Quantitative Educational Aspirations

Running head: EDUCATIONAL ASPIRATIONS AND OUTCOMES 1
Educational Aspirations and outcomes of Students based on the Education Longitudinal Study of
2002
Natalie Ortega & Erin Parra
School of Education
University of Redlands
EDUC 603
July 2015

EDUCATIONAL ASPIRATIONS AND OUTCOMES 2
Educational Aspirations and outcomes of Students based on the Education Longitudinal Study of
2002
“A large number of factors including variables and sociological, psychological, cultural
and financial factors affect participation in post-secondary education. (Bell & Anisef, 2005).”
Researchers have measured a combination of different things that affect a student’s pathway to
college. A longitudinal study was conducted to measure the relations of parenting style and its
effect on students and their educational developing aspirations. Results supported that parenting
practices in middle schools have an effect on academic successes in high school and college
enrollment (Hill, N. E., & Wang, M. T., 2015).
Along with these results, another study was conducted measuring the importance of the
effect of cultural factors and career aspirations. Booth, C. S., & Myers, J. E. (2011), compared
career aspirations in African-American women and Caucasian women and to determine if
multiple role plans would predict career aspirations to any extent. These three universities
consisted of a historically African-American university, a predominantly Caucasian university
and public university for undergraduate women. The results supported that career motivation was
related to multiple role planning and career motivation differed based on cultural background.
The most significant finding of this study was African American women had a higher
commitment and were more motivated to advance in career roles, as well as choosing a career
that served others. Also, African American women had higher knowledge and commitment to
multiple role lifestyles. Overall, multiple role planning did not predict career aspiration.
In relation to our study, a study by Signer and Saldana (2001) measured the different
aspects that affect the educational aspirations of students. The research question was to
determine if relationships between high school students’ aspirations and their parents’ education

differed by their mothers’ and fathers’ education. This qualitative study used 100 secondary
students, 50 African-American and 60 Caucasian. They were either low-SES or high-SES and
from urban and suburban communities. Several factors were taken into consideration for this
study, including mathematics achievement levels, ethnicity, gender and socioeconomic status. A
chi-square analysis was performed on the data between the student variables and parents’
education. In this study, Signer and Saldana (2001) found that there was a significant interaction
between mathematics achievement and the student’s ethnicity with educational aspirations. One
criticism of this study was the population sample that was used. It would have been ideal to have
a more diverse sample, rather than only African-Americans and Caucasians. Cultural differences
and parents’ education and occupations seem as though they would be one-sided with Caucasian
families having high-SES and the African-American families having low-SES. This study is
important because it shows that there are student variables that can be accounted for when
measuring students’ educational aspirations. If educational aspirations are being affected by
variables like mathematics level, then we can consider this when comparing other data related to
students’ aspirations.
Qian and Blair (1999) used the second follow up National Education Longitudinal study
(1992) to explore how different factors affect educational aspirations across racial groups. The
analyses were limited to high school seniors. Their research proposal was that several factors
affect high school seniors’ educational aspirations including individual, family, and school
characteristics. A standard T-test was performed on the data and they found that social and
financial capital had different effects across cultures. Asian-Americans were more affected by
human capital and having English as a Native language; whereas, parental involvement had a
stronger impact on minority students such as African-Americans or Hispanics. This study was

relevant because it may be used to identify differences in the students’ educational aspirations
and which factors in their lives played a role. This sample was useful because it contained
relevant data on several races.
A study by Shapka and Domene (2012) focused more on gender differences, whereas the
other studies focused on cultural differences and socioeconomic status. Participants in grades 9-
13 were pulled from an ongoing longitudinal study in Ontario, Canada. The research proposal
was that there would be a difference in students' educational aspirations between genders. This
qualitative study used questionnaires to measure the students' educational aspirations.
Hierarchical linear modeling techniques were used to determine the growth curves of levels of
educational aspiration over time. Shapka and Domene (2012) found significant results for
genders; Boys had lower aspirations in early high school that rapidly accelerated to having
higher aspirations than girls by late high school. Although, post-high school, both genders had
equally dropped off in aspirations to the point of equivalence across genders. Shapka and
Domene (2012) also found that experiencing barriers to attaining education significantly
influenced students’ aspirations. This study shows even more student variables that affect
students' educational aspirations, which should be taken into consideration while analyzing our
data.
The purpose of this experiment was to determine which factors were a good predictor of
degree attainment. It was predicted that students who reported in the educational longitudinal
study of 2002, who planned to go to college, would actually attend a post-secondary institution
and obtains some type of post-secondary educational degree. This means, that our results would
show a significant difference in degree attainment between students who planned to college and
students who did not plan to go to college.

Methods
Participants
NCES collected data from 16,197 participants who participated in the Education
Longitudinal Study of 2002 (ELS:2002). These participants were10th graders in 2002 and 12th
graders in 2004. Students were followed throughout secondary and postsecondary years. ELS
Data was collected in waves. The base year of collecting data was 2002. The first-follow up year
was in 2004, the second follow up year was in 2006 and the third follow up year was in 2012. In
this research we viewed the first follow up that was given in 2004. The students that participated
in the first follow up were seniors. The third follow up survey (2012) was also used to collect
data.
Procedure
In follow up one of the NCES longitudinal study questions 42, 45 and 47 were
reviewed. Question 42 asked participants, “As things stand now, how far in school do you think
you will get?” The possible answers were; less than high school(1),GED (2), High school
graduation only(3) , attend or complete a 1-or 2- year program in a community college or
vocational school (4), College 4 year incomplete (5) attend college, but not complete a 4- or 5-
year degree(6), graduate from college (4-to-5-year degree) (7), obtain a Ph.D., M.D., or other
advanced degree or equivalent (8), don’t know(9). Question 45 asked participants, “Do you plan
on going to school right after high school?” The possible responses were; Yes (1), No (2), don’t
know (3). Question 47 asked participants, “Do you plan to continue your education at some time
in the future?” There were five possible responses; no(1), yes right after high school(2), yes, after
staying out of school for up to one year (3)yes, after staying out of school for over a year (4),
don’t know(5).
Design

All data was recoded to get rid of missing variables. The new variables were used in a
Chi-square to determine if there was a significant relationship between student’s educational
aspirations and their educational outcome. The independent variable is the student educational
aspirations, specifically how far the student anticipated they would get in their education. There
were nine levels within this variable; less than high school(1),GED (2), High school graduation
only(3) , attend or complete a 1-or 2- year program in a community college or vocational school
(4), College 4 year incomplete (5) attend college, but not complete a 4- or 5-year degree(6),
graduate from college (4-to-5-year degree) (7), obtain a Ph.D., M.D., or other advanced degree
or equivalent (8), don’t know(9).The Dependent variable measured the student educational
outcomes, specifically if a student obtained any type of degree at a post-secondary institution.
The possible outcomes that measure attainment are; yes (1) or no (2).
Results
In the hypothesis, it was expected that there would be a significant difference in the
educational outcome of students who reported in the educational longitudinal study of 2002, who
planned to go to a post-secondary institution were more likely to go to college, than students who
students had no post-secondary plans. There were three combinations of questions from follow-
up one and follow-up three.
The first independent variable analyzed was educational aspirations, with nine levels. The
question stated, “As things stand from now, how far do you think you will get?”. The levels
consisted of responses numbered one through nine. Response one represented the aspiration to
complete less than high school, response two was to complete a G.E.D, response three was to
complete high school only, response four was to complete a two-year degree, response five was
to attend but incomplete a four-year degree, response six was graduate from a four-year

university, response seven was to obtain a Master’s degree, response eight was to obtain a Ph.D.
or M.D., and response nine was, “I don’t know”. The dependent variable was the attainment of a
post-secondary degree, with two levels that were attained from the third follow-up questionnaire
of 2012. The question stated, “Earned a credential from last-attended post-secondary school?”.
Response ‘0’ represented no degree attained, and the response ‘1’ represented that there was a
degree attained. A chi-square test was ran with these variables, which showed P<.001, so we
reject the null hypothesis. There was a strong and significant difference between students who
aspired to graduate from college and those who did not aspire to graduate. The odds ratio was
computed, showing that students who aspired to graduate from college were 2.13 times more
likely to obtain any credential than those who thought they did not know how far they would go
in school or did not aspire to obtain a degree. People who aspire to obtain a degree will most
likely obtain any type of degree more than those who do not know what they aspire to attain or
do not aspire to attain a degree. Having higher educational aspirations were a good predictor of
future degree attainment. Refer to table 1, 2, and 3.
Second, the independent variable of plans on when to attend a post-secondary institution
was analyzed. The question stated, “Do you plan on going to school right after high school?”.
This variable consisted of three levels, response ‘1’ represented yes, response ‘2’ represented no,
and response ‘3’ represented “I don’t know”. The dependent variable of degree attainment
consisted of two levels again, ‘0’ representing no degree attained while ‘1’ represented a degree
was attained. The chi-square analysis showed, P<.001, therefore, the null was rejected. There
was a strong and significant difference between students who planned on going to school right
after high school were the most likely to obtain a post-secondary degree. When the same
questions were compared using odds ratio, results showed, students who planned on attending

school right after high school were more than 3 times likely to obtain a post-secondary degree.
Specifically, when students had plans to attend a post-secondary institution immediately after
school was a good predictor of future degree attainment. Refer to figure 4, 5, and 6.
Finally, the independent variable of when students’ planned to continue post-secondary
education was analyzed. The levels consisted of not continuing after high school, continuing
right after high school, continuing up to one year after high school, and continuing over one year
after high school. The question stated, “Do you plan on continuing your education sometime in
the future?” The dependent variable was again degree attainment, with responses being no
degree attained and a degree attained. The chi-square test showed a significance of P<.001.
Therefore, the null was rejected. This means that there was a strong and significant difference
between students who planned to attend right after school and those who planned to attend at
later dates or not at all. Those who planned to attend right after high school were most likely to
obtain a post-secondary degree. The odds ratio was computed and revealed that students who
planned to attend right after high school were 2.79 times more likely to obtain a degree than
those who planned to wait up to one year after high school to attend. Refer to figure 7, 8 and 9.
Discussion
The purpose of this study was to determine if educational aspirations were good
predictors of higher educational outcomes. A limitation of this experiment was the survey that
was used was limited to only high school seniors of 2002, which may contribute to a cohort
effect. This is only one student population that has been measured. Overall, the results were very
strong and what was expected. Other considerations that resulted from this experiment are to
consider the factors contributing to students not being aware of the urgency to pursue higher
education after high school. With these results, educators can promote awareness to students.

Educational leaders can also promote the immediate enrollment at post-secondary institutions,
after high school.

References
American Psychological Association.(2002). Ethical principles of psychologists and code of
conduct.American Psychologist, 57, 1060-1073.
Bell, Stephen., & Anisef, Paul. (2005). Accessibility and student debt: The shift from public to
private support in Canada. Preparing for post-secondary education: New roles for
governments and families, 55-86.
Booth, C. S., & Myers, J. E. (2011). Differences in career and life planning between African
American and Caucasian undergraduate women. Journal Of Multicultural Counseling
And Development, 39(1), 14-23.
Blackhurst, A., & Auger, R. (2008). Precursors to the gender gap in college enrollment:
Children's aspirations and expectations for their futures.Professional School Counseling,
11(3), 149-158.
Hill, N. E., & Wang, M. T. (2015). From middle school to college: Developing aspirations,
promoting engagement, and indirect pathways from parenting to post high school
enrollment. Developmental psychology, 51(2), 224.
Loera, G., Nakamoto, J., Oh, Y. J., &Rueda, R. (2013). Factors that promote motivation and
academic engagement in a career technical education context. Career and Technical
Education Research, 38(3), 173-190.
Martin, A. J. (2010). Should students have a gap year? Motivation and performance factors
relevant to timeout after completing school. Journal of Educational Psychology, 102(3),
561.

Stringer, K., Kerpelman, J., &Skorikov, V. (2012). A longitudinal examination of career
preparation and adjustment during the transition from high school.Developmental
psychology, 48(5), 1343.

Tables
Table 1
“How far do you think you will get?” Vs. earned credential frequency
F3A13ANEW
Total.00 1.00
F1S42NEW 1.00 8 2 10
2.00 17 11 28
3.00 84 63 147
4.00 456 432 888
5.00 129 104 233
6.00 908 1872 2780
7.00 444 1601 2045
8.00 287 847 1134
9.00 247 239 486
Total 2580 5171 7751

Table 2
“How far do you think you will get?” vs. earned credential Chi-square analysis
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 462.308a
8 .000
Likelihood Ratio 453.938 8 .000
Linear-by-Linear Association 139.951 1 .000
N of Valid Cases 7751
a. 1 cells (5.6%) have expected count less than 5.The minimum expected
count is 3.33.
Table 3
“How far do you think you will get?” vs. earned credential bar graph

Table 4
“Do you plan on going to school right after high school?”vs. earned credential,frequency
F3A13ANEWPAIR
Total.00 1.00
F1S45NEW 1.00 1893 4677 6570
2.00 260 196 456
3.00 178 140 318
Total 2331 5013 7344
Table 5
“Do you plan on going to school right after high school?”vs. earned credential,Chi-square analysis
Value df
Asymp. Sig. (2-
sided)
2 .000
count is 100.93.

Table 6
“Do you plan on going to school right after high school?”vs. earned credential,bar graph
Table 7
“Do you plan on continuing youreducation sometime in the future?” vs. earned credential,frequency
F3A13ANEWPAIR
Total.00 1.00
F1S47NEW 1.00 17 15 32
2.00 1893 4677 6570
3.00 243 214 457
4.00 87 52 139
5.00 127 73 200
Total 2367 5031 7398

Table 8
“Do you plan on continuing your education sometime in the future?” vs. earned credential,Chi-square analysis
Value df
Asymp. Sig. (2-
sided)
4 .000
count is 10.24.
Table 9
“Do you plan on continuing youreducation sometime in the future?” vs. earned credential,bar graph

Quantitative Educational Aspirations

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