our results concerning our
surveys.
In calculating the p-value for our data, we used the statistics program SPSS. We
ran individual T-tests on the results from our Implicit Association Tests. The T-tests gave
us a value for t, as well as for the degrees of freedom. Using these two values, we were
able to calculate a value for p for each set of data. P represents the probability that the
differences we observed can be explained by chance alone. For the people under the age
of thirty, we calculated a p-value equal to 0.012. Our p-value for the people over the age
of thirty who were surveyed is equal to 0.020. In comparison to 0.05, we see that both of
these p-values are smaller. Therefore, we can conclude that the results from both of these
generationsí surveys are significant.
The Implicit Association Tests were used in our research to explore the connection
between gender bias over two separate generations. We decided to split the generations
up into two groups: people over the age of thirty and people under the age of thirty. After
interpreting the results of these two separate groups, we found that there was not an
obvious distinction between the two generations and their ideas concerning gender roles in
our society. There was a slight overall increase in the amount of people who had a strong
association between males and science for the generation of people over the age of thirty.
This was not a significant enough difference of which to draw conclusions. Overall, we
found the two generations to have extremely close results, which was surprising to us.
However, one note to make in describing this survey is the results that were obtained from
people over the age of sixty. We surveyed five people over the age of sixty, and all five of
their results stated that they had a strong automatic association between males and
science. Because of this, we thought it would have been interesting, if we were to do this
again, to compare the results of people over the age of sixty to those under the age of
thirty. We think that the results would be more distinguishable between these generations
than between the two that we actually surveyed.
Another key observation that we noticed was that in the surveys we conducted, we
did not have anyone fall into the category of ìStrong automatic association between
females and science.î We found this to be rather interesting. Why is it that not one
person that we surveyed fit into this category?
The inconclusive category on our pie graphs represents the results of people who
did not perform the test correctly. Most likely, these people did not answer the questions
quickly enough. As stated earlier, the computer had a time limit for each person on each
question, and could not give results for those who took too long in answering. This
explains why it is an automatic association test, the results are accurate because they do
not allow people to think about their answers.
The results from the survey we conducted on the association between gender and
left-versus right-brained dominance supported the hypothesis that women are generally
more left-brained, whereas men are generally more right-brained. However, the results
from this survey were not overwhelming. We feel this is survey supports our hypothesis in
the fact that the majority of the males had more right-brained skills compared to females.
However, there are many women that are in fact more right-brained and males that are
more left-brained and our survey shows this through the close statistics that we observed
in our graph.
In closing, we would like to mention how this research will be beneficial in the
learning that takes place within our future classrooms. We feel this project has allowed us
to see that although the majority of males that we surveyed were right-brained and the
majority of females were left-brained, there was still a large percentage of both males and
females whose brain dominance did not support this theory. It is important for us to
realize that this is a generalization mainly because each individual has his/her own unique
learning abilities. Our conclusions told us that there are definitely certain patterns among
gender and brain dominance, however, our results did not overwhelmingly outline these
patterns for us. As future educators, we plan to incorporate the idea that everyone learns
differently and everyone has his/her own strengths and weaknesses, despite his/her gender.
In summary, we have found that we need to teach to each child as a student, not as a
ìmale studentî or ìfemale student.î

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