A Look at Positive Labeling and its Impact
on the Educational Trajectories of Students
Gabriela
Monasterio
Northeastern
University Political Science Department
In
education, labels are applied to everyone, whether it is explicit or implied. Children
with learning disabilities (LDs), those with behavioral issues, “average”
students, and the gifted are all labeled, and each of these labels has a
meaning associated with it. Labels tell us how we should act around others, and
our labels change how others treat us. In education, this can be the difference
between success and failure, or between getting accepted or rejected from a
university. In one experiment involving
young children, a randomly selected group was labeled as “spurters,” or those about
to experience an intellectual growth spurt. The students labeled as spurters
showed a greater increase in IQ over the year, despite being randomly selected
(Rosenthal and Jacobson, 1968). This is known as the Pygmalion effect, and this
effect is most pronounced in marginalized groups, including women and
minorities. This inspired the following research, which surveyed the population
of the Northeastern University freshman dorm International Village. The
opposing force to the Pygmalion effect is stereotype threat, where minorities
perform worse on average when reminded of the stereotypes that label them as
inferior or when the “stigmatized identities were activated” (Thompson, 2014). Although these examples deal with education
and positive labeling, the vast majority of the literature does not deal with
positive labeling, and much of it deals with LDs and behavioral disorders.
When
dealing with LDs, the literature is conflicted, as many students have multiple
disorders or mitigating factors, so the additional labeling may push them back
further instead of helping them (Moniqueka and Heraldo, 2012). Several studies
involving labeling video or paper descriptions of students resulted in conflicting
conclusions, with Batzel et al, and Harvey & Pellock concluding that labels
influence the way teachers perceive a student, and Boucher, and Cornett-Ruiz
& Hendricks concluding that labels do not overwhelmingly influence teachers
(Ayers, Krueger and Jones, 2015). A 2013 study looked at the outcomes of the
students diagnosed with LDs, and the real causes behind their outcomes. It was
concluded that the outcomes were a combination of self-stigmatization, their
deficiencies, direct stigmatization, and cumulative disadvantage (Shifrer,
2013).
One
study that did involve positive labels looked at the correlation between a
mother’s praise and her student’s performance in school, but the results were
quite strange. Although the praise increased the child’s perception of their
intelligence, it decreased their likelihood to take on challenges (Pomerantz
and Kempner, 2013). To the average observer, those seem contrary, but Pomerantz
and Kempner concluded that greater perceived intelligence in children was inversely
correlated to effort in those children. In the following research, The goal was
to fill in the gaps that these studies have left; what correlation does
positive labeling have on students once they have exited the K-12 school
system?
Methods
The
Northeastern University dorm was surveyed door-to-door between floors 2 and 9
using a 1-page front and back written survey. The survey was completed between
the hours of 8 and 11:30 on a weeknight. This time was chosen because it was
between normal dinner hours and before quiet hours, so the researcher surmised
that the most students would be in their dorm rooms or common areas between
those hours. The survey was posed as an optional break from studying or way to
procrastinate further on assignments being ignored, and as a way to help a
fellow student. Respondents were asked
about their experiences being labeled, and asked to provide specific details
about the first instance of labeling. They were also asked about their college
applications and acceptances in order to see the effects of the labeling. The
respondents were also asked a panel of questions to measure their self-esteem
(Rosenberg, 1965). For classification purposes, respondents were also asked
their race, ethnicity, age, and the race they are perceived to be by others. The
full battery of questions can be found in figure 3, and the responses can be
found in table 2.
An
attempt was made to sample each floor equally, and all sections of the dorm
were sampled equally other than 5th floor West side, and 9th
floor West side, both with no responses. In total, 57 students were surveyed,
and 4 of those were omitted due to incomplete surveys. All respondents were
freshmen attending Northeastern University, and all respondents were members of
the Honors College.
The
data were inputted by hand and then analyzed using Microsoft Excel.
Hypotheses
1. If
the student was positively labeled before the age of 10 and was not told they
were below average, then the student would be admitted to more colleges and
honors programs compared to those labeled after the age of 10
2. If
the student was negatively labeled, they will have lower self-esteem than those
who were not negatively labeled.
Results
Of
the 53 complete responses, all 53 had been labeled positively, and only 3 had
been labeled negatively in addition to being labeled positively. The mean age
for positive labels was 8.5, the median was 8, and the range was 11. The mean
age for negative labels was 12.6, the median was 14, and the range was 12. Of
the respondents, 66% were White, 17% were Asian, 12% were African American or
African American and White, and 8% were Other or White and Other. One student
requested to be labeled as “Eastern European” and was placed under the “White”
label for ease of analysis. Men comprised 51% of those sampled, women comprised
49%, 96% of respondents were educated in the United States, and 77% attended
public school. Nearly 90% of the respondents participated in AP, 68%
participated in Honors programs, 15% participated in IB, and 6% participated in
other advanced programs (Figure 1). The average respondent was an 18.1year-old
white man who was labeled as above average in intelligence by a teacher at the
age of 8.5. “He” believed his teacher both at the time and now, went to a
public school, participated in 1.7 advanced programs, and has a self-esteem
score of 17/24. He got into 68% of his universities, and was accepted into 76%
of his honors programs.
The
6% (n=3) of respondents who were labeled negatively had higher levels of self-esteem
(17.6/24) compared to the average student (17.3/24). Non-white students were
recognized at earlier ages (7.3) compared to white students (8.8), and those
with learning disabilities were recognized over two years earlier, at age 6.3.
As
seen in table 1, there was no strong or moderate positive correlation between
the data other than what was directly related, such as number of schools
applied to and number of schools admitted to (r=.57), and number of honors
programs applied to and number of honors programs accepted to (r=.72). There
were no strong negative correlations, and a few weak positive correlations
between number of advanced programs that the student participated in and the
number of schools the student was admitted to (r=.34). Other weak positive
correlations included being Hispanic and the number of schools a student was
admitted to (r=.32), and believing a label at the time and continuing to
believe it (r=.33). There was a weak negative correlation between the number of
honors programs applied to and the continuing belief in a label. All other
correlations had an |r|<.3.
Conclusion
The first
hypothesis presented above was supported by the data in figure 4, which show
the difference in percentage acceptance rate by age of labeling. Those who were
labeled at or before age 10 had better outcomes than those who were labeled
later in life. This has interesting implications when applied with the Pygmalion
effect, as that would imply that simply by labeling the child they became smarter
and more high-achieving than their later-blooming counterparts. Yet this is
contrary to the Pomerantz and Kempner study, which linked praise and lower
effort.
The
second hypothesis was not supported by the data, which showed slightly higher
self-esteem in those who were labeled negatively, but this could be due to
sampling error, as the sample size of those labeled negatively was 3, or it
could be attributed to imperfect self-esteem measurement, as the researcher cut
several questions from the self-esteem quiz. This will require more study to be
effectively supported or not supported.
Other
forms of error include the small sample size, 53 out of the dorm capacity of
770; question bias, the informal setting in which the survey was administered,
and human error in inputting and calculating the data. The demographic data
also strayed from the university-wide demographics data from 2015, but that in
itself if flawed, as there is no honors-specific data available other than what
was collected in this research.
This
research can form the building blocks for further studies about labeling of
high-achieving students, and can be drawn from and re-analyzed to form other
conclusions about the population of the Honors College. This research also adds
to the complexity of the effects of labeling in education, and shows the need
for further research in the area.
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Appendix
Table 1.
Table 2.
Figure 1.
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Figure 2.
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Figure 3.
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