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The Relationships among High School STEM Learning Experiences, Expectations, and Mathematics and Science Efficacy and the Likelihood of Majoring in STEM in College

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This study examines college students’ science, technology, engineering, and mathematics (STEM) choices as they relate to high school experiences, parent, teacher, and self-expectations, and mathematics and science efficacy. Participants were 2246 graduates of a STEM-focused public Harmony Public Schools in Texas, Harmony Public Schools (HPS). Descriptive analyses indicated that the overall percentage of HPS graduates who chose a STEM major in college was greater than Texas state and national averages. Logistic regression analyses revealed that males and Asian students are more likely to choose a STEM major in college than females and non-Asian students, respectively. Moreover, students whose parents had a college degree in the U.S. are more likely to major in STEM fields than those who did not. Furthermore, males with higher mathematics efficacy and females with higher science efficacy are more likely to choose a STEM major than their counterparts with lower mathematics and science efficacy.
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The relationships among high school STEM
learning experiences, expectations, and
mathematics and science efficacy and the
likelihood of majoring in STEM in college
Alpaslan Sahin , Adem Ekmekci & Hersh C. Waxman
To cite this article: Alpaslan Sahin , Adem Ekmekci & Hersh C. Waxman (2017): The relationships
among high school STEM learning experiences, expectations, and mathematics and science
efficacy and the likelihood of majoring in STEM in college, International Journal of Science
Education, DOI: 10.1080/09500693.2017.1341067
To link to this article: http://dx.doi.org/10.1080/09500693.2017.1341067
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The relationships among high school STEM learning
experiences, expectations, and mathematics and science
efficacy and the likelihood of majoring in STEM in college
Alpaslan Sahin
a
, Adem Ekmekci
b
and Hersh C. Waxman
c
a
Harmony Public Schools, Houston, TX, USA;
b
Rice University, Houston, TX, USA;
c
Teaching, Learning, and
Culture, Texas A&M University, College Station, TX, USA
ABSTRACT
This study examines college studentsscience, technology,
engineering, and mathematics (STEM) choices as they relate to
high school experiences, parent, teacher, and self-expectations,
and mathematics and science efficacy. Participants were 2246
graduates of a STEM-focused public Harmony Public Schools in
Texas, Harmony Public Schools (HPS). Descriptive analyses
indicated that the overall percentage of HPS graduates who chose
a STEM major in college was greater than Texas state and national
averages. Logistic regression analyses revealed that males and
Asian students are more likely to choose a STEM major in college
than females and non-Asian students, respectively. Moreover,
students whose parents had a college degree in the U.S. are more
likely to major in STEM fields than those who did not.
Furthermore, males with higher mathematics efficacy and females
with higher science efficacy are more likely to choose a STEM
major than their counterparts with lower mathematics and
science efficacy.
ARTICLE HISTORY
Received 20 February 2017
Accepted 8 June 2017
KEYWORDS
Integrative STEM; career
choice; mathematics and
science efficacy; Pygmalion
Introduction
A myriad of national reports emphasises the importance of science, technology, engineer-
ing, and mathematics (STEM) due to its critical role in securing a competitive edge in an
increasingly global economy (Augustine, 2007; National Research Council [NRC], 2013;
National Science Board [NSB], 2007; Presidents Council of Advisors on Science and
Technology [PCAST], 2012). What is particularly unsettling, however, is that the U.S. col-
leges do not produce adequate number of graduates in STEM fields (Chen & Solder, 2013;
Sass, 2015). Although the U.S. is a leader in the global economy and technology, university
degrees conferred in STEM fields in the U.S. is far behind other developed countries.
According to the National Science Foundation (NSB, 2016), almost one-third of university
degrees awarded in 2012 were in science and engineering in the U.S., whereas in China, for
example, almost half were in science and engineering. Among all university degrees in
science and engineering globally, 23% were conferred in China; 23% were conferred in
© 2017 Informa UK Limited, trading as Taylor & Francis Group
CONTACT Alpaslan Sahin sahinalpaslan38@gmail.com
Supplemental data for this article can be accessed at https://doi.org/10.1080/09500693.2017.1341067.
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION, 2017
https://doi.org/10.1080/09500693.2017.1341067
India; 12% were conferred in European Union; and only 9% were conferred in the U.S.
(NSB, 2016).
Given this critical STEM gap in the U.S., educators, policy-makers, and scientists have
been promoting studentsinterest and achievement in the STEM fields and have been
trying to understand the factors that may play an important role for student persistence
in STEM. The vast majority of existing evidence in the extant literature on student persist-
ence on STEM pipeline is based on college-level experiences (Sass, 2015). However, this
may conceal important impacts of pre-college experiences, preparation, and resources
on STEM persistence. The focus on college coursework, instructors, and grades in under-
standing STEM major and career choices only provides limited information about what
has happened to a student prior to attending college and, in turn, may not provide any
connection between post-secondary STEM choices and pre-college indicators. Research
indicates that high school and early grades are critical times for developing expectancies
for interest and success in STEM fields (Tai, Liu, Maltese, & Fan, 2006; Wang, 2013).
Therefore, the goal of this study is to investigate the factors at the high school level that
may relate to studentsentering the STEM pipeline. More specifically, high school
STEM experiences, teacher and parental expectations, and studentsmotivational beliefs
are the factors of interest in this study.
Theoretical framework
This study is grounded in social cognitive career theory (SCCT; Lent, Brown, & Hackett,
1994), which posits that ones career choice is influenced by the beliefs the individual
develops and refines through complex interplay between the individual, environment,
and behaviour. Like many other areas of human functioning such as organisational behav-
iour, SCCT is an extension and application of social cognitive theory (Bandura, 1986)to
career choice (Lent & Brown, 2006).
SCCT focuses on the interconnection of self-efficacy, outcome expectancy, and per-
sonal goals and how they may interrelate with other personal, contextual, and experien-
tial factors that generate aspirations for ones career choice (Lent et al., 1994). As part of
social cognitive construct, self-efficacy is defined as a judgment of ones capability to
accomplish a certain level of performance(Bandura, 1986, p. 391). Perceived self-effi-
cacy in a given academic domain has been found to predict sustained effort, choice,
and performance in that domain (Crombie et al., 2005). Self-efficacy is influenced by
personal mastery experiences, vicarious experiences (observation of models), social per-
suasion, and physiological indicators (Schunk, Pintrich, & Meece, 2008; Tschannen-
Moran & Hoy, 2001).
Moreover, SCCT suggests that decisions about a particular intent to pursue a field can
be explained by interests and goals (Lent & Brown, 2006; Wang, 2013). Selecting a STEM
major in college is conceivably influenced by studentsintent to pursue these fields upon
high school graduation or college entry. Given the key role of early science and mathemat-
ics experience in STEM persistence (Ma & Johnson, 2008), interest in majoring in STEM
can be argued as an outcome of motivational attributes and learning in science and math-
ematics at the high school level (Lee, Min, & Mamerow, 2015). Therefore, this intent may
be closely related to high school studentsmotivational beliefs, course takings, and achieve-
ment in science and mathematics (Wang, 2013).
2A. SAHIN ET AL.
A limited number of studies related to academic major choices in STEM have utilised
the SCCT theoretical framework to investigate issues relevant to STEM choice (Wang,
2013). Although SCCT emphasises the interchange among three main components (i.e.
individual, environment, and behaviour), very few studies have taken into account all
three aspects of career choice together. Lee et al. (2015) focused on self-efficacy and
social expectations; Wang (2013) considered motivational beliefs and academic work,
while Andersen and Ward (2014) examined motivational beliefs and academic perform-
ance in science and mathematics when studying the students STEM persistence. Maltese
and Tai (2011) and Lichtenberger and George-Jackson (2013), two of the most compre-
hensive studies in terms of factors that may have impact on STEM persistence, did not
investigate the social expectations and informal STEM activities students engage in.
This may be due to the vagueness of defining environment which may refer to many
different aspects of parental and school contextual factors. Moreover, some studies
focused on aspirations and intentions to purse a STEM major or career rather than the
long-term outcome of whether STEM choice has actually happened either in college or
after graduation from college (Andersen & Ward, 2014).
The present study integrates SCCT and previous research on factors closely connected
with academic choices of college students. While our goal is not to examine the structural
model of SCCT directly, this study addresses the interconnectedness among personal and
environmental factors and STEM choice. These factors are detailed below under two main
headings: (a) school contextual factors and (b) parental and teacher expectations. Unlike
previous research, the present study analyses the actual academic college records (i.e. aca-
demic major selection) of students who graduated from a public school system with a
STEM focus. Most studies utilised national large databases such as High School Longitudi-
nal Study-2009 (Andersen & Ward, 2014; Lee et al., 2015; Maltese & Tai, 2011; Wang,
2013) when studying STEM persistence. The present study avoids the issues with second-
ary analysis of national databases such as use of proper weights and restriction of variables
of interest (Rutkowski, Gonzalez, Joncas, & von Davier, 2010).
Factors influencing studentschoice of STEM majors
In their study of 25 education systems across the world, Barber and Mourshed (2007) ana-
lysed the student achievement outcomes of the best-performing school systems defined by
Organisation for Economic Co-operation and Development. What schoolsand school
systemshave to offer for the best education possible for every child is among the three
things that they found matter the most for student outcomes. School factors such as
course-offerings, extracurricular activities including science fairs and STEM clubs, and
early exposure to mathematics and science that schools can make available to its students
may be influential in studentsfuture choices and performance in STEM (Dabney et al.,
2012; Dawes, Long, Whiteford, & Richardson, 2015; Gottfried & Williams, 2013; Simp-
kins, Davis-Kean, & Eccles, 2006). Research indicates that there are several school level
factors related to both formal and informal STEM activities and experiences that are
associated with STEM college major selection and STEM career choice (Bottia, Stearns,
Mickelson, Moller, & Parker, 2015; Bouvier & Connors, 2011; Dabney et al., 2012;
Dawes et al., 2015; Nugent et al., 2015). More specifically, researchers have found
several factors that are related to students pursuing and persisting STEM fields, such as
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 3
(a) the number of courses taken (Chen & Solder, 2013; Simpkins et al., 2006); (b) early
exposure to mathematics and science (Anderson & Kim, 2006; Graham, Frederick,
Byars-Winston, Hunter, & Handelsman, 2013); (c) mathematics and science curriculum
(Elliott, Strenta, Adair, Matier, & Scott, 1996); (d) advanced level courses in mathematics
and science (Maltese & Tai, 2011; Wang, 2013); (e) STEM clubs and summer camps or
internships (Gottfried & Williams, 2013; Kong, Dabney, & Tai, 2013); (f) STEM teachers
and parentsexpectations (Lee et al., 2015); (g) opportunities and support students receive
(Seymour & Hewitt, 1997); (h) participation to science fairs (Dawes et al., 2015); and (i)
teacher quality and diversity (Andersen & Ward, 2014; Price, 2010).
Dawes et al. (2015) surveyed freshman college students studying STEM-related fields
to understand the reasons why they choose STEM degrees. They found that STEM
teachers, parents, and STEM engagement activities such as science fairs, STEM clubs,
and STEM internships had a great influence on studentsdecisions about majoring in
STEM. Gottfried and Williams (2013) studied the connection between mathematics
and science club participation and the probability of STEM major selection in college
and found that mathematics club participation was significantly associated with
increased likelihood of choosing STEM major in college. Moreover, research has also
found that participation in pre-college mathematics and science enrichment activities
is positively associated with motivational beliefs such as self-efficacy, value, and interest
mathematics and science in post-secondary years (Sass, 2015). Additional research has
indicated that developing expectancies for success and interests in mathematics and
science in pre-college years strongly increases the likelihood of students persisting in
STEM fields (Tai et al., 2006).
Parental and teacher expectations on studentseducational degree attainment
In addition to school and out-of-school level variables, researchers have also identified
other factors that affect studentseducational achievement and attainment including tea-
chers and parentsexpectations of students (Lee et al., 2015; Zhan, 2014). Both teachers
and parents have significant influence on studentsschool performances and college
matriculation (Fehrmann, Keith, & Reimers, 1987; Hossler & Stage, 1992). The effect of
these variables cannot be underestimated due to their mediating roles in studentsedu-
cational experiences (Hill & Tyson, 2009).
In their seminal work, Rosenthal and Jacobson (1968) investigated the effect of tea-
chersexpectations on studentsachievement. Their findings spawned research and led
to the development of a new branch of research called expectancy research. They found
that teachershigh expectations about their students increased the studentscognitive
ability positively; a phenomenon often defined as the Pygmalion effect(Rosenthal &
Jacobson, 1968). Later, researchers found that teachersexpectations are influenced by stu-
dentsgender, prior performance, race, ethnicity, and SES (Ferguson, 1998). Teachers were
found to treat students differently based on their level of expectations for different stu-
dents (Flores, 2007). For instance, depending on teacherslevel of expectations, teachers
have generally showed lower expectations for low-income students compared with their
high-income peers (Alvidrez & Weinstein, 1999; Muller, Katz, & Dance, 1999). These
lower expectations create a significant challenge for low-income studentsacademic out-
comes (Zhan & Sherraden, 2011). Eventually, these expectations affect studentssuccess
4A. SAHIN ET AL.
and attitudes towards mathematics and science which are pivotal in studentsaspirations
in STEM-related majors (Crisp, Nora, & Taggart, 2009).
Researchers further found that teacher expectations affect not only studentsacademic
performance, but also long-term educational goals like attending college (Benner &
Mistry, 2007). In particular, studies have indicated that mathematics and science teachers
expectation and encouragement have a strong positive correlation with studentsacademic
performance and majoring in STEM fields (Heaverlo, 2011). We also know that math-
ematics and science teachers play a pivotal role in augmenting low-income students
motivation and interest in mathematics and science which are precursors to develop
STEM interest that may result with pursuit of a career in STEM area (Shumow &
Schmidt, 2013).
Another adult group (especially mothers) that makes a difference in studentslives are
parents. Previous research showed that parental expectations affect studentseducational
success (Stevenson & Stigler, 1992; Stevenson, Chen, & Uttal, 1990). Christenson, Rounds,
and Gorney (1992) indicated that the connection between parental expectations and stu-
dentsperformance is complex because it involves many other mediating factors. For
example, parental behaviours such as contacting the schools and regularly encouraging
students to do school works have a direct effect on studentsacademic achievement
(Seginer, 1983). In other words, academic success is positively correlated with parental
expectations (Benner & Mistry, 2007; Boersma & Chapman, 1982; Catsambis, 2001).
Ma (2001) found that parentsexpectations are more influential than teacher or peer
expectations when it comes to college matriculation. Moreover, research found that par-
ental expectations are critical in studentsdecision to attend a college (Brasier, 2008;
Hossler & Stage, 1992). Children whose parents actively and positively intervene to
their childrens education perform higher than their peers whose parents do not
(Epstein, 2001). According to Rutchick, Smyth, Lopoo, and Dusek (2009), parental expec-
tations also change studentsexpectations of themselves. According to Rutchick, parental
educational expectations continue to impact studentsacademic performance even five
years later. Archer et al. (2013) found that aspirations in mathematics and science-
related areas are also affected by familial attitudes mostly from parents. In other words,
studentsmathematics and science efficacy as well as academic and vocational choices
are the results of parental expectations and attitudes (Lee et al., 2015). In summary, the
expectations of parents, teachers, and others (Pygmalion effect), either positive or nega-
tive, have great potential to influence studentsacademic motivation, behaviour, and per-
formance in content areas such as STEM (Brophy & Good, 1970; Lee et al., 2015;Ma,
2001). Given that early positive experience and performance are critical to a students
future success in STEM disciplines, Pygmalion effects may be pervasive in forming
future STEM workforce (Crisp et al., 2009; Lee et al., 2015)
Purpose of the study
Due to strategic importance of STEM education in countriesglobal leadership in
economy and innovation, there is a need to identify the characteristics of students who
have successfully navigated the STEM pipeline (Lee et al., 2015; Steffens, Jelenec, &
Noack, 2010). A very recent study investigated the effects of studentmathematics and
science efficacy and students, parents, and teachersexpectations in studentsSTEM-M
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 5
(edicine) career selection (Lee et al., 2015). The present study extends the Lee et al. study
and adds additional school and out-of-school level variables to shed more light about what
students do during high school in terms of academics and extracurricular activities that
might lead them to choose a STEM major. To accomplish this, we worked with a
Harmony Public Schools (HPS) that has a focus on STEM education. We aimed to
collect three groups of variables: (a) student and parent demographics; (b) school and
out-of-school academic variables; and (c) students, teachers, and parentsexpectations,
and studentsself-efficacy in mathematics and science. The purpose of this study is to
examine how studentshigh school experiences, their self, parent, and teacher expec-
tations, and mathematics and science efficacy are related to them majoring in STEM
choices after controlling student and parent demographics.
Our overarching research question was to investigate the characteristics of students
who have successfully navigated the STEM pipeline. More specifically:
1. What are the numbers of HPSalumni majoring in STEM degree compared to the state
of Texas and the Nation?
2. What are the impacts of both studentsschool and out-of-school activities on the like-
lihood to pursue a STEM degree?
3. What are the impacts of both teacher and parental educational expectations on stu-
dentsintentions to pursue a STEM degree?
4. What are the impacts of a studentsself-efficacy in mathematics and science and college
expectations on the likelihood to pursue a STEM degree?
Methods
Settings: HPS
HPS are a Texas-based charter management organisation (CMO) that operates 48 schools
serving a diverse student population of more than 30,000 students. Of which 61% of stu-
dents receive free or reduced price lunch and 68% are under-represented minorities. HPS
are serving K-12 grade students located in Texas with a strong focus on STEM providing
opportunities for underserved communities. The 48 schools are located in urban settings
such as Houston and Dallas and more rural sites in Brownsville, Laredo, etc. Beginning
with the launch of its first STEM-focused school in Houston in 2000 (HPS 2020, 2016),
HPS are an open-enrollment college prep school system. Because HPS are public
schools, they must follow all federal laws that apply to any other public school. Therefore,
they have to accept students by lottery and cannot choose its students based on their inter-
ests or achievements. Within the international context, HPS can be thought of as regular
public schools that have more autonomy in areas such as choosing their own curriculum
and accepting students from any distance like private schools. Although implications of
this study should be interpreted within HPS context, it could be informative for different
schools, school districts, or education systems around the world.
We chose to study HPS because the system schools provided almost all the variables
that SCCT described. For instance, HPS have their own integrative STEM teaching
approach called STEM students on the stage (SOS). It is an integrated interdisciplinary,
standards-focused, and engaging STEM teaching approach that is teacher-facilitated,
6A. SAHIN ET AL.
student-centred and directed through sets of open-ended and inquiry-based projects
(Sahin & Top, 2015). Students are required to use technology and social media extensively
to complete their projects for each project including website, digital video presentation,
brochure, and YouTube and Facebook pages. Culminating products are also presented
and saved in their individual e-portfolio. Students present their projects in different
occasions including school festivals, VIP visits, and different STEM Expos. STEM SOS
is used in all STEM courses integrated with English Language and Arts and Social
study courses. HPS also offers a variety of STEM clubs in addition to non-STEM clubs
including Robotics, game design, rocketry, solar car, MATHCOUNTS, and American
Mathematics Contest (AMC). Shortly, students find a variety of STEM-related opportu-
nities as part of the schools STEM mission.
Sample
The study utilises data from HPS alumni (n= 2246) who graduated between years 2005
and 2015. These students were either currently attending colleges or already graduated
from a college.
Data collection began in Fall 2015 by surveying all the HPS alumni (n= 2246) who
enrolled in colleges (including community colleges) between years 2005 and 2015. We
ended the data collection on 20 March 2016. A total of 697 students completed the
survey for a 31% response rate. A total of 56 students already graduated from 4-year col-
leges (see Table 1 in supplementary online materials).
1
The 697 participants included 298 males (43%), 141 white (20%), 59 black (8%), 347
Hispanic (50%), and 148 Asian students (21%). Only 15% of parents had obtained a
masters degree or higher. Twenty-six per cent of the parents had a 4-year college
degree. Parents with some college degree (e.g. 2 years) were 10%. The remaining 50%
Table 1. Student demographic information.
Group Not graduated Graduated Total Percentage
Gender
Male 281 17 298 0.43
Female 360 39 399 0.57
Total 641 56 697 1
Ethnicity
White 124 17 141 0.2
Black 50 9 59 0.08
Hispanic 326 21 347 0.5
Asian 139 9 148 0.21
Total 639 56 695 1
Parent education level
High school or less 318 24 342 0.5
Some college 64 5 69 0.1
Bachelors 157 20 177 0.26
Masters degree or higher 94 7 101 0.15
Total 633 56 689 1
Grades
Freshman 291 290 41.7
Sophomore 168 168 24.1
Junior 134 134 19.2
Senior 49 49 7
Graduated 56 56 8
Total 642 56 697 1
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 7
of parents had high school or lower degrees. Participating studentsgrades were scattered
as 291 freshmen (43%), 168 sophomores (24.1%), 134 juniors (19.2%), 49 seniors (7%),
and 56 college graduates (8%).
Instrument
We used an online survey consisting of 30 questions grouped under four categories of vari-
ables: (a) student demographics, (b) family context, (c) school- and out-of-school-related
activities, and (d) Pygmalion-related variables including student expectation about them-
selves, parent and teacher expectations, and studentsmathematics and science efficacy
(see Appendix 1). We used items from previously developed reliable and valid instrument.
We adapted Lee et al.s(2015) instrument and study design, but we added more student
and school-related variables to come up with a more comprehensive description of the
characteristics of students who choose STEM majors in college. In addition to Lees
et al. study variables (student and parent demographics, student, parent, and teacher
expectations, and studentsmathematics and science self-efficacy), we also included the
number of studentsproject and science fair completions, number of STEM club partici-
pation, number of STEM and total Advanced Placement (AP) course takings, status of
summer STEM camp experiences, and internship completion. Mathematics and science
self-efficacy items were adapted from previously developed valid and reliable scales
used in Longitudinal Study of American Youth (Lee et al., 2015; Miller, 2014). These
were the only constructs we measured in the study. Each question regarding efficacies
required students to rate their responses on a Likert-type scale of 15, with 5 being
strongly agree. High instrument reliabilities for the mathematics and science self-efficacy
were obtained using Cronbachs alpha .939 and .947, respectively.
We shared the survey link with the alumni through Facebooks and e-mails. To increase
participation, we gave 40 $50 credit card gift cards by lottery. The first author provided
weekly updates to the director. After four reminders, the final participant number was 697.
Variables
We had one dependent variable named STEM Major. Students indicated either 1as
majoring in STEM-related area or 0indicating not STEM majoring area. We used Lee
et al.s(2015) approach and defined STEM majors as the combination of National
Science Foundation (2010)s STEM profession classification and medicine-related
majors. We used the term STEMas our acronym to represent all STEM and Medicine
majors. We had two groups of independent variables. The first group included school-
and out-of-school-related activities like studentsnumber of STEM club participation,
STEM AP course taking, number of science fair participation, number of STEM-related
project completion, summer STEM camp participation, and any STEM-related internship
done at local universities or medical institutes. The second group of variables included stu-
dentsexpectation about their educational attainment, parentsand STEM teachersexpec-
tations, and studentsmathematics and science efficacy. We used studentsgender,
ethnicity, parentseducation level, parentscollege degree, and household income as our
control variables to examine how other variables related to STEM major, after statistically
controlling for student and parent demographics.
8A. SAHIN ET AL.
Analyses
First, we did descriptive analyses to show how the school systems graduatesSTEM
selection percentage compared with the state and national averages. Second, because
our dependent variable is a dichotomous, we employed multiple binary logistic
regression to test our models. We first ran a binary logistic regression to examine
which group of variables predicted studentsprobability of STEM major selection.
Later, we ran separate binary logistic regressions for each gender because gender was sig-
nificant in the first analysis. Table 2 provides the descriptive for the variables used in the
data analyses.
Results
Research question 1
For the first question,the descriptive findings highlight the fact that HPS graduates who
responded to the survey were more than twice as likely to choose a STEM field major
than the average of students (a) across the state of Texas and (b) across the U.S. (see
Table 3). In addition, about four times as many females chose a STEM major than
the state and national averages. Finally, we saw that Black, Hispanic, and Asian students
were twice as likely to choose STEM majors than other students in the state and national
averages.
Research question 2
First, the data analyses revealed that from among all school and out-of-school factors,
none of them came out as significant (see Table 4). Covariates male and Asian variables
were significant. That is, male students are 2.15 times more likely to choose a STEM
major in college than female students do. Likewise, Asian students are 1.92 times more
likely to choose a STEM major than non-Asian students do.
Table 2. Descriptive data for participants.
NRange Mean Std. deviation
Gender 697 01 0.43 0.50
White 698 01 0.20 0.40
Black 698 01 0.08 0.28
Hispanics 698 01 0.50 0.50
Parent college degree (Y/N) 689 01 0.35 0.48
Parentseducation level 689 15 3.05 1.16
Household income 688 13 1.95 0.76
Count STEM club participation 698 02 0.76 0.80
Count STEM project participation 636 05 2.75 1.64
Count science fair participation 698 08 2.69 3.30
STEM AP course taking 603 08 1.89 1.80
Summer camp(Y/N) 634 01 0.13 0.336
STEM internship(Y/N) 634 01 0.14 0.349
Student expectation 608 17 4.61 1.08
Parents expectation 624 14 3.67 0.68
Teacher expectation 624 14 3.59 0.69
Math efficacy 624 15 3.83 1.10
Science efficacy 624 15 3.83 0.96
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 9
Research questions 3 and 4
For the second and third questions, we ran another logistic regression analysis where
we controlled for gender and ethnicities (see Table 5). We found that male students are
2.05 times more likely to consider a STEM degree in their first year of college. It was
also found that students with higher measures of mathematics efficacy are 1.33 times
more likely to select a STEM major in college. Similarly, students with higher measures
of science efficacy are 1.37 times more likely to consider a STEM field in their college
study.
We ran separate analyses for male and female students, respectively. Table 6 presents
findings from the third logistic regression analysis for males. We found that Asian
students are 2.51 times more likely to choose a STEM major during first year of college
(p< .05).
In the second part of logistic regression analysis for malesPygmalion effect vari-
ables, we found that male Asian students are 3.05 times more likely to choose a
STEMmajorincollege.Itwasalsofoundthatmalestudentswithhighermathematics
efficacy are 1.60 times more likely to pursue in STEM-related field in college (see
Table 7).
In a separate analysis for girls, it was found that students whose parents had a college
degree in the U.S. are 2.08 times more likely to major in STEM fields in college (see
Table 8). In the second part of logistic regression analysis for femalesPygmalion effect
variables, we found that students with higher science efficacy measures are 1.40 times
more likely to major in STEM in college (see Table 9).
Table 3. STEM field majoring percentages by gender and ethnicity.
Overall Male Female White Black Hispanics Asian
HPS STEM 58.1 61.7 55.2 52.5 56.7 58.1 63.5
State_STEM
a
27 43.20 13.60 29 24.20 27 33.70
National_STEM
b
25 40 15 27 22 25 33
a
From My College Options (2012).
b
From ASTRA (2015).
Table 4. Logistic regression coefficients for school- and out-of-school-
related variables.
BExp(B)
Parent bachelor degree in the U.S. 0.451 1.570
Parent education level 0.001 0.999
Household income 0.05 0.951
Male 0.770* 2.159
Asian 0.657* 1.929
Black 0.089 1.037
Hispanics 0.412 1.077
STEM club participation 0.136 2.051
STEM projects completed 0.043 0.757
Science fair participated 0.036 1.977
STEM AP taking 0.074 0.609
Summer camp 0.719 0.915
STEM internship (Y/N) 0.279 0.663
Constant 1.726 0.178
*p< 0.05.
10 A. SAHIN ET AL.
Table 5. Logistic regression coefficients for Pygmalion effect variables.
BExp(B)
Male 0.718* 2.050
Black 0.352 1.422
Hispanics 0.260 1.297
Asian 0.617* 1.854
Parent bachelor degree in the U.S. 0.232 1.261
Household income 0.054 0.948
Parent educational level 0.050 1.051
Student expectation 0.033 1.033
Parents expectation 0.019 0.981
STEM teacher expectation 0.042 0.959
Math efficacy 0.291* 1.337
Science efficacy 0.316* 1.371
Constant 2.617 0.073
*p< 0.05.
Table 6. Logistic regression coefficients for male studentsSTEM major
selection: in school and out-of-school variables.
BExp(B)
Black 0.461 1.586
Hispanics 0.042 1.043
Asian 0.923* 2.517
Parent bachelor degree in the U.S. 0.264 0.768
Household income 0.037 1.038
Parent educational level 0.133 1.142
STEM AP course taking 0.044 1.045
Summer camp 0.827 2.287
STEM internship 0.397 0.672
Science fair participation 0.019 1.019
STEM projects completed 0.026 1.026
STEM club participation 0.170 1.186
Constant 0.208 0.812
*p< 0.05.
Table 7. Logistic regression coefficients for male studentsSTEM major
selection: Pygmalion variables.
BExp(B)
Black 0.605 1.831
Hispanics 0.424 1.529
Asian 1.118* 3.059
Parent bachelor degree in the U.S. 0.229 0.795
Parent education level 0.218 1.244
Household income 0.011 1.012
Student expectation 0.130 0.878
Parents expectation 0.291 0.747
STEM teacher expectation 0.022 0.978
Math efficacy 0.476* 1.609
Science efficacy 0.312 1.366
Constant 1.627 0.197
*p< 0.05.
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 11
Discussion
In the present study, we examined whether HPSstudents who graduated from high school
choose STEM as their major in college and what factors they perceived influenced their
decision for choosing STEM as their college major. The results of the present study are
encouraging, although not surprising since HPSs STEM focus, in that they suggest that
HPS students who responded to the survey were much more likely to choose a STEM
major in college than typical high school students from the state of Texas and the U.S.
This finding suggests that schools and school districts may be able to influence students
interest in becoming a STEM major. What is even more encouraging is that we found that
female, black, and Hispanic students from HPS were also much more likely to choose a
STEM major in college than the typical student from the state of Texas and the U.S.
The gap for female and black students, in particular, seemed to be a lot smaller for HPS
students when compared to statewide and national rates. These dramatic findings of
STEM field majors suggest that the HPS have been successful in closing the STEM oppor-
tunity gaps that have persisted over time for female and minority students in Texas and the
U.S. Although females from HPS were much more likely to choose STEM majors than
other female students in Texas and the U.S., we still found that HPS male students
Table 9. Logistic regression coefficients for female studentsSTEM major
selection: Pygmalion variables.
BExp(B)
Black 0.150 1.161
Hispanics 0.236 1.266
Asian 0.302 1.352
Parent bachelor degree in the U.S. 0.631 1.879
Parent education level 0.087 0.917
Household income 0.086 0.918
Student expectation 0.117 1.124
Parents expectation 0.123 1.131
STEM teacher expectation 0.043 0.958
Math efficacy 0.203 1.225
Science efficacy 0.334* 1.397
Constant 2.851 0.058
*p< 0.05.
Table 8. Logistic regression coefficients for female studentsSTEM major
selection: in school and out-of-school variables.
BExp(B)
Black 0.207 1.230
Hispanics 0.193 1.212
Asian 0.482 1.619
Parent bachelor degree in the U.S. 0.731* 2.077
Parent education level 0.152 0.859
Household income 0.082 0.921
STEM clubs participated 0.104 1.110
STEM projects completed 0.091 1.095
Science fair participated 0.089 1.093
STEM AP course taking 0.070 1.073
Summer camp 0.219 1.245
STEM internship 0.312 1.366
Constant 0.613 0.542
*p< 0.05.
12 A. SAHIN ET AL.
were about twice more likely than HPS female students to consider a STEM degree in their
first year of college. Explanations for these sex-related differences need to be explored in
greater detail in future studies. Similar to other U.S. studies, we also found that HPS Asian
students were more likely to choose a STEM field than students from other racial groups.
This overrepresentation of Asians in STEM majors has similarly persisted over time and is
due to a number of factors including Asian studentshigher test scores and class ranks.
Factors influencing STEM career choice
Our study used logistic regression to examine whether (a) school and out-of-school factors
and (b) student, teacher, parent expectations and studentsmathematics and science effi-
cacy impact studentsdecision to major in a STEM field. Surprisingly, we found that stu-
dents, parents, and STEM teachersexpectations were not predictive of choosing a STEM
major.
Although prior research found that parent expectations influence studentspersistence
in STEM fields (Archer et al., 2013; Lee et al., 2015;Ma,2001), our findings show that
parentscollege degree, education level and household income did not impact students
decision to enroll in a STEM major in college. One explanation for this finding is that
there may be an inherent selection bias due to the fact that HPS are a charter school
system where parents chose to send their children to school because of its reputation,
especially in the STEM area. Consequently, most HPS parents probably have similar
high expectations and STEM aspirations for their children.
Prior research has found that teacher expectations (Heaverlo, 2011; Shumow &
Schmidt, 2013) strongly increase the likelihood of students persisting in STEM fields.
The findings from the current study, however, did not arrive at the same conclusions.
This may be due to the fact that the emphasis on STEM is prevalent in all 48 HPS. Fur-
thermore, the districts inquiry-based project STEM teaching approach is consistently
implemented across the district (Sahin & Top, 2015). Consequently, teacher expectations
and encouragement for studentssuccess in STEM are fairly high and consistent across the
district, but that invariance did not allow us to determine its actual impact on students
career choice.
Prior research has found that student participation in STEM school-based activities
influences studentsSTEM aspirations (Dabney et al., 2012; Dawes et al., 2015; Gottfried
& Williams, 2013; Nugent et al., 2015; Sass, 2015). We found, however, that none of the
school and out-of-school factors such as participating in a STEM club, STEM projects,
science fair, summer camp, or a STEM internship were predictive of choosing a STEM
major in college. This may be due to the limited frequency of most of the activities like
summer camp, STEM internships, and STEM clubs. It may also be related to the way
we measured school activities. We focused on the quantity of activities rather than the per-
ceived quality of those activities. A more comprehensive measure focusing on the quantity
and quality of school activities may be important to consider in future studies.
We also found that students with higher measures of mathematics and science efficacy
were more likely to consider a STEM field for their college major than students with lower
measures of mathematics and science efficacy. This lends support to the importance of
social cognitive theory (SCCT) that focuses on how aspects of self-efficacy are associated
with career choice.
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 13
Overall, it appears that student, parent, and STEM teacher expectations did not influ-
ence studentschoosing a STEM major. This may be due to the limited variability of
responses (i.e. small standard deviations) for parent and teacher expectations. Although
there is more variation for studentsexpectations, it appears that studentsmathematics
and science efficacy may be more influential in studentsSTEM career choice than their
expectations.
Limitations and future research
One of the limitations of this study is the relatively small response rate (31%) of HPS
graduates. While this response rate is quite similar to other studies, we ideally would
have preferred a much higher response rate. Future studies might want to include more
incentives to potentially increase the response rate.
Another limitation of the study relates to the measurement of variables. Although
student self-report measures have been used in many similar STEM studies (Gottfried
& Williams, 2013; Lee et al., 2015), there are some concerns about the use of such measures
due to the possible large measurement error with self-reporting items (Bertrand & Mul-
lainathan, 2001). Future studies could address this issue by either including other data
resources or triangulation of the data (Denzin, 2012).
A final limitation of the study is that it was conducted in one large school district that
was implementing an integrated STEM curriculum for several years. For future studies, it
would be interesting to include other large school districts so that we could possibly
compare across districts on how the three factors of (a) demographics, (b) school and
out-of-school factors, and (c) Pygmalion effect variables such as student, teacher, parent
expectations and studentsmathematics and science efficacy differentially affect students
choosing STEM majors in college.
Additional studies could also include other research methods such as interviewing stu-
dents, teachers, and school administrators to address research questions that focus on
other personal, school, and out-of-school factors that may have motivated students to
choose STEM majors in college. Content analyses of teacherslesson plans and the HPS
school curriculum could also provide interesting data about the extent to which STEM
is integrated in the curriculum. Finally, observational studies would be useful to determine
the actual quality of the STEM integration in schools and classrooms.
Additional research is also needed to the relations among studentsexpectations and
their mathematics and science efficacy. Future studies, for example, might want to see
what school and out-of-school factors influence studentsmathematics and science efficacy.
Conclusions
Although the descriptive and correlational nature of the results does not allow causal infer-
ences, the findings of this study provide valuable information to educators and researchers
involved in STEM education. First, the study makes an important contribution and pro-
vides support for the SCCT (Lent et al., 1994). The present study is one of the few studies
in the field that have used the SCCT framework to examine all three aspects of career
choice (i.e. individual, environment, and behaviour) together. A second important contri-
bution of this study involves the adaptation of an existing instrument (Lee et al., 2015) that
includes more student- and school-related variables (e.g. number of student projects,
STEM courses, STEM club, and internship participation). This adapted instrument
14 A. SAHIN ET AL.
provides us with a comprehensive measure of the STEM-related opportunities that stu-
dents had in high school. A third important contribution of this study is that it focuses
on high school graduates and the decisions that they have already made regarding entering
the STEM field. Most prior studies in this field generally obtained high school student per-
ceptual data of whether they expect to enter a STEM field without actually knowing
whether they will even graduate from high school. Fourth, the unique school system
that participated in the present study suggests that urban and rural schools serving predo-
minantly low-income and unrepresented minorities can be successful in closing the STEM
opportunity gaps by encouraging all of their students to enter the STEM pipeline. This
finding should be heartening to many school systems across the world that have been chal-
lenged with the encouraging more of their low-income high school students to choose
STEM careers in college. This district invested heavily in STEM-related school activities
and the findings appear to be promising.
Last but not least, even though implications of this study should be interpreted within
HPS context, it could be informative for different schools, school districts, or education
systems around the world. Many countries are emphasising the need to incorporate
STEM activities in high school in order to encourage students to choose STEM careers.
The findings from this study provide some promise in that this school system is doing
better than the state and national averages in terms of having students choose STEM
majors in college. The findings from this study also provide caution to educators across
the world because most of the STEM school activities such as STEM clubs, STEM projects,
science fairs, summer camps, and STEM internships were not found to be predictive of
students choosing a STEM major in college. What we did find, however, was that high
school studentswith high measures of mathematics and science efficacy were more
likely to choose a STEM field for their college major. This suggests that schools may
need to focus on developing interventions to increase studentsefficacy in science and
mathematics rather than merely implement more school-related STEM activities. This
emergent finding provides new insight into how school systems may want to proceed
in order to promote STEM in their high schools.
Note
1. All the tables are provided in the supplementary materials for the interested reader.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Alpaslan Sahin http://orcid.org/0000-0001-7096-3513
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APPENDIX 1
Student Demographics
Please answer questions below:
* 2. Please enter your first name
3. Middle initial
* 4. Last name
* 5. Campus name
* 6. High school graduation year
* 7. College name
* 8. Year in college
Freshman
Sophomore
Junior
Senior
Graduated
* 9. What major did you get admitted to after high school?
Agricultural sciences
Chemistry
Computer Science
Engineering
Environmental Science
Geosciences
Life/Biological Sciences
Mathematics
Physics/Astronomy
Medicine/Medical
Business
Social Sciences
Communication/RTF
Liberal Arts
General
Study/Undecided
Other (please specify)
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 19
Family Context
Please answer the following questions:
* 10. Did either of your parents have a college degree in the United States when you were in high
school?
Yes
No
* 11. What was your parents highest level of education when you were in high school?
Less than high school
High school diploma or GED
Associates degree
Bachelors degree (4-year)
Masters degree or higher
* 12. What was your estimated household income when you were in high school?
Less than $30,000
Between $30,000$69,000
Higher than $69,000
* 13. Which clubs did you attend during high school? (Check all that apply)
American Mathematics Competition (AMC)
Math Contest
Science Olympiad
Astronomy
Harmony Scientific Research Society
Biology
Computer Science Club
Rocketry Club
Advanced Research Club
Environmentalists
FTC Robotics
Sea Perch
Project Construction Scale Modeling
Spanish
Health
French
Folk Dance
Cheerleading
Chess
Poetry
Odyssey of the Mind
Drama
Shell Eco
College Readiness and Leadership Program (CRLP)
Other (please specify)
20 A. SAHIN ET AL.
* 14. How many Science, Technology, Engineering, and Mathematics (STEM)-related projects did
you complete?
0
1
2
3
4
* 15. In which subject(s) did you complete a STEM-related project(s)?
* 16. Where did you present your STEM project(s) at? (Check all that apply)
School, city, and/or state science fairs
Classroom
School festivals VIP visits
I-SWEEEP Competition
STEM EXPOs
Texas Celebration of STEM Education Week
Outside STEM Events
Other (please specify)
* 17. Please enter the information regarding science fair competitions you participated in during
your high school years.
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 21
* 18. How many STEM-related Advanced Placement (AP) courses did you take during high school?
* 19. Did you attend any Science, Technology, Engineering, and Mathematics (STEM)-related
summer camps?
Yes
No
* 20. Did you participate in any Science, Technology, Engineering, and Mathematics (STEM)-
related internships at a medical and/or higher ed(university) institutions?
Yes
No
* 21. Did you already graduate from a college?
Yes
No
* 22. Was your college degree in one of STEM-related areas?
Yes
No
* 23. Do you have intent to declare a science, technology, engineering, and mathematics (STEM)-
related major in college?
Yes
No
* 24. What type of career did/will you pursue?
Agricultural sciences
Chemistry
Computer Science
Engineering
Environmental Science
Geosciences
Life/Biological Sciences
Mathematics
Physics/Astronomy
Medicine/Medical
Business
Social Sciences
Communication/RTF
Liberal Arts
Other (please specify)
22 A. SAHIN ET AL.
* 25. Do you feel that your high school experience at CSS provided you the opportunities to obtain/
develop skills and content necessary to perform your college STEM work?
Strongly Agree
Agree
Neither Agree nor disagree
Disagree
Strongly Disagree
* 26. Please choose three factors you think affect(ed) your career interest most.
Teachers
Parents
Science Fairs
Afterschool clubs
Summer camps
Internships
Early exposure to science and/or mathematics
Science curricula
Gender
Socioeconomic status
Self interest
Other (please specify)
Pygmalion Effect Variables
We would like to know how much influence your, your parents, and your STEM teachersexpec-
tations had on your college enrollment and persistence (and completion if applies). Please answer
the following 5 questions as much as you remember about your perceptions or beliefs about your-
self, your parents, and your teachers.
* 27. What was your educational degree expectation about yourself during high school?
High school or less
Vocational training
Some college (ex: 2-year)
College graduation
Masters
Doctorate or Professional Degree
Dont know
* 28. How encouraging were your parents about going to college?
Not encouraging at all
Somewhat encouraging
Encouraging
Strongly encouraging
* 29. How encouraging were your STEM teachers about going to college?
Not encouraging at all
Somewhat encouraging
Encouraging
Strongly encouraging
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION 23
* 30. How confident were you about your performance in math while you were in high school?
Strongly Agree Agree Neutral Disagree Strongly Disagree
I was good at Math
I understood Math well
* 31. How confident were you about your performance in science while you were in high school?
Strongly Agree Agree Neutral Disagree Strongly Disagree
I was good at Science
I understood Science well
24 A. SAHIN ET AL.
... Parental expectations are generally characterised as parents' realistic beliefs or judgements about their children's future achievements (Yamamoto & Holloway, 2010). The positive impact of parental expectations on students' likelihood of majoring in STEM in college and further their career aspiration has been documented (Lloyd et al., 2018;Mau & Li, 2018;Sahin et al., 2017;Woong Lee et al., 2015). However, such an effect on students' career aspirations may decrease, unless the students themselves perceive them (Šimunović et al., 2018). ...
... As a result, despite students' high self-concept in science and mathematics learning, they may experience greater stress and anxiety if they perceive that they are learning for their parents' sake, which may further negatively affect their aspiration for related work, as presented by the negative indirect impact of self-concept on career aspiration through outcome expectations for parental reasons. Such an explanation supports the statement indicated by Sahin et al. (2017) that there is an optimal range for parental expectations and this range needs to be further determined. Additionally, in light of possible gender and cultural differences in the relationship between self-concept and career aspirations, future research may deepen this study by investigating the role of different regions and genders in these relationships, particularly in the mediating effect of career outcome expectations. ...
... The findings of this study showed that perceived parental expectations may not have a direct impact on students' aspirations for STEM careers, which differs from prior research that parental expectations influence students' persistence in STEM fields (Lloyd et al., 2018;Mau & Li, 2018;Sahin et al., 2017;Woong Lee et al., 2015). This difference may be attributed to students' perceived parental expectations being lower than parents' actual expectations (Šimunović et al., 2018). ...
... Family SES was based on parents' education, occupation, and income. Following Sahin, Ekmekci, and Waxman [97], we counted the highest level of education of both parents (1: they had a college degree, 0: they did not). In addition, we investigated whether either parent had a STEM-related job (1: STEM-related career, 0 not STEM-related), according to Standard Occupational Classification [98]. ...
... Social support from schools, teachers, and peers was measured by four items as an independent variable (see Appendix A). These were largely adapted from Sahin, Ekmekci, and Waxman [97]. Similarly, we used a five-point Likert scale to identify students' social support. ...
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Faced with a shortage of college graduates with STEM degrees, many countries are seeking ways to attract more high school students to pursue STEM majors after graduation. This study aims to promote the sustainability of high school students in STEM fields by analyzing the effects of digital competence on the STEM major intentions of high school students. The survey collected data from 2415 participants comprising 1230 females and 1185 males from 16 high schools in China. Using hierarchical logistic regression, the study found that digital competence had significant positive effects on high school students’ STEM major intention. Also, computational thinking was the strongest predictor among the four areas of digital competence. Moreover, latent profile analysis identified two profiles of male students and four profiles of female students. Among male students, advanced male users had the strongest STEM major intention; among female students, low-level female novices had the weakest STEM major intention. Thus, digital competence can be considered an effective way to bridge the gender gap in STEM major selection. Based on the findings, strategies are discussed for improving high school students’ STEM major intentions and promoting digital competence, thereby ensuring the sustainable development of students in STEM fields in the digital era.
... This trend may be attributed to the role of secondary education in shaping students' academic trajectories and career aspirations, making it a strategic stage for intervention implementation. This focus was evidenced in research conducted in secondary education settings that examine students' self-efficacy, grade expectations, and career aspirations in STEM (Chen et al., 2022;Sahin et al., 2017;Thompson, 2021;Tzu-Ling, 2019). These studies elucidated the prominent emphasis on secondary education in STEM interventions. ...
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Education in the STEM fields—science, technology, engineering, and mathematics—has become essential to learning in the twenty-first century, particularly in rural places where resources for education are sometimes scarce. The present state of STEM education in rural regions is examined in this systematic study, with an emphasis on the use of STEM interventions and technology. The goals are to close the knowledge gap in rural STEM interventions and to provide research directions to improve STEM education in rural areas. This systematic review examined 64 articles in rural STEM education published between July 2013 and June 2023. The findings revealed that while STEM toolkits have proven effective in enhancing student engagement and academic performance in non-Asian contexts with most studies conducted in North America, there is a significant lack of understanding of their implementation and impact in Asian rural communities. Future research should focus on creating STEM interventions that are resource-conscious and culturally sensitive as well as expanding the use of artificial intelligence (AI) technologies in rural STEM education. Comprehensive teacher training programs are needed to give educators the tools they need to successfully implement STEM education. Rural STEM education could empower students to actively participate in the global economy and foster positive community impacts.
... En general el problema principal con el que se enfrenta las potencias económicas en la actualidad es la escasez de recurso humano especializado en CTIM. Por lo que diversos estudios han abordado desde varios enfoques el interés de los jóvenes por elección de carreras CTIM, desde el género, autoeficacia, logros académicos, apoyo parental, etc., (Avendaño et al., 2017, Sahin et al., 2017Sinclair et al., 2019;Tellhed et al., 2016). Sin embargo, la literatura nos indica que son escasos los estudios que relacionen las habilidades sociales con el interés por elección de carreras CTIM, por consiguiente, el objetivo de este estudio es develar las relaciones existentes entre las habilidades sociales de comunicación e interacción con desconocidos, la autoeficacia y el interés en elección de carreras en CTIM. ...
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Introducción: En un contexto social de constantes cambios mediado por avances tecnológicos y la IA, se agudiza la demanda de personal especializado en ciencias, tecnologías, ingeniería y matemáticas (CTIM), sin embargo, la escasez de recursos humanos en estas áreas es alto, por lo que el propósito de este estudio es explicar las relaciones existentes entre las variables de estudio. Metodología: Este estudio fue realizado bajo el enfoque cuantitativo, con un diseño no experimental transversal de tipo explicativo, la muestra estuvo compuesta por 904 estudiantes (DT= 0,67); 462 eran mujeres (M=17,35 años; DT=0,66) y 442 hombres (M=17,46 años; DT= 0,68) de bachillerato pertenecientes a los pueblos originarios del sur de México. Resultados: El modelo estructural indica que existe relación entre las variables, que la autoeficacia influye directa y positiva en el interés por carreras CTIM. Discusión: Existen múltiples estudios que buscan explicar los factores que predominan en el desarrollo del interés en carreras CTIM, además esta investigación contribuye a la validación de los postulados propuestos en la teoría social cognitiva de la carrera. Conclusiones: Se sugiere replicar este estudio en contextos similares en las que se incluya al género como un factor moderador del interés por elección de carreras CTIM.
... Matematika merupakan salah satu cabang ilmu pengetahuan yang turut dalam memajukan Pendidikan (Sahin, Ekmekci, & Waxman, 2017). Matematika dengan konsepkonsep yang sederhana hingga kompleks, sistematis, logis, dan hierarkis telah memberikan peranan yang sangat penting bagi kehidupan manusia (Nahdi & Jatisunda, 2020). ...
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In the global economy that is intertwined with scientific and technical knowledge and innovation, raising a Science, Technology, Engineering, and Mathematics (STEM)-literate generation of students has emerged as one of the paramount goals of most countries. Educational models that contribute to meeting those countries’ goals have become important in education. The absence of standards-focused, ready-to-teach teacher and student materials and lack of regular teacher trainings are some of the barriers attributed to the current STEM teaching approaches. Against this background, we investigated a successful STEM teaching model that has ready-to-teach materials, standards-focused, regular teacher professional trainings and student choice and voice that utilize both classroom and out-of-classroom projects as a solution to the aforementioned issues. The purpose of this research is to examine a new STEM teaching approach developed by a public charter school system, Harmony Public Schools (HPS). We used theoretical sampling; 11 semi-structured interviews were conducted with high school students. Grounded theory and constant comparative analysis were utilized. Study findings have revealed that the students were active learners most of the time, presenting and sharing their findings with classmates and visitors. Thus the title of this research, STEM Students on the Stage (SOS), is used to describe this model. In addition, emerging substantive theory suggested that STEM SOS model helped students learn STEM subjects better, cultivate STEM subject interests, and develop skills for their college and professional lives. Implications of the effect of this model on K-12 students’ learning experiences are discussed in detail.
Chapter
Producing sufficient numbers of graduates who are prepared for science, technology, engineering, and mathematics (STEM) occupations has become a national priority in the United States. To attain this goal, some policymakers have targeted reducing STEM attrition in college, arguing that retaining more students in STEM fields in college is a low-cost, fast way to produce the STEM professionals that the nation needs (President's Council of Advisors on Science and Technology [PCAST] 2012). Within this context, this Statistical Analysis Report (SAR) presents an examination of students' attrition from STEM fields over the course of 6 years in college using data from the 2004/09 Beginning Postsecondary Students Longitudinal Study (BPS:04/09) and the associated 2009 Postsecondary Education Transcript Study (PETS:09). In this SAR, the term STEM attrition refers to enrollment choices that result in potential STEM graduates (i.e., undergraduates who declare a STEM major) moving away from STEM fields by switching majors to non-STEM fields or leaving postsecondary education before earning a degree or certificate.1 The purpose of this study is to gain a better understanding of this attrition by: • determining rates of attrition from STEM and non-STEM fields; • identifying characteristics of students who leave STEM fields; • comparing the STEM coursetaking and performance of STEM leavers and persisters; and • examining the strength of various factors' associations with STEM attrition. Data from a cohort of students who started their postsecondary education in a bachelor's or associate's degree program in the 2003-04 academic year were used to examine students' movement into and out of STEM fields over the subsequent 6 years through 2009. Analyses were performed separately for beginning bachelor's and associate's degree students. For brevity, these two groups are frequently referred to as bachelor's or associate's degree students in this study. Selected findings from this SAR are described below.
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This study incorporates teacher and child perceptions of child school experiences into the examination of the reciprocal influence between teacher and child educational expectations and child academic achievements. Analyzing a longitudinal data from north-west rural China, the results highlight strong lagged effects of child school experiences: a child's early feelings of disengagement have strong negative impact on his/her later educational expectations and achievements, while the teacher's early evaluations of the child are closely linked to later teacher expectations and child achievement. A child's family background has almost no direct effect on child and teacher expectations and achievements when controlling child and teacher perceptions of child's progress in school. The findings suggest that future studies should focus more on child school experiences, which is a topic that has brought much insight to disparities in educational outcomes in developed countries.
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Background/Context Schools are integral to augmenting and diversifying the science, technology, engineering, and mathematics (STEM) workforce. This is because K–12 schools can inspire and reinforce students’ interest in STEM, in addition to academically preparing them to pursue a STEM career. Previous literature emphasizes the importance of high-quality STEM academic preparation in high school and the role of informal and formal exposure to STEM as important influences on students’ chances of following a STEM career. Interestingly, although many students decide to major in STEM fields while they are in high school, the majority of the extant literature about why students choose STEM majors primarily focuses on students’ experiences during the college years. Purpose/Objective/Research Question/Focus of Study Through our research, we seek to investigate how learning experiences of inspiration/reinforcement/preparation toward STEM that students have during high school can help explain the stark differences in STEM involvement by gender and ethnicity. We first investigate the importance of high school inspirational/ reinforcing/ preparatory experiences for students’ intent to major in STEM while in high school. We then see how they relate to students’ actual choice of a STEM major. We do this focusing on gender and racial/ethnic differences in outcomes. Specifically, we analyze the impact of the timing of high school STEM courses (algebra, biology, and physics), the quantity of STEM-related classes, and the quality of these courses on students’ decision to pursue a college STEM major. Research Design This is an analysis of quantitative data gathered about members of North Carolina's 2004 high school graduating class who also matriculated to one of the 16 campuses of the University of North Carolina system. Our research developed in two different stages. In the first stage, we utilize multilevel binomial models to examine students’ intent to declare a STEM major in their senior year of high school. In the second stage, we employ multilevel multinomial models to analyze chances of declaring a STEM major during the years 2005–2011, when students are in college. Findings/Results Findings suggest that STEM experiences of inspiration/reinforcement/ preparation during high school interact with demographic variables to moderate students’ interest in STEM. Taking physics and intending to major in STEM during high school are the variables most closely associated with students’ choice of STEM as a major. In addition, taking physics is especially important for young women's odds of declaration of STEM. Conclusions/Recommendations Findings suggest several policy recommendations: Provide a variety of high school learning STEM experiences that will link and augment students’ interest in STEM; change the way physics is presented to female students; utilizing curricula and pedagogy that focus on ways that physics is personally relevant may increase the number of young women who take the course in high school; increase the quality of the STEM-related academic preparation of students; particular attention should be given to underrepresented subgroups of students; increase the offering of math and science-focused program at schools; and increase the availability of more STEM-related co- and extracurricular experiences available to youth.