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The Importance of Community Colleges in Students' Choice to Major in STEM

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Title: The Importance of Community Colleges in Students' Choice to Major in STEM
Language: English
Authors: Bottia, Martha Cecilia (ORCID 0000-0001-5150-520X), Stearns, Elizabeth (ORCID 0000-0002-9678-2160), Mickelson, Roslyn Arlin (ORCID 0000-0003-2578-0659), Moller, Stephanie (ORCID 0000-0002-8239-719X), Jamil, Cayce
Source: Journal of Higher Education. 2020 91(7):1116-1148.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 33
Publication Date: 2020
Sponsoring Agency: National Science Foundation (NSF)
Contract Number: 1420363
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Two Year Colleges
High Schools
Secondary Education
Descriptors: Community Colleges, College Attendance, Majors (Students), STEM Education, Longitudinal Studies, High School Graduates, State Universities, Undergraduate Students, College Transfer Students, First Generation College Students, Economically Disadvantaged, Socioeconomic Status, Correlation, Graduation Rate, Educational Attainment
Geographic Terms: North Carolina
DOI: 10.1080/00221546.2020.1742032
ISSN: 0022-1546
Abstract: This article investigates whether attending a community college is related to an increase in the number of students majoring and graduating with degrees in science, technology, engineering and mathematics (STEM) at four-year colleges. We follow a longitudinal sample of students in North Carolina from middle school through college graduation, including some who attended a community college. Our multilevel models indicate that for our sample of students, who attended a four-year institution and declared a major within 6 years of high school graduation, ever attending a community college and/or starting post-secondary education at a community college have a significant positive relationship with their likelihood of declaring and graduating with a STEM major. Results hold true even after controlling for sample self-selection through propensity score matching techniques. Our findings also show that the benefits of community college attendance on students' likelihood of declaring and graduating with a STEM major are not restricted to only low-SES students. Overall, this study supports the notion that two-year colleges could work as means of helping push students from diverse socioeconomic backgrounds into STEM.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1271732
Database: ERIC
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  Value: <anid>AN0146366020;jhe01oct.20;2020Oct12.04:45;v2.2.500</anid> <title id="AN0146366020-1">The Importance of Community Colleges in Students' Choice to Major in STEM </title> <p>This article investigates whether attending a community college is related to an increase in the number of students majoring and graduating with degrees in science, technology, engineering and mathematics (STEM) at four‐year colleges. We follow a longitudinal sample of students in North Carolina from middle school through college graduation, including some who attended a community college. Our multilevel models indicate that for our sample of students, who attended a four‐year institution and declared a major within 6 years of high school graduation, ever attending a community college and/or starting post‐secondary education at a community college have a significant positive relationship with their likelihood of declaring and graduating with a STEM major. Results hold true even after controlling for sample self‐selection through propensity score matching techniques. Our findings also show that the benefits of community college attendance on students' likelihood of declaring and graduating with a STEM major are not restricted to only low‐SES students. Overall, this study supports the notion that two‐year colleges could work as means of helping push students from diverse socioeconomic backgrounds into STEM.</p> <p>Keywords: Community college; STEM; socioeconomic status; multilevel models; propensity score matching</p> <hd id="AN0146366020-2">Introduction</hd> <p>Youth from lower socioeconomic (LSES) backgrounds are less likely to attend college or graduate with a bachelor's degree in science, technology, engineering and mathematics (STEM) than peers from more prosperous families. These socioeconomic inequalities in STEM degree attainment are a worrisome reality that has long-lasting consequences for the STEM labor supply (National Science Foundation, [<reflink idref="bib38" id="ref1">38</reflink>]) and for low-income students' chances of upward mobility. While the need for more STEM graduates is clear, strategies to increase the number of STEM graduates and broaden their demographic representativeness are less evident. In this article, we focus on the importance of attending a community college in fostering the choice of a STEM major among students who transfer from community colleges to four-year colleges.</p> <p>The origins of underrepresentation of low-income students in STEM likely emerge from inadequacies in opportunities to learn during their K-12 educations (Xie et al., [<reflink idref="bib62" id="ref2">62</reflink>]). The majority of LSES youth do not have the financial resources to matriculate directly from high school into a four-year college. One possible strategy to overcome these limitations to a four-year college STEM degree is to enroll in a community college, which provides opportunities to students who otherwise might not go to a four-year college (Townsend & Dever, [<reflink idref="bib56" id="ref3">56</reflink>]). First, community colleges operate under a policy of "open admission," whereby anyone with a high school diploma may attend, regardless of prior academic status or college entrance exam scores. Second, they offer academic remediation and supplementary preparation that allow students with deficient preparation to consider a STEM major (Wang, [<reflink idref="bib59" id="ref4">59</reflink>]). Community colleges are important for low-income youth because they cost considerably less than four-year colleges. Additionally, community colleges also provide students with necessary information about the four-year college entrance. In these ways, community colleges serve as crucial gateways into bachelor-level STEM degrees (Malcom & Dowd, [<reflink idref="bib28" id="ref5">28</reflink>]).</p> <p>Community college attendance may have an impact on students' bachelor degree completion (Doyle, [<reflink idref="bib17" id="ref6">17</reflink>]; Wang et al., [<reflink idref="bib60" id="ref7">60</reflink>]). Yet, with the notable exceptions of Wang ([<reflink idref="bib57" id="ref8">57</reflink>]) and Wang et al. ([<reflink idref="bib60" id="ref9">60</reflink>]), there is limited research examining the importance of community college attendance for students' STEM career preparations. To our knowledge, no previous research has looked at the specific importance that community college attendance—in particular, beginning a post-secondary education in a community college compared to directly matriculating from high school to a four-year institution—might have on students' chances of earning four-year college STEM degrees. This research question is important because college type, whether the student first enrolled in a two-year or four-year college, has been recognized as an important factor to consider with respect to STEM degree completion (Perez-Felkner et al., [<reflink idref="bib42" id="ref10">42</reflink>]).</p> <p>This article investigates the relationship between students' community college attendance and the probability of declaring and graduating with a four-year STEM degree. We test whether community college attendance has a positive or negative relationship with students' declaration and graduation with a STEM major once they transfer to four-year institutions. We use multilevel logistic modeling and propensity score matching to examine the likelihood of majoring in STEM and graduating with a STEM degree at a four-year college among different groups of students—those with and without community college experiences. Using a unique population of 2004 North Carolina high school graduates (N = 14,520) who graduated from the University of North Carolina system within six years, we are able to identify if community college attendance contributes to persistence and graduation with a STEM degree and if these effects differ for students from different social class backgrounds.</p> <hd id="AN0146366020-3">Literature review</hd> <p>Previous research shows that LSES students are more likely to receive inferior quality secondary educations, are less likely to enter higher education than their peers from higher income families, and those who attend college are more likely to attend community colleges than four-year schools. Moreover, they have low participation in STEM degree programs (Provasnik & Planty, [<reflink idref="bib45" id="ref11">45</reflink>]).</p> <hd id="AN0146366020-4">Theoretical model</hd> <p>We utilize a rational choice theoretical framework to explain students' choice of major. In this perspective, behaviors and actions, such as college major selection, are influenced by a cost/benefit analysis dependent on students' amount of information. When the benefits of a particular action are strong, individuals will consistently select the perceived best and logical action (Tierney & Venegas, [<reflink idref="bib55" id="ref12">55</reflink>]). When choosing a college major, students weigh information they have about cost, academic rigor, future salaries, and their own academic abilities to determine what major to choose (Wang et al., [<reflink idref="bib60" id="ref13">60</reflink>]). Students utilize all available information about their academic potential to determine whether the probability of graduating is high enough to merit the risk (Hilmer, [<reflink idref="bib23" id="ref14">23</reflink>]). This model considers students as actors who attempt to make the best educational choices in the light of the expected costs and benefits of the available options they perceive.</p> <p>Our study's conceptual framework also utilizes sociological theories that focus on the structural roots of inequality, especially prior school contexts and learning opportunities offered to youth from different backgrounds. We consider differences arising from students' SES, and the interplay between structural and individual factors. We draw on the theory of cumulative disadvantage, which proposes that an individual initially exposed to disadvantages will accumulate further disadvantages from continued exposure over time, magnifying small differences and making it difficult for individuals or groups that are "behind" at one point in time to catch up. In the case of learning, initial small differences grow larger over time because progression from each step to the next depends on attainment of satisfactory performance in the previous step and produce further relative detriments (DiPrete & Eirich, [<reflink idref="bib16" id="ref15">16</reflink>]; Merton, [<reflink idref="bib30" id="ref16">30</reflink>]). We apply the cumulative disadvantage perspective by examining the succession of educational events, starting in middle school and continuing through college, that collectively build upon each other to affect students' participation in STEM fields.</p> <hd id="AN0146366020-5">Low-SES students and choosing a college major</hd> <p>For many students, choosing a major is the first important college decision for which they are fully responsible. This decision is important because it has implications for family ties, friendships, and vocational and career plans (Galotti & Mark, [<reflink idref="bib20" id="ref17">20</reflink>]). Previous research shows that socioeconomic background, gender, parental education, academic ability, costs of post-secondary education and expected earnings are important factors in the college major choice process (Montmarquette et al., [<reflink idref="bib34" id="ref18">34</reflink>]). Given that lower SES students often have limited access to sources of information when choosing a major, they rely more on school–based academic information (Cabrera & La Nasa, [<reflink idref="bib12" id="ref19">12</reflink>]). Unfortunately, lower SES students usually learn in K-12 contexts where the quality of teachers and counselors is weaker, educational resources are scarcer, and peers have less educated parents. Consequently, often lower SES students are unaware of how the college admissions process works, do not have knowledge of the academic requirements for going to college, and are not aware of the availability of financial aid options (Perna, [<reflink idref="bib43" id="ref20">43</reflink>]).</p> <p>Parental educational attainment is the strongest predictive factor in the college selection process for many reasons (Cabrera & La Nasa, [<reflink idref="bib12" id="ref21">12</reflink>]). Students who come from LSES backgrounds are more likely to have parents with less formal education and fewer economic resources. LSES parents provide their children with less of the cultural, social, and financial capital that facilitate college enrollment (Bourdieu, [<reflink idref="bib10" id="ref22">10</reflink>]; Erola et al., [<reflink idref="bib19" id="ref23">19</reflink>]; Perna & Titus, [<reflink idref="bib44" id="ref24">44</reflink>]). Parents with lower levels of education tend to be less involved in the educational trajectories of their children. But individuals coming from working-class cultural backgrounds typically possess norms that embrace interdependence on family and community rather than norms of independence (Stephens et al., [<reflink idref="bib54" id="ref25">54</reflink>]). Furthermore, students whose parents had some college experience tend to begin the college preparation process earlier and to rely less heavily on guidance counselors compared to peers with parents who have no college education (Stanton-Salazar, [<reflink idref="bib50" id="ref26">50</reflink>]).</p> <p>Prior research links socioeconomic gaps in student performance to structural inequalities present in the system of formal education (Mickelson, [<reflink idref="bib31" id="ref27">31</reflink>]). For example, lower SES students suffer a larger learning loss during the summer given that they have fewer educational resources within their homes and fewer opportunities available in their communities to help them reinforce and advance their academic skills (Alexander, Entwisle & Olson, [<reflink idref="bib1" id="ref28">1</reflink>]). Additionally, LSES students are typically tracked into general rather than college-preparatory math courses in high school, with lower levels of achievement growth compared to youth in college-preparatory classes (Oakes, [<reflink idref="bib39" id="ref29">39</reflink>]). All of these circumstances often result in LSES students receiving inferior academic preparation and less information for navigating the college major selection process. Thus, for LSES youth, the decision to choose a STEM major may appear to have higher costs.</p> <hd id="AN0146366020-6">Choosing a STEM major</hd> <p>Prior academic achievement, school contexts, interest in STEM during high school, a strong sense of self-efficacy and positive initial postsecondary experiences, such as academic interaction with peers and receipt of financial aid, are among the factors most commonly cited as predictive of likely participation in STEM (Bottia et al., [<reflink idref="bib8" id="ref30">8</reflink>], [<reflink idref="bib7" id="ref31">7</reflink>]; Chang et al., [<reflink idref="bib13" id="ref32">13</reflink>]). For example, high school math achievement is widely recognized as a strong antecedent to STEM participation. Students who take higher-level math classes and score well on standardized math exams are routinely found to have strong likelihoods of entering into and graduating in STEM (Engberg & Wolniak, [<reflink idref="bib18" id="ref33">18</reflink>]; Ma, [<reflink idref="bib27" id="ref34">27</reflink>]; Maltese & Tai, [<reflink idref="bib29" id="ref35">29</reflink>]; Wang, [<reflink idref="bib58" id="ref36">58</reflink>]; Xie et al., [<reflink idref="bib62" id="ref37">62</reflink>]). Similarly, taking physics during high school is a strong predictor of students' participation in STEM (Bottia et al., [<reflink idref="bib8" id="ref38">8</reflink>]).</p> <p>Other key contributing factors for a STEM major are a keen interest in science or math. An interest in science or math can be nurtured by peers, teachers, or parents. Indeed, the majority of students who major in STEM made that choice while in high school (Maltese & Tai, [<reflink idref="bib29" id="ref39">29</reflink>]). Such timing highlights the influence that high school contexts have on students' likelihood of enrolling in a STEM major. Studies also find that the gender composition of the high school STEM faculty and racial composition of peer groups are forces that influence students' odds of going into STEM (Bottia et al., [<reflink idref="bib9" id="ref40">9</reflink>], [<reflink idref="bib7" id="ref41">7</reflink>]). However, many LSES students achieve lower math and science grades and are exposed to fewer formal or informal opportunities to learn about STEM. Thus, they have fewer chances to develop a STEM interest and prepare for pursuing it in college.</p> <p>Furthermore, high school- and college-level characteristics have also been identified as relevant to students' choice of major. Secondary schools provide students with crucial opportunities to learn. High school is where the majority of the students receive most of their academic preparation and exposure to many inspirational factors that can channel youth toward a STEM pathway (Bottia et al., [<reflink idref="bib8" id="ref42">8</reflink>]; Maltese & Tai, [<reflink idref="bib29" id="ref43">29</reflink>]). Characteristics of the high schools, teaching staff and peers who attend the school are crucial for students' college and/or career choices (Bottia et al. [<reflink idref="bib9" id="ref44">9</reflink>], [<reflink idref="bib7" id="ref45">7</reflink>]; Stearns et al., [<reflink idref="bib51" id="ref46">51</reflink>]). The quality of schools attended by LSES youth tends to be significantly different when compared to schools of higher SES students. Students who attend schools with a higher SES composition tend to be exposed to more rigorous classes, have higher-quality teachers, better infrastructures, higher ability peers, and more enriching opportunities to engage in activities that will amplify their interests in STEM (Mickelson et al., [<reflink idref="bib32" id="ref47">32</reflink>]; Reardon, [<reflink idref="bib47" id="ref48">47</reflink>]).</p> <p>College organizational features also have been identified as having significant effects on STEM degree attainment (Zhang et al., [<reflink idref="bib63" id="ref49">63</reflink>]). Several characteristics of post-secondary institutions are related to students' educational outcomes such as career choice (Weidman, [<reflink idref="bib61" id="ref50">61</reflink>]).</p> <hd id="AN0146366020-7">Community college and choosing STEM</hd> <p>Community colleges are increasingly becoming an important pathway to STEM degrees (Bahr et al., [<reflink idref="bib4" id="ref51">4</reflink>]). Fifty percent of the science, engineering and health graduates between 2001 and 2007 report having attended community college at some point in their studies (National Science Foundation, [<reflink idref="bib38" id="ref52">38</reflink>]). Community colleges provide college opportunities to students who otherwise might not go to college because of their difficulties paying higher four-year college's tuition, their lower levels of academic preparation, and their lack of information on how four-year colleges operate. Additionally, some students enrolled in four-year colleges simultaneously enroll in a community college in order to inexpensively earn credits toward their bachelor's degree or gain skills in certain occupational fields (Mooney & Foley, [<reflink idref="bib35" id="ref53">35</reflink>]).</p> <p>Timing variations could influence the relationship between attending a community college and students' STEM trajectories. Students attend community colleges at different times in their academic careers. Some students start their post-secondary academic life at a community college; others take a few community college credits before graduating from high school or earning a high school equivalency certificate; some youth earn community college credits toward their bachelor's degree while enrolled in a four-year college; and after leaving a four-year college or university, certain students enroll in a two-year school (Mooney & Foley, [<reflink idref="bib35" id="ref54">35</reflink>]). Given community colleges' potential for remediating students' inadequate academic preparation, offering additional information on the four-year college process, the majors available, and their capacity to provide education to individuals at a lower cost, community colleges may offer a four-year college STEM pathways for some students.</p> <p>A considerable amount of prior research has explored the relationships between attending community college and participation in STEM disciplines. Some prior research evaluates the impact of community college-based interventions such as coaching, supplemental instruction, or summer research experiences specifically designed to increase students' persistence in STEM (Amelink et al., [<reflink idref="bib2" id="ref55">2</reflink>]). Other studies focus on how the relationship between student characteristics and community college experiences influences students' STEM trajectories (Engberg & Wolniak, [<reflink idref="bib18" id="ref56">18</reflink>]; LaSota & Zumeta, [<reflink idref="bib24" id="ref57">24</reflink>]; Wang, [<reflink idref="bib57" id="ref58">57</reflink>]; Wang, [<reflink idref="bib59" id="ref59">59</reflink>]). A smaller portion of the prior research linking community college attendance with STEM college outcomes examines the roles of socioeconomic status, race, parental involvement, social capital, cultural capital and financial capital on students' paths toward STEM (Perna & Titus, [<reflink idref="bib44" id="ref60">44</reflink>]).</p> <p>Scholars debating the impact of community colleges in the larger landscape of higher education find that either they contribute to educational opportunity by creating pathways to the baccalaureate or that they detract from such opportunity by "cooling students" out of higher education goals (Clark, [<reflink idref="bib14" id="ref61">14</reflink>]). LaSota and Zumeta ([<reflink idref="bib24" id="ref62">24</reflink>]) find that individuals who start their post-secondary careers at two-year colleges are less likely to graduate with four-year degrees compared to students who start at four-year colleges, while Wang ([<reflink idref="bib59" id="ref63">59</reflink>]) shows that community colleges have the potential to effectively assist some disadvantaged students in their degree pursuits. In a recent study, Wang et al. ([<reflink idref="bib60" id="ref64">60</reflink>]) conclude that community college attendance does not limit access to graduate and professional education and can complement traditional routes to graduate and professional school. Thus, two-year colleges, while not a reliable pathway to STEM for all students, appear to have the potential to aid some academically disadvantaged students by providing necessary academic remediation, guidance, and support.</p> <p>Given that approximately 50% of science and engineering degree recipients attend community college (National Science Board, [<reflink idref="bib37" id="ref65">37</reflink>]), our study sheds light on the relationship of community colleges with the probability of declaring a STEM major and/or graduating with a STEM degree at a four-year college institution. We attempt to identify the characteristics of the 50% who obtain their four-year degree after transferring from a community college. We frame our investigation within the rational choice perspective where individuals do or do not choose STEM majors after they consider costs and benefits of the choice. Community college attendance might offer opportunities that directly and indirectly influence students' choice of major at a four-year college. For example, attending a community college may provide low-cost additional academic preparation and important information and cultural capital necessary for students to choose STEM as a major at a four-year college. Our first hypothesis, thus, is</p> <p> <bold>H<subs>1</subs></bold>: Students who attended a community college are more likely to declare a STEM major at a four-year university than students who never attended a community college.</p> <p>Framed with cumulative disadvantage theories that look at how initial inequalities grow stronger over the lifetime of a cohort, we expect that the chances of choosing a STEM major for lower SES students (who are more likely to have lower levels of academic preparation, lower levels of cultural capital, and less access to financial resources to pay for a four-year college education) are differentially affected by attending community college compared with students from more prosperous families. Our second hypothesis is</p> <p> <bold>H<subs>2</subs></bold>: The relationship between attending community college and declaring a STEM major at a four-year institution varies depending on students 'socioeconomic status.</p> <hd id="AN0146366020-8">Data, variables and methods</hd> <p></p> <hd id="AN0146366020-9">Data</hd> <p>We analyze the North Carolina (NC) Roots of STEM Success dataset (Stearns et al., [<reflink idref="bib52" id="ref66">52</reflink>]) to test our hypotheses. It contains longitudinal information on the academic performance and scholastic experiences of all 2004 North Carolina public school graduates. The analytic sample for this article includes two groups of undergraduates: students who matriculated directly from a NC high school to one of the 16 campuses of the University of North Carolina (UNC) system and those who transferred credits from a North Carolina community college to one of the 16 UNC system campuses. Data include student, family, school, and achievement indicators from seventh grade through college graduation obtained from administrative records. Additionally, the Roots dataset contains information about the characteristics of the secondary schools, two- and the four-year colleges that students attended throughout their educational careers. By utilizing data from secondary school years, we are able to look at the pathways students traversed to declaration of a STEM major, which according to Pearson and Miller ([<reflink idref="bib41" id="ref67">41</reflink>], p. 57), is a process that "begin[s] early and require[s] navigation through a series of educational gateways."</p> <p>We focus on a racially and socioeconomically diverse sample of 19,640 four-year college-bound women and men who attended approximately 350 high schools in North Carolina and graduated in 2004, attended any of the 16 University of North Carolina colleges between 2004 and 2011, and declared a major. A little over 21% of our sample attended 1 of 58 community colleges in North Carolina. Our analytic sample decreases to 14,520 students who attended 317 high schools in North Carolina due to missing data, primarily socioeconomic status and previous achievement indicators (See Appendix A). Our sample is representative of North Carolina's student population that has attended a four-year college and has ever declared a major and/or graduated with a STEM major within six years of high school graduation. Findings about community college attendance apply only to North Carolina high school graduates who earned credits at two-year colleges and transferred to four-year colleges where they declared a major.</p> <hd id="AN0146366020-10">Variables</hd> <p>We chose dependent and independent variables based on our conceptual framework and central questions regarding community college attendance and STEM major choice. In our analysis we use binary measures of student major choices. To define a STEM major, we use the categorization utilized by the National Science Foundation Advance Program where majors such as engineering, physical sciences, earth, atmospheric or ocean sciences, mathematical and computer sciences, and biological and agricultural sciences are considered to be within the STEM category. We exclude social sciences from our STEM category in this analysis. Importantly, our dependent variable follows student major declaration and graduation up to 6 years after high school graduation. In this way, our dependent variables are able to measure major declaration and major graduation of the most academically successful community college transfer students at a four-year college.</p> <p>Our key independent variable of interest is community college attendance. We utilize two different variables to measure attendance because we are aware that there are multiple ways undergraduates utilize community colleges in the pursuit of their bachelor's degrees. The first category of attendance, <emph>ever attended community college</emph>, indicates the student transferred community college credits to a four-year university. The second category, <emph>started post-secondary education at a community college</emph>, signifies that the first post-secondary institution the student attended was a community college. This group is the subset of students within the <emph>ever attended a community college</emph> category that started their post-secondary education at a two-year school. By employing two categories of previous community college attendance we are able to capture whether one or both forms of attendance influence students' STEM major declaration at a four-year college.</p> <p>Our models include a variety of both individual-and school-level control variables that could influence students' rational choice of college major and could capture any cumulative disadvantages students experience.</p> <p>Individual-Level Variables: Our models include student demographic and family characteristics such as race/ethnicity (White is reference category), gender, and family socioeconomic status. We operationalize family SES as the combination of whether the person is a first-generation college student and whether the student received free/reduced lunch during middle school. We created four categories that operationalize the possible combinations of the two measures described above: (a) students who are not first-generation college students and did not receive free/reduced lunch (79.2% of the sample), (b) students who are not first-generation college students but received free/reduced lunch (8.4%), (c) first-generation college students who did not receive free/reduced lunch (8.6%), and (d) first-generation college students who received free/reduced lunch (3.8%) (reference category). We decided to account for both students' lack of financial resources via their free/reduced lunch status and students' lack of social and cultural capital via their first-generation college status, because both are important determinants of college attendance, adjustment and persistence (Moschetti & Hudley, [<reflink idref="bib36" id="ref68">36</reflink>]). In fact, low income and first-generation students may lack basic knowledge about college, including degree expectations and planning, expenses and funding, and career preparation (Pascarella et al., [<reflink idref="bib40" id="ref69">40</reflink>]), placing them at risk for poor adjustment and persistence in college.</p> <p>Drawing on factors identified in previous research as important in predicting STEM participation, we also included variables related to academic preparation: if the student took physics in high school, Grade 10 English standardized test score, Grade 8 math and reading standardized test score, and high school GPA. Additionally, another important control variable that we utilize is whether a student had an intent to declare a STEM major in his or her high school senior year. STEM major intention is a dichotomous variable that comes from a question asked on the SAT questionnaire in 2003–2004, in which students indicated the major or area of study that most interested them, followed by their other choices. Students who reported on their SAT questionnaire that they intended to major in agriculture and natural sciences, biological sciences, computer and information science technology, engineering and engineering technician studies, mathematics and/or physical sciences were categorized as students intending to major in STEM.</p> <p>High School-Level Variables: Certain variables capture important high school organization characteristics that previous research associates with students' interest in STEM and could also correlate with our primary independent variables and the probability of declaring and/or graduating with a STEM degree (Borman et al., [<reflink idref="bib6" id="ref70">6</reflink>]; Bottia et al., [<reflink idref="bib8" id="ref71">8</reflink>], [<reflink idref="bib7" id="ref72">7</reflink>]; Hanushek et al., [<reflink idref="bib22" id="ref73">22</reflink>]; Lleras, [<reflink idref="bib26" id="ref74">26</reflink>]). These variables include racial composition of the high school attended (measured as proportion of White students); proportion of female students in the school; proportion of experienced teachers at the school (those with more than 10 years of experience); proportion of licensed teachers; proportion of teachers with advanced degrees; and school's average total SAT score.</p> <p>College-Level Variables: Because organizational characteristics and social climates of four-year colleges also influence students' choice of major (Bettinger & Long, [<reflink idref="bib5" id="ref75">5</reflink>]), we include a control for the type of college campus attended (if students attended a historically black college or if they attended North Carolina State University (a STEM-focused university). Lastly, we included a four-year college characteristic associated with STEM outcomes—the gender composition of the STEM faculty operationalized as percent female.</p> <hd id="AN0146366020-11">Empirical strategies</hd> <p></p> <hd id="AN0146366020-12">Multilevel modeling</hd> <p>The main analytical approach we use to test our hypotheses is multilevel modeling. This strategy takes into consideration the fact that certain groups of students attended the same high schools and the same colleges. Individual error terms in nested data like the Roots of STEM dataset typically have correlated errors among individuals at the same high school and individuals at the same college (Raudenbush & Bryk, [<reflink idref="bib46" id="ref76">46</reflink>]). Our multilevel binomial logistic models (Grilli & Rampichini, [<reflink idref="bib21" id="ref77">21</reflink>]) estimate the probability students chose STEM majors, correcting for random effects. We estimate the models using secondary school-level and four-year college-level variables centered at the grand mean. Importantly, in the multilevel models, we assume that students' community college attendance is exogenous to students' major declaration/graduation.</p> <hd id="AN0146366020-13">Propensity Score Matching (PSM) procedures</hd> <p>It could be the case that students who attended community colleges differ from students who did not in critical unobserved ways that relate to majoring and/or graduating with a STEM major at a four-year college. Demographic characteristics, parents' cultural and social capital, if a student had intent to declare a STEM major in his or her high school senior year, secondary school academic preparation, and prior achievement might be among the differences that could make it misleading to simply compare all students who attended a community college with all of those that did not attend a community college. Because we are dealing with students who were nested within high schools before they attended a community college (and specific characteristics about their high schools might have had an influence on the selection of attending community college), we calculate propensity scores by using multi-level logistic models.</p> <p>We utilize PSM techniques to more strictly evaluate the relationship between community college attendance and STEM-related college outcomes because selection into "attending a community college" might lead to different baseline covariates and potential outcomes (Steiner & Cook, [<reflink idref="bib53" id="ref78">53</reflink>]). PSM techniques have been used previously to purge bias from the estimates of the effect of attendance at a certain type of school (Reardon et al., [<reflink idref="bib48" id="ref79">48</reflink>]) and to predict the impact of having attended a community college on access to graduate and professional schools (Wang et al., [<reflink idref="bib60" id="ref80">60</reflink>]). They have not been utilized to specifically assess the impact of community colleges on future STEM pathways. In this study, we use multi-level PSM to adjust for a number of pretreatment predictors of students' probability of enrolling in a community college to assess if the impact exists.</p> <p>The PSM balances the differences between the treatment and the control groups based on a group of control student characteristics and then estimates the treatment effect. Because PSM reduces the bias in estimates due to differences in observables, it then provides a more accurate inference about any possible treatment effect that might exist (Shadish et al., [<reflink idref="bib49" id="ref81">49</reflink>]). Therefore, if certain balancing conditions are met, we can argue that PSM methods allow us to make causal inferences about the effect of a treatment. In summary, the PSM technique simulates a counterfactual as we compare two groups of students who are similar in many relevant characteristics except for their community college attendance. We then estimate treatment effects. PSM creates a single-number summary of the propensity of attending a community college generated by estimating a multi-level logistic regression in which the dichotomous dependent variable takes a value of 1 if the subject received the treatment and 0 if it did not, and the independent variables consist of all relevant measured characteristics for individuals in the sample (Monaghan & Attewell, [<reflink idref="bib33" id="ref82">33</reflink>]).</p> <p>After obtaining the propensity score using multi-level logistic regression, we examined the balancing properties and common support of the treatment and control groups to ensure a correct specification of the PSM estimation model (See Appendix B). To then select the matched individuals for the comparison analysis we used nearest neighbor matching n (<reflink idref="bib1" id="ref83">1</reflink>) with replacement algorithm and the statistical STATA procedure called "psmatch2." To ensure that we achieved satisfactory internal validity in our PSM method, we only produced estimates with cases in the region of common support. When generating matched samples, we mainly focused on how well the groups were matched in terms of the covariates included in the propensity-score model.</p> <hd id="AN0146366020-14">Results</hd> <p>Table 1 shows comparisons across our sample by both community college attendance status and by socioeconomic status. There are substantial differences in the sample by both factors, with community college students and lower SES students both showing lower levels of academic achievement.</p> <p>Table 1. Descriptive statistics of key variables, by community college attendance and by socioeconomic status.</p> <p> <ephtml> <table><thead><tr><td /><td>By Community College Attendance</td><td>By Socioeconomic Status</td></tr><tr><td /><td>Attended CC (n = 3,110)</td><td>Did not attend CC (n = 11,410)</td><td>Started at CC (n = 1,510)</td><td>Higher SES (No FRL & No FGC) (n = 11,490)</td><td><bold>Entire Sample included in analysis (n = 14,520)</bold></td><td>Lower SES (n = 3,030)</td></tr><tr><td>Variable</td><td>Mean</td><td /><td>Mean</td><td /><td>Mean</td><td>Mean</td><td /><td>Mean</td><td /><td>Mean</td></tr></thead><tbody><tr><td>Declared a STEM Major</td><td>0.181</td><td>***</td><td>0.229</td><td /><td>0.217</td><td>0.228</td><td>*</td><td>0.219</td><td>***</td><td>0.181</td></tr><tr><td>Graduated with a STEM Major(a)</td><td>0.136</td><td>***</td><td>0.203</td><td>***</td><td>0.160</td><td>0.199</td><td>*</td><td>0.189</td><td>***</td><td>0.148</td></tr><tr><td>Intention to Major in STEM (b)</td><td>0.351</td><td>***</td><td>0.395</td><td /><td>0.367</td><td>0.396</td><td /><td>0.386</td><td>***</td><td>0.354</td></tr><tr><td>Student is Male</td><td>0.420</td><td /><td>0.429</td><td>***</td><td>0.489</td><td>0.440</td><td>**</td><td>0.427</td><td>***</td><td>0.376</td></tr><tr><td>Black</td><td>0.165</td><td>***</td><td>0.232</td><td>***</td><td>0.123</td><td>0.147</td><td>***</td><td>0.218</td><td>***</td><td>0.486</td></tr><tr><td>Hispanic</td><td>0.012</td><td /><td>0.011</td><td /><td>0.014</td><td>0.007</td><td>***</td><td>0.011</td><td>***</td><td>0.027</td></tr><tr><td>Asian</td><td>0.023</td><td>***</td><td>0.033</td><td /><td>0.026</td><td>0.025</td><td>***</td><td>0.031</td><td>***</td><td>0.054</td></tr><tr><td>AI</td><td>0.011</td><td>**</td><td>0.007</td><td>*</td><td>0.004</td><td>0.006</td><td>**</td><td>0.008</td><td>***</td><td>0.017</td></tr><tr><td>Other</td><td>0.005</td><td /><td>0.004</td><td>***</td><td>0.005</td><td>0.004</td><td /><td>0.004</td><td /><td>0.006</td></tr><tr><td>White</td><td>0.786</td><td>***</td><td>0.713</td><td>***</td><td>0.829</td><td>0.812</td><td>***</td><td>0.728</td><td>***</td><td>0.411</td></tr><tr><td>No FRL & Not FGC</td><td>0.754</td><td>***</td><td>0.802</td><td>***</td><td>0.733</td><td>1.000</td><td /><td>0.792</td><td /><td>0.000</td></tr><tr><td>FRL & Not FGC</td><td>0.079</td><td /><td>0.085</td><td>**</td><td>0.069</td><td>0.000</td><td /><td>0.084</td><td>***</td><td>0.447</td></tr><tr><td>No FRL & FGC</td><td>0.126</td><td>***</td><td>0.076</td><td>***</td><td>0.152</td><td>0.000</td><td /><td>0.086</td><td>***</td><td>0.164</td></tr><tr><td>FRL & FGC</td><td>0.041</td><td /><td>0.037</td><td /><td>0.046</td><td>0.000</td><td /><td>0.038</td><td>***</td><td>0.389</td></tr><tr><td>Math EOG</td><td>176.716</td><td>***</td><td>180.049</td><td>***</td><td>175.333</td><td>180.387</td><td>***</td><td>179.335</td><td>***</td><td>175.339</td></tr><tr><td>High School GPA</td><td>333.713</td><td>***</td><td>373.316</td><td>***</td><td>313.617</td><td>371.782</td><td>***</td><td>364.832</td><td>***</td><td>338.426</td></tr><tr><td>Took Physics in High School</td><td>0.164</td><td>***</td><td>0.299</td><td>***</td><td>0.132</td><td>0.293</td><td>***</td><td>0.270</td><td>***</td><td>0.185</td></tr><tr><td>English EOC</td><td>59.846</td><td>***</td><td>62.514</td><td>***</td><td>58.775</td><td>62.730</td><td>***</td><td>61.943</td><td>***</td><td>58.951</td></tr><tr><td>% Teachers with Advanced Degrees</td><td>0.263</td><td>***</td><td>0.276</td><td>***</td><td>0.267</td><td>0.281</td><td>***</td><td>0.273</td><td>***</td><td>0.243</td></tr><tr><td>% Peers who are White</td><td>0.686</td><td>***</td><td>0.647</td><td>***</td><td>0.718</td><td>0.678</td><td>***</td><td>0.656</td><td>***</td><td>0.571</td></tr><tr><td>% Teachers with +5 years of Experience</td><td>0.567</td><td>***</td><td>0.543</td><td>***</td><td>0.568</td><td>0.548</td><td /><td>0.548</td><td /><td>0.549</td></tr><tr><td>% Teachers with License</td><td>0.826</td><td>***</td><td>0.821</td><td>***</td><td>0.831</td><td>0.828</td><td>***</td><td>0.822</td><td>***</td><td>0.799</td></tr><tr><td>Proportion Peer Female Students</td><td>0.495</td><td /><td>0.495</td><td /><td>0.494</td><td>0.494</td><td>*</td><td>0.495</td><td>***</td><td>0.496</td></tr><tr><td>Average SAT Total at HS</td><td>986.297</td><td>***</td><td>1000.412</td><td>***</td><td>991.509</td><td>1007.880</td><td>***</td><td>997.388</td><td>***</td><td>957.531</td></tr><tr><td>Ever Attended CC</td><td>1.000</td><td /><td>0.000</td><td /><td>1.000</td><td>0.204</td><td>**</td><td>0.214</td><td>***</td><td>0.253</td></tr><tr><td>Student Started at CC</td><td>0.485</td><td>***</td><td>0.000</td><td /><td>1.000</td><td>0.096</td><td>**</td><td>0.104</td><td>***</td><td>0.133</td></tr><tr><td>Attended NCSU</td><td>0.051</td><td>***</td><td>0.181</td><td>***</td><td>0.066</td><td>0.173</td><td>**</td><td>0.153</td><td>***</td><td>0.080</td></tr><tr><td>Percent Female Professors Teaching STEM</td><td>30.923</td><td>***</td><td>29.441</td><td>***</td><td>32.197</td><td>29.663</td><td /><td>29.758</td><td /><td>30.119</td></tr><tr><td>Attended Historically Black College</td><td>0.111</td><td>***</td><td>0.147</td><td>***</td><td>0.099</td><td>0.086</td><td>***</td><td>0.140</td><td>***</td><td>0.345</td></tr></tbody></table> </ephtml> </p> <p>1 Asterisks represent significant differences in means ***<emph>p</emph> <.001, **<emph>p</emph> <.05 and *<emph>p</emph> <.90.</p> <p>2 (a) <emph>n</emph> is smaller for graduated with a STEM major 12,160, (b) <emph>n</emph> is smaller for intent to major in STEM 9,760.</p> <hd id="AN0146366020-15">Descriptive analysis</hd> <p>There are some important differences in the means between students who attended community colleges (including those who started at community colleges) and students who did not attend community colleges that might influence students' rational choice of major in a four-year college. Table 1 shows that the percent of students who declare a STEM major is statistically significantly higher for students who never attended community college (23%) compared to those who <emph>ever attended</emph> community college (18%). Nevertheless, Table 1 also shows that the sample of students who <emph>started post-secondary education</emph> at a community college do not have statistically different percentages of students majoring in STEM fields. Table 1 also shows that there is a significantly higher percentage of students who graduate with a STEM degree (20.3%) for the sample of students who never attended community college versus those who ever attended community college (13.6%), and those who started their post-secondary education at a community college (16%).</p> <p>From Table 1, we also see that enrollment in community college is related to students' previous academic level of preparation. Specifically, students who attended community college—and especially those who started their post-secondary education at a community college—have significantly lower levels of academic preparation than students who begin their post-secondary education at four-year universities. They have significantly lower high school GPAs, lower math achievement scores, and were enrolled in significantly lower proportions in physics when in high school. These results suggest that community colleges attract students who are less academically prepared. Additionally, the percentages of White students in the sample of students who ever attended community colleges (79%) and in those who started their post-secondary education at a community college (83%) are significantly higher than those who never attended a community college (71%).</p> <p>Table 1 also shows that the proportion of students who are first-generation college but did not receive free/reduced lunch are significantly larger in the sample of students who ever attended community college (12.6%) and those who started at a community college (15.2%), compared to those who never attended a community college (8.7%). These results suggest that first-generation college students that are not low income attended community college in higher proportions and may therefore have less cultural capital and likely have less familiarity with navigating the higher educational system. In summary, the results of this descriptive analysis illustrate substantial preexisting differences between students who attended CC compared to those who did not, which is the main motivation for using matching techniques. In the following sections, the results of multilevel logit models followed by PSM are described.</p> <p>The unequal socioeconomic distribution of STEM majors is apparent in the UNC system. Table 1 (by SES) presents means for variables for three different groups of students: the entire sample of students included in our analysis, LSES students, and high SES students. Asterisks indicate significant differences in means across the adjacent groups after a t-test statistical analysis. For the 2004 HS graduating cohort, 21.9% of the students declared a STEM major and 18.9% graduated with a STEM major. These percentages are lower among LSES students (18.1% and 14.8%, respectively) and significantly higher for students from higher SES backgrounds (22.8% and 19.9%, respectively). Results in Table 1 show that LSES students enroll and graduate less in STEM majors compared to high SES students. Notably, in 12th grade, students from different socioeconomic backgrounds report significantly different interests in pursuing a STEM major when in high school. While 38.6% of all students identified an interest in pursuing a STEM major, 35.4% of LSES students expressed an interest. This compares to 39.6% of high SES students who did so.</p> <p>Table 1 also provides evidence of the lower levels of academic preparation, lower quality of high school learning contexts, and lower levels of parental education among LSES undergraduates. For example, they have significantly lower levels of secondary mathematics and English achievement (EOC scores), and significantly lower high school GPAs than both the general sample of students and high SES students. Regarding high school contexts, Table 1 shows that LSES students attended high schools with lower percentages of teachers with advanced degrees and licenses, and with significantly lower mean high school-level SAT scores. Lastly, Table 1 illustrates that rates of community college enrollment are different for students from lower SES and higher SES backgrounds. While 25.3% of LSES students in our sample <emph>ever</emph> attended community college, 20.4% of the high SES students <emph>ever</emph> attended community college. Additionally, the percentage of students who start a post-secondary education at a community college is significantly higher for LSES students (13.3%) compared to students from high SES backgrounds (9.6%). All of these differences could have an important impact on students' rational choice of what major to follow when attending a four-year college.</p> <hd id="AN0146366020-16">Multilevel models' results</hd> <p>Table 2 presents results of multilevel logistic models nesting students in high schools and four-year college campuses attended. Models 1 to 8 in Table 2 present students' odds ratios of declaring and graduating with a STEM major at a four-year college and their significance levels. Models 1, 3, 5 and 7 include students' intent to major in STEM, while Models 2, 4, 6 and 8 do not include intent to major in STEM as a control. Models present results for different sets of variables predicting students' odds ratios of declaring a STEM major and graduating with a STEM major at a four-year college and measures the effects of a student having <emph>ever attended a community college</emph> or if students <emph>started</emph> their post-secondary education at a community college or not.</p> <p>Table 2. Differences in STEM declaration and STEM graduation by community college attendance—multilevel binomial models.</p> <p> <ephtml> <table><thead><tr><td /><td><bold>Model 1</bold>. DECLARE STEM (controlling for intent to major in STEM) (<italic>n</italic> = 9,760)</td><td><bold>Model 2</bold>. DECLARE STEM (<italic>n</italic> = 14,520)</td><td><bold>Model 3</bold>. GRADUATE STEM (controlling for intent to major in STEM) (<italic>n</italic> = 8,210)</td><td><bold>Model 4</bold>. GRADUATE STEM (<italic>n</italic> = 9,990)</td><td /><td><bold>Model 5</bold>. DECLARE STEM (controlling for intent to major in STEM) (<italic>n</italic> = 9,760)</td><td><bold>Model 6</bold>. DECLARE STEM (<italic>n</italic> = 14,520)</td><td><bold>Model 7</bold>. GRADUATE STEM (controlling for intent to major in STEM) (<italic>n</italic> = 8,210)</td><td><bold>Model 8</bold>. GRADUATE STEM (<italic>n</italic> = 9,990)</td></tr><tr><td /><td>Odds ratio</td><td>Sig.</td><td>Odds ratio</td><td>Sig.</td><td>Odds Ratio</td><td>Sig.</td><td>Odds ratio</td><td>Sig.</td><td /><td>Odds ratio</td><td>Sig.</td><td>Odds ratio</td><td>Sig.</td><td>Odds ratio</td><td>Sig.</td><td>Odds ratio</td><td>Sig.</td></tr></thead><tbody><tr><td>Ever Attended CC</td><td>1.409</td><td>***</td><td>1.465</td><td>***</td><td>1.100</td><td /><td>1.256</td><td>***</td><td>Started at CC</td><td>2.427</td><td>***</td><td>2.432</td><td>***</td><td>2.080</td><td>***</td><td>2.125</td><td>***</td></tr><tr><td /><td>0.078</td><td /><td>0.062</td><td /><td>0.095</td><td /><td>0.076</td><td /><td /><td>0.104</td><td /><td>0.080</td><td /><td>0.129</td><td /><td>0.100</td><td /></tr><tr><td>AIC (smaller is better)</td><td>8214.71</td><td /><td>12,878.73</td><td /><td>6237.90</td><td /><td>9831.80</td><td /><td>AIC</td><td>8167.30</td><td /><td>12,800.58</td><td /><td>6212.83</td><td /><td>9788.28</td><td /></tr></tbody></table> </ephtml> </p> <ulist> <item>3 ***<emph>p</emph> <.001, **<emph>p</emph> <.05 and *<emph>p</emph> <.90.</item> <item>4 The control variables used include male, race, SES (free/reduced lunch and first-generation college status), math EOG, high school GPA, took physics in high school, English EOC, attended North Carolina State University, attended Historically Black College, Percent Female Professors Teaching STEM at a four-year college, percent of teachers with advanced degrees at high school, percent of students who were White at HS, percent of experienced teachers at HS, percent of licensed teachers at HS, percent of female students at HS, average SAT Score at the school.</item> </ulist> <p>Findings in Table 2 (Models 1 through 4) show that there is a significant positive relationship between having <emph>ever attended a community college</emph> and students' odds ratio of declaring and graduating with a STEM major at a four-year college. Figure 1 shows the predicted probabilities of declaring a STEM major and graduating with a STEM major at a four-year college for students who attended and those who never attended a community college, based on the results from Models 2 and 4 (models not controlling for intent to major in STEM that have larger sample of students). While students who attended community college have a 27% predicted probability of declaring a STEM major when at a four-year college, students who did not attend community college have a significantly lower predicted probability of 20%. In addition, students who attended a community college have a 19% predicted probability of graduating with a STEM major at a four-year college, compared to a 16% predicted probability of graduating with a STEM major at a four-year college for students who never attended one.</p> <p>PHOTO (COLOR): Figure 1. Predicted probability student will declare or graduate with a STEM major, by ever attended CC status.</p> <p>Findings in Models 5 through 8 in Table 2 show results when the treatment variable is <emph>started post-secondary education at a community college</emph>. Compared to the results for <emph>ever attended</emph> and <emph>never attended</emph>, there appears to be an even stronger and more positively significant relationship between started at a community college and the probability of declaring and graduating with a STEM major at a four-year college. Figure 2 compares the predicted probability of declaring a STEM major (37%) and graduating with a STEM major (29%) at a four-year college for the students who started their post-secondary educations at a community college, with the predicted probability of declaring a STEM major (19%) and graduating with a STEM major (15%) at a four-year college for students who did not start their post-secondary education at a community college. Figure 2 is based on the results from models 6 and 8.</p> <p>PHOTO (COLOR): Figure 2. Predicted probability student will declare or graduate with a STEM major, by started at CC status.</p> <p>Furthermore, because we are interested in knowing whether students' socioeconomic status differentiates their odds of declaring/graduating with a STEM major at a four-year college after attending a community college, we run the models with an interaction term between <emph>ever attended</emph> community college, <emph>started post-secondary education at a community college</emph>, and socioeconomic status. Models in Appendix C & D show that there is no differential effect of community college attendance by students' socioeconomic status for their chances of declaring and/or graduating with a STEM major at a four-year college.</p> <hd id="AN0146366020-17">Findings from the propensity score matching analysis</hd> <p>For our PSM analysis, we constructed a "treatment" variable for both types of community college attendance (<emph>ever attended community college</emph> and <emph>started post-secondary education at community college</emph>). We matched students on a rich set of pre-high school covariates to account for selection bias associated with community college attendance. Prior literature suggests the selection of an array of covariates that predict students' choice of community college attendance must include variables also related to the outcome variable we are trying to explain. We chose the following variables as covariates: students' gender, race, SES (operationalized as the interaction between the student receiving free lunch with parents' level of education), if student had intent to declare a STEM major in his or her high school senior year (in one set of models), academic preparation (measured as math and English standardized test score in eighth grade, high school GPA, and if student took physics in high school). At the high school level, we selected covariates that could also help explain students' decision to enroll at a community college. We included teacher characteristics (percent of teachers with advanced degrees, percent of teachers with more than 10 years of experience, percent of licensed teachers) and characteristics of students' high school experience (percent of White students, percent of female students, and average SAT of students at school).</p> <p>Utilizing these variables, we calculate the propensity score that students <emph>ever attended a community college</emph> and that students <emph>started their post-secondary education at a community college</emph> and proceed to match students based on their estimated propensity scores in order to reduce selection bias. Our primary sample attended community colleges (both <emph>ever</emph> attended and s<emph>tarted</emph> at community college) and the matched sample did not attend community college. We began our analyses by calculating the impact of <emph>ever attended a community college</emph> on students' chances of declaration of a STEM major and chances of graduation with a STEM major. We then repeated these procedures for the <emph>started at community college</emph> cohort.</p> <p>Because we wanted to compare individuals who are as similar as possible on initial covariates and estimate the impact of attending a community college on students' declaration of STEM majors and graduation with a STEM degree at a four-year college, we checked the balancing properties of the baseline covariates. After matching, all of the covariates were balanced in means and the standard deviation ratios are close to one. We present results for models predicting ever attended community college and started post-secondary at community college with (Table 3, Model 9, 11, 13, and 15) and without including students' intent to major in STEM (Table 3, Models 10, 12, 14, and 16) as a predictor. Samples with intent to major in STEM as a predictor are substantially smaller due to missing values for students who did not take the SAT.</p> <p>Table 3. Average treatment of the treated (ATT) on STEM declaration and STEM graduation by community college attendance, propensity score matching.</p> <p> <ephtml> <table><thead><tr><td /><td><bold>Model 9</bold>. DECLARE STEM (controlling for intent to major in STEM) (<italic>n</italic> = 9,600)</td><td><bold>Model 10</bold>. DECLARE STEM (<italic>n</italic> = 14,520)</td><td><bold>Model 11</bold>. GRADUATE STEM (controlling for intent to major in STEM) (<italic>n</italic> = 8,060)</td><td><bold>Model 12</bold>. GRADUATE STEM (<italic>n</italic> = 7,410)</td><td /><td><bold>Model 13</bold>. DECLARE STEM (controlling for intent to major in STEM) (<italic>n</italic> = 9,600)</td><td><bold>Model 14</bold>. DECLARE STEM (<italic>n</italic> = 14,520)</td><td><bold>Model 15</bold>. GRADUATE STEM (controlling for intent to major in STEM) (<italic>n</italic> = 8,060)</td><td><bold>Model 16</bold>. GRADUATE STEM (<italic>n</italic> = 7,410)</td></tr><tr><td /><td>ATT</td><td>Sig.</td><td>ATT</td><td>Sig.</td><td>ATT</td><td>Sig.</td><td>ATT</td><td>Sig.</td><td /><td>ATT</td><td>Sig.</td><td>ATT</td><td>Sig.</td><td>ATT</td><td>Sig.</td><td>ATT</td><td>Sig.</td></tr></thead><tbody><tr><td>Ever Attended CC</td><td>0.066</td><td>***</td><td>0.054</td><td>***</td><td>0.040</td><td>**</td><td>0.032</td><td>**</td><td>Started at CC</td><td>0.104</td><td>***</td><td>0.101</td><td>***</td><td>0.088</td><td>***</td><td>0.074</td><td>***</td></tr><tr><td /><td>0.017</td><td /><td>0.014</td><td /><td>0.017</td><td /><td>0.015</td><td /><td /><td>0.025</td><td /><td>0.020</td><td /><td>0.026</td><td /><td>0.020</td><td /></tr></tbody></table> </ephtml> </p> <ulist> <item>5 ***<emph>p</emph> <.001, ** <emph>p</emph> <.05 and *<emph>p</emph> <.90.</item> <item>6 The variables utilized to predict community college attendance include male, race, SES (free/reduced lunch and first-generation college status), math EOG, high school GPA, took physics in high school, English EOC, percent of teacher with advanced degrees at high school, percent of students who were White at HS, percent of experienced teachers at HS, percent of licensed teachers at HS, percent of female students at HS, average SAT score at the school.</item> </ulist> <p>The results of the PSM estimations are similar to the multilevel binomial estimates, suggesting significant differences in students' STEM declaration and students' STEM graduation at a four-year college if they attended community college. Holding all else constant, results show that having ever attended a community college significantly increases the odds of declaring a STEM major at a four-year college by 6.6% (Model 9) or by 5.4% (Model 10) and significantly increases the odds of graduating with a STEM major at a four-year college by 4% (Model 11) or by 3.2% % (Model 12). Findings show that when we compare two individuals with similar propensity scores, we find a significantly higher likelihood of declaring and graduating with a STEM major at a four-year college for those who attended community college. These results suggest that the effects found are unlikely due to confounding variables shared only by students who attended community colleges.</p> <p>PSM results presented in Table 3 support that having started post-secondary education at a community college has a stronger effect than ever attending a community college on students' odds of declaration of a STEM major at a four-year college (10.4% in Model 13 controlling for intent and 10.1% in Model 14 not controlling for intent) and with students' odds of graduation with a STEM major at a four-year college (8.8% in Model 15 controlling for intent and 7.4% in Model 16 not controlling for intent). Thus, our results from PSM models suggest that, even after controlling for self-selection into attending community colleges, we find a significant difference in students' odds of declaration and graduation with a STEM major at a four-year college, depending on whether students started their post-secondary educations at community colleges. Once again, the results of the PSM confirm the multilevel model's results showing positive effects from ever attended a community college and started post-secondary education at community colleges and odds of declaring and graduating with a STEM major once students enroll in a four-year institution. These findings support Wang's ([<reflink idref="bib59" id="ref84">59</reflink>]) findings that community colleges have the potential to assist some students in their degree pursuits and Wang et al.'s ([<reflink idref="bib60" id="ref85">60</reflink>]) results, which state that community college attendance might complement the route to graduate and professional school. These findings remain very similar when models predicting community college attendance use students' intent to major in STEM when in high school as a predictor. To test the reliability of our findings we also ran the multilevel binomial models on the matched sample utilized for the PSM analysis: results again show the significant and positive relationship between community college attendance and STEM declaration and graduation at a four-year college.</p> <hd id="AN0146366020-18">Discussion</hd> <p>This study integrates the rational choice framework and the theories of cumulative disadvantage (DiPrete & Eirich, [<reflink idref="bib16" id="ref86">16</reflink>]; Merton, [<reflink idref="bib30" id="ref87">30</reflink>]) to help account for community college transfer students' selection of STEM as a college major. The main objective of this study was to test if community college attendance was significantly related to students' declaration of a STEM major and students' graduation with a STEM degree at a four-year college. Based on previous literature, we expected that community college attendance may provide low-cost additional academic preparation, and access to broader information necessary for making well-informed major choices. This sequence may contribute to the choice of a STEM as a major once they transfer to a four-year college. Two different measures of community college attendance were used: ever attended a community college and started post-secondary education at a community college. The results suggest that, for our sample of North Carolina students, both, having ever attended a community college or starting post-secondary education at a community college, have a significant positive relationship with their likelihood of declaring and graduating with a STEM major. In other words, students who attended a community college are more likely to declare and graduate with a STEM major at a four-year college than otherwise comparable students who did not attend a community college. This supports previous findings suggesting that community colleges have tremendous potential of becoming important pathways to STEM degrees (Bahr et al., [<reflink idref="bib4" id="ref88">4</reflink>]).</p> <p>The second objective of this study was to recognize if the importance of community college enrollment in students' likelihood of going into STEM at a four-year college varies depending on students' socioeconomic status. Given LSES community college students' likely lower levels of social and cultural capital and academic preparation for higher education, we hypothesized that community college attendance might be more beneficial in increasing these students' odds of going into STEM. Although our results lend support to the notion that community college attendance helps disrupt the negative effects of cumulative disadvantage encountered by LSES students, they do not support the hypothesis that either type of community college attendance has a differential effect on students' likelihood of declaring or graduating with a STEM degree based on students' socioeconomic status. In fact, our results show that community college attendance is related to increases in students' odds of majoring and graduating with a STEM degree at a four-year college irrespective of family SES. Our findings suggest that the benefits of community college attendance are not restricted to only low-SES students. The finding is consistent with previous research showing that community colleges are becoming an important pathway to STEM degrees for all youth.</p> <hd id="AN0146366020-19">Limitations</hd> <p>This study has several limitations. First, our analytic sample is made of students who attended secondary public school in North Carolina, declared a major and/or graduated with a STEM degree from 1 of UNC's 16 four-year campuses, and graduated within six years of high school completion. Therefore, the estimates obtained are applicable exclusively to community college students enrolled in curriculum programs that link to an associate's degree or transfer to four-year colleges. These students account for almost 40% of the community college enrollment across the state (Clotfelter et al., [<reflink idref="bib15" id="ref89">15</reflink>]), but not to all students who attended community colleges. Because of this, we are not able to study other important missions of community colleges besides the transfer mission, including workforce preparation in applied degree programs that may be STEM-focused. Second, the lack of additional availability of psychological/aspirational variables in our dataset limit the possibility of including variables that better capture the socioemotional factors that contribute to the decision-making processes associated with declaring and graduating with a STEM degree at a four-year college. Third, our findings might be related to the particular circumstances that exist in North Carolina. North Carolina's community college system is the third largest in the country. Consequently, students in North Carolina have closer proximity and better availability of community college campuses than students in most other states across the U.S. Additionally, the North Carolina community college and four-year university systems have a system of articulation agreements designed to ease transfer between institutions, a factor perhaps not as well developed in other states' higher education systems.</p> <hd id="AN0146366020-20">Future research</hd> <p>While our analysis offers a view of the importance of community colleges on students' four-year college STEM success, other important questions remain to be answered. Future studies should aim to (<reflink idref="bib1" id="ref90">1</reflink>) study the other ways in which community colleges might be significantly related to STEM attainment beyond the transfer mission; (<reflink idref="bib2" id="ref91">2</reflink>) obtain data on STEM attainment at two-year colleges to be better able to address the STEM pathways of non-traditional and LSES students.</p> <hd id="AN0146366020-21">Conclusions</hd> <p>There are a number of policy implications related to our results. First, our findings support previous findings that argue community colleges foster the educational attainment of some students (Leigh & Gill, [<reflink idref="bib25" id="ref92">25</reflink>]). At least for 40% of students who transfer and pursue STEM degrees, the findings do not support the diversion effect argument that suggests that two-year colleges stunt the educational aspirations and attainment of their students (Brint & Karabel, [<reflink idref="bib11" id="ref93">11</reflink>]; Clark, [<reflink idref="bib14" id="ref94">14</reflink>]). This finding is important given that community colleges represent more than one fourth of all postsecondary educational institutions in the United States, enroll more than one third of all college students, and serve a disproportionate number of low-SES students (American Association of Community Colleges, [<reflink idref="bib3" id="ref95">3</reflink>]).</p> <p>Second, the results of this study suggest that starting post-secondary education at a community college might even have an additional positive relationship with students' odds of going into STEM at a four-year college. A portion of high school students that likely utilize community colleges as bridges into four-year college STEM majors, perhaps because community colleges allow them to take introductory college-level courses at a lower cost, in smaller learning contexts, and provide opportunities to acquire important social and cultural capital necessary to successfully transition and persist at four-year institutions.</p> <p>Third, the fact that our findings are not only restricted to low SES students in our sample is encouraging. Community colleges in NC might be helping improve the rigorous academic preparation of all students given the very high academic demands of STEM majors. Community colleges likely help all students in their transitions into four-year colleges by providing them with additional information that fosters better rational choices regarding their college major. Based on our findings, policy makers can advocate for the significant and positive role community colleges could have in increasing the pool of potential STEM workers.</p> <p>In conclusion, our results suggest that two-year colleges can serve as a step in preparing a larger number of students for the successful pursuit of STEM baccalaureate degrees. Affordable community colleges allow those who experienced the cumulative disadvantages of poverty or poor secondary educations a pathway to remediate their academic deficiencies and/or lack of information. Additionally, community colleges foster STEM participation among more privileged students who begin their pursuit of a STEM degree at a community college. Our findings support the notion that community colleges may have a positive impact on STEM four-year college attainment. Our findings for North Carolina suggest expanded access to community college educations can advance both individual educational attainment and STEM workforce preparation.</p> <hd id="AN0146366020-22">Disclosure Statement</hd> <p>No potential conflict of interest was reported by the authors.</p> <hd id="AN0146366020-23">Appendix A. Descriptive statistics of students excluded and included in our analysis</hd> <p></p> <p> <ephtml> <table><thead><tr><td /><td>Excluded</td><td /><td>Included</td></tr><tr><td>Variable</td><td>Obs</td><td>Mean</td><td /><td>Obs</td><td>Mean</td></tr></thead><tbody><tr><td>Declared a STEM Major</td><td>5,130</td><td>0.234</td><td>**</td><td>14,520</td><td>0.219</td></tr><tr><td>Graduated with a STEM Major</td><td>4,180</td><td>0.206</td><td>**</td><td>12,170</td><td>0.189</td></tr><tr><td>Intention to Major in STEM</td><td>2,900</td><td>0.396</td><td /><td>9,770</td><td>0.386</td></tr><tr><td>Student is Male</td><td>5,130</td><td>0.462</td><td>***</td><td>14,520</td><td>0.427</td></tr><tr><td>Black</td><td>5,130</td><td>0.165</td><td>***</td><td>14,520</td><td>0.218</td></tr><tr><td>Hispanic</td><td>5,130</td><td>0.027</td><td>***</td><td>14,520</td><td>0.011</td></tr><tr><td>Asian</td><td>5,130</td><td>0.041</td><td>***</td><td>14,520</td><td>0.031</td></tr><tr><td>American Indian</td><td>5,130</td><td>0.011</td><td>**</td><td>14,520</td><td>0.008</td></tr><tr><td>Other</td><td>5,130</td><td>0.013</td><td>***</td><td>14,520</td><td>0.004</td></tr><tr><td>White</td><td>5,130</td><td>0.743</td><td>**</td><td>14,520</td><td>0.728</td></tr><tr><td>Did NOT Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td>1,310</td><td>0.705</td><td>***</td><td>14,520</td><td>0.792</td></tr><tr><td>Received Free/Reduced Lunch & NOT First-Generation College Students</td><td>1,310</td><td>0.103</td><td>**</td><td>14,520</td><td>0.084</td></tr><tr><td>Did NOT Receive Free/Reduced Lunch & First- Generation College Student</td><td>1,310</td><td>0.126</td><td>***</td><td>14,520</td><td>0.086</td></tr><tr><td>Received Free/Reduced Lunch & First- Generation College Student</td><td>1,310</td><td>0.067</td><td>***</td><td>14,520</td><td>0.038</td></tr><tr><td>Math EOG (standardized test)</td><td>2,570</td><td>178.656</td><td>***</td><td>14,520</td><td>179.335</td></tr><tr><td>High School GPA</td><td>4,150</td><td>363.529</td><td /><td>14,520</td><td>364.832</td></tr><tr><td>Took Physics in High School</td><td>3,170</td><td>0.368</td><td>***</td><td>14,520</td><td>0.270</td></tr><tr><td>English EOC (standardized test)</td><td>3,570</td><td>61.630</td><td>**</td><td>14,520</td><td>61.943</td></tr><tr><td>Percent of Teachers with Advanced Degrees</td><td>3,540</td><td>0.262</td><td>***</td><td>14,520</td><td>0.273</td></tr><tr><td>Percent of Students who are White</td><td>3,230</td><td>0.661</td><td /><td>14,520</td><td>0.656</td></tr><tr><td>Percent of Experienced Teachers</td><td>3,540</td><td>0.539</td><td>***</td><td>14,520</td><td>0.548</td></tr><tr><td>Percent of Licensed Teachers</td><td>3,540</td><td>0.817</td><td>***</td><td>14,520</td><td>0.822</td></tr><tr><td>Percent of Female Students</td><td>3,140</td><td>0.497</td><td>***</td><td>14,520</td><td>0.495</td></tr><tr><td>Average SAT Score</td><td>3,070</td><td>1003.838</td><td>***</td><td>14,520</td><td>997.388</td></tr><tr><td>Ever Attended CC</td><td>5,130</td><td>0.381</td><td>***</td><td>14,520</td><td>0.214</td></tr><tr><td>Started at CC</td><td>5,130</td><td>0.276</td><td>***</td><td>14,520</td><td>0.104</td></tr><tr><td>Attended NCSU</td><td>5,130</td><td>0.155</td><td /><td>14,520</td><td>0.153</td></tr><tr><td>Percent Female Professors Teaching STEM</td><td>5,130</td><td>28.831</td><td>***</td><td>14,520</td><td>29.758</td></tr><tr><td>Attended Historically Black College</td><td>5,130</td><td>0.106</td><td>***</td><td>14,520</td><td>0.140</td></tr></tbody></table> </ephtml> </p> <p>7 ***<emph>p</emph> <.001,**<emph>p</emph> <.05 and *<emph>p</emph> <.90.</p> <hd id="AN0146366020-24">Appendix B. Pstest of variables utilized in the psmatch of treated and control observations</hd> <p></p> <p> <ephtml> <table><thead><tr><td /><td>Mean</td><td /><td /></tr><tr><td>Variable</td><td>Treated</td><td>Control</td><td>%bias</td><td>V(T)/V(C)</td></tr></thead><tbody><tr><td>Male</td><td>0.484</td><td>0.445</td><td>7.8</td><td /></tr><tr><td>Race</td><td>5.345</td><td>5.526</td><td>−9.9</td><td>1.49</td></tr><tr><td>SES</td><td>1.48</td><td>1.446</td><td>4.1</td><td>1.08</td></tr><tr><td>Math EOG</td><td>175.72</td><td>175.02</td><td>8.7</td><td>1.25</td></tr><tr><td>High School GPA</td><td>318.57</td><td>320.23</td><td>−2.8</td><td>1.35</td></tr><tr><td>Took Physics in High School</td><td>0.139</td><td>0.119</td><td>4.9</td><td /></tr><tr><td>English EOC</td><td>58.965</td><td>58.744</td><td>3.7</td><td>1.2</td></tr><tr><td>Percent of Teachers with Advanced Degrees</td><td>0.268</td><td>0.264</td><td>4.1</td><td>1.05</td></tr><tr><td>Percent of White Students</td><td>0.723</td><td>0.751</td><td>−13.9</td><td>1.19</td></tr><tr><td>Percent of Experienced Teachers</td><td>0.569</td><td>0.579</td><td>−10.8</td><td>1.21</td></tr><tr><td>Percent of Licensed Teachers</td><td>0.832</td><td>0.838</td><td>−7.1</td><td>1.13</td></tr><tr><td>Percent of Female Students</td><td>0.493</td><td>0.495</td><td>−6.3</td><td>1.22</td></tr><tr><td>Average SAT Score at School</td><td>994.72</td><td>995.46</td><td>−1.1</td><td>1.24</td></tr></tbody></table> </ephtml> </p> <hd id="AN0146366020-25">Appendix C. Multilevel binomial models predicting students odds of declaring and graduating w...</hd> <p></p> <p> <ephtml> <table><thead><tr><td /><td>Declare STEM</td><td /><td>Graduate with STEM</td></tr><tr><td /><td>(With intention to major in STEM) <italic>n</italic> = 9,760</td><td /><td>(No intention to major in STEM) <italic>n</italic> = 14,520</td><td /><td>(With intention to major in STEM & SES interaction) <italic>n</italic> = 9,760</td><td /><td>(no intention to major in STEM & SES interaction) <italic>n</italic> = 14,520</td><td /><td>(With intention to major in STEM) <italic>n</italic> = 8,210</td><td /><td>(No intention to major in STEM) n = 9,990</td><td /><td>(With intention to major in STEM & SES interaction) <italic>n</italic> = 8,210</td><td /><td>(No intention to major in STEM & SES interaction) <italic>n</italic> = 9,990</td></tr><tr><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td></tr></thead><tbody><tr><td><bold><italic>Student Level Variables</italic></bold></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Intercept</td><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td><td /><td /><td>***</td><td /><td>0.000</td><td>***</td><td /><td /><td>***</td><td /><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td></tr><tr><td>Male</td><td>1.366</td><td>***</td><td /><td>2.058</td><td>***</td><td /><td /><td>***</td><td /><td>2.056</td><td>***</td><td /><td /><td>***</td><td /><td>2.104</td><td>***</td><td /><td>1.301</td><td>***</td><td /><td>2.102</td><td>***</td></tr><tr><td>Black</td><td>1.140</td><td /><td /><td>1.249</td><td>**</td><td /><td>1.136</td><td /><td /><td>1.251</td><td>***</td><td /><td>1.133</td><td /><td /><td>0.998</td><td /><td /><td>0.916</td><td /><td /><td>1.001</td><td /></tr><tr><td>Hispanic</td><td>1.148</td><td /><td /><td>1.101</td><td /><td /><td>1.153</td><td /><td /><td>1.104</td><td /><td /><td>1.413</td><td /><td /><td>0.764</td><td /><td /><td>0.732</td><td /><td /><td>0.764</td><td /></tr><tr><td>Asian</td><td>2.370</td><td>***</td><td /><td>2.444</td><td>***</td><td /><td>2.383</td><td>***</td><td /><td>2.451</td><td>***</td><td /><td>1.175</td><td>***</td><td /><td>2.380</td><td>***</td><td /><td>2.187</td><td>***</td><td /><td>2.377</td><td>***</td></tr><tr><td>American Indian</td><td>2.661</td><td>***</td><td /><td>2.518</td><td>***</td><td /><td>2.612</td><td>***</td><td /><td>2.515</td><td>***</td><td /><td>1.381</td><td>**</td><td /><td>1.965</td><td>**</td><td /><td>2.124</td><td>**</td><td /><td>1.940</td><td>**</td></tr><tr><td>Other</td><td>0.794</td><td /><td /><td>0.979</td><td /><td /><td>0.798</td><td /><td /><td>0.985</td><td /><td /><td>1.624</td><td /><td /><td>1.287</td><td /><td /><td>1.065</td><td /><td /><td>1.307</td><td /></tr><tr><td>Did NOT Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td>0.930</td><td /><td /><td>0.919</td><td /><td /><td>0.938</td><td /><td /><td>0.904</td><td /><td /><td>1.202</td><td /><td /><td>0.747</td><td>*</td><td /><td>0.802</td><td /><td /><td>0.789</td><td /></tr><tr><td>Received Free/Reduced Lunch & NOT First-Generation College Students</td><td>0.942</td><td /><td /><td>0.962</td><td /><td /><td>0.925</td><td /><td /><td>0.916</td><td /><td /><td>1.231</td><td /><td /><td>0.777</td><td /><td /><td>0.723</td><td /><td /><td>0.738</td><td /></tr><tr><td>Did NOT Receive Free/Reduced Lunch & First-Generation College Student</td><td>0.826</td><td /><td /><td>0.777</td><td>*</td><td /><td>0.763</td><td /><td /><td>0.736</td><td>*</td><td /><td>1.236</td><td>*</td><td /><td>0.615</td><td>***</td><td /><td>0.630</td><td>*</td><td /><td>0.630</td><td>**</td></tr><tr><td>Intention to Major in STEM</td><td>4.172</td><td>***</td><td /><td /><td /><td /><td>4.170</td><td>***</td><td /><td /><td /><td /><td>1.073</td><td>***</td><td /><td /><td /><td /><td>4.328</td><td>***</td><td /><td /><td /></tr><tr><td>Math EOG (standardized test)</td><td>1.024</td><td>***</td><td /><td>1.033</td><td>***</td><td /><td>1.024</td><td>***</td><td /><td>1.033</td><td>***</td><td /><td>1.006</td><td>***</td><td /><td>1.033</td><td>***</td><td /><td>1.026</td><td>***</td><td /><td>1.033</td><td>***</td></tr><tr><td>High School GPA</td><td>1.005</td><td>***</td><td /><td>1.006</td><td>***</td><td /><td>1.005</td><td>***</td><td /><td>1.006</td><td>***</td><td /><td>1.001</td><td>***</td><td /><td>1.008</td><td>***</td><td /><td>1.007</td><td>***</td><td /><td>1.008</td><td>***</td></tr><tr><td>Took Physics in High School</td><td>1.612</td><td>***</td><td /><td>1.781</td><td>***</td><td /><td>1.612</td><td>***</td><td /><td>1.781</td><td>***</td><td /><td>1.074</td><td>***</td><td /><td>1.741</td><td>***</td><td /><td>1.588</td><td>***</td><td /><td>1.742</td><td>***</td></tr><tr><td>English EOC (standardized test)</td><td>0.998</td><td /><td /><td>0.992</td><td /><td /><td>0.998</td><td /><td /><td>0.992</td><td /><td /><td>1.008</td><td /><td /><td>0.988</td><td>**</td><td /><td>0.991</td><td /><td /><td>0.988</td><td>**</td></tr><tr><td>Ever Attended CC</td><td>1.409</td><td>***</td><td /><td>1.465</td><td>***</td><td /><td>1.369</td><td /><td /><td>1.360</td><td /><td /><td>1.100</td><td /><td /><td>1.256</td><td>***</td><td /><td>1.184</td><td /><td /><td>1.478</td><td /></tr><tr><td>Attended NCSU</td><td>2.625</td><td>***</td><td /><td>2.735</td><td>***</td><td /><td>2.632</td><td>***</td><td /><td>2.731</td><td>***</td><td /><td>1.454</td><td>**</td><td /><td>2.507</td><td>**</td><td /><td>2.263</td><td>**</td><td /><td>2.505</td><td>**</td></tr><tr><td>Percent Female Professors Teaching STEM</td><td>0.976</td><td>*</td><td /><td>0.973</td><td>**</td><td /><td>0.976</td><td>*</td><td /><td>0.973</td><td>**</td><td /><td>1.014</td><td>**</td><td /><td>0.969</td><td>**</td><td /><td>0.970</td><td>**</td><td /><td>0.969</td><td>**</td></tr><tr><td>Attended Historically Black College</td><td>1.866</td><td>***</td><td /><td>1.634</td><td>**</td><td /><td>1.859</td><td>***</td><td /><td>1.633</td><td>**</td><td /><td>1.264</td><td>***</td><td /><td>1.856</td><td>***</td><td /><td>2.049</td><td>***</td><td /><td>1.861</td><td>***</td></tr><tr><td><bold><italic>High School Level Variables</italic></bold></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Percent of Teachers with Advanced Degrees</td><td>0.746</td><td /><td /><td>0.961</td><td /><td /><td>0.743</td><td /><td /><td>0.962</td><td /><td /><td>1.739</td><td /><td /><td>1.056</td><td /><td /><td>1.047</td><td /><td /><td>1.071</td><td /></tr><tr><td>Percent of Students who are White</td><td>0.812</td><td /><td /><td>1.036</td><td /><td /><td>0.804</td><td /><td /><td>1.039</td><td /><td /><td>1.265</td><td>*</td><td /><td>0.845</td><td /><td /><td>0.659</td><td>*</td><td /><td>0.848</td><td /></tr><tr><td>Percent of Experienced Teachers</td><td>1.196</td><td /><td /><td>1.415</td><td /><td /><td>1.202</td><td /><td /><td>1.412</td><td /><td /><td>1.615</td><td /><td /><td>1.369</td><td /><td /><td>1.209</td><td /><td /><td>1.361</td><td /></tr><tr><td>Percent of Licensed Teachers</td><td>4.316</td><td>***</td><td /><td>3.257</td><td>**</td><td /><td>4.351</td><td>***</td><td /><td>3.271</td><td>**</td><td /><td>1.911</td><td>***</td><td /><td>5.794</td><td>***</td><td /><td>5.636</td><td>***</td><td /><td>5.866</td><td>***</td></tr><tr><td>Percent of Female Students</td><td>0.064</td><td /><td /><td>0.314</td><td /><td /><td>0.064</td><td /><td /><td>0.319</td><td /><td /><td>7.278</td><td /><td /><td>0.839</td><td /><td /><td>0.075</td><td /><td /><td>0.907</td><td /></tr><tr><td>Average SAT Score</td><td>1.001</td><td /><td /><td>0.999</td><td /><td /><td>1.001</td><td /><td /><td>0.999</td><td /><td /><td /><td /><td /><td>0.999</td><td /><td /><td>1.000</td><td /><td /><td>0.999</td><td /></tr><tr><td><bold><italic>Interaction Terms</italic></bold></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Ever Attended Community College* Did NOT Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td /><td /><td /><td /><td /><td /><td>0.979</td><td /><td /><td>1.058</td><td /><td /><td /><td /><td /><td /><td /><td /><td>0.932</td><td /><td /><td>0.787</td><td /></tr><tr><td>Ever Attended Community College* Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td /><td /><td /><td /><td /><td /><td>1.055</td><td /><td /><td>1.279</td><td /><td /><td /><td /><td /><td /><td /><td /><td>1.367</td><td /><td /><td>1.332</td><td /></tr><tr><td>Ever Attended Community College* Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td /><td /><td /><td /><td /><td /><td>1.358</td><td /><td /><td>1.216</td><td /><td /><td /><td /><td /><td /><td /><td /><td>1.218</td><td /><td /><td>0.903</td><td /></tr></tbody></table> </ephtml> </p> <p>8 *** p <.001,** p <.05 and * p <.90.</p> <hd id="AN0146366020-26">Appendix D. Multilevel binomial models predicting students odds of declaring and graduating w...</hd> <p></p> <p> <ephtml> <table><thead><tr><td /><td>Declared a STEM Major</td><td>Graduated with a STEM Major</td></tr><tr><td /><td>(With intention to major in STEM) <italic>n</italic> = 9,760</td><td>(No intention to major in STEM) <italic>n</italic> = 14,520</td><td>(With intention to major in STEM & SES interaction) <italic>n</italic> = 9,760</td><td>(No intention to major in STEM & SES interaction) <italic>n</italic> = 14,520</td><td>(With intention to major in STEM) <italic>n</italic> = 8,210</td><td>(No intention to major in STEM) <italic>n</italic> = 9,990</td><td>(With intention to major in STEM & SES interaction) <italic>n</italic> = 8,210</td><td>(No intention to major in STEM & SES interaction) <italic>n</italic> = 9,990</td></tr><tr><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td><td /><td>OR</td><td>Sig.</td></tr></thead><tbody><tr><td><bold><italic>Student Level Variables</italic></bold></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Intercept</td><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td><td /><td>0.000</td><td>***</td></tr><tr><td>Male</td><td>1.349</td><td>***</td><td /><td>2.044</td><td>***</td><td /><td>1.351</td><td>***</td><td /><td>2.044</td><td>***</td><td /><td>1.305</td><td>***</td><td /><td>2.138</td><td>***</td><td /><td>1.306</td><td>***</td><td /><td>2.067</td><td>***</td></tr><tr><td>Black</td><td>1.236</td><td>**</td><td /><td>1.330</td><td>***</td><td /><td>1.226</td><td>*</td><td /><td>1.317</td><td>***</td><td /><td>0.982</td><td /><td /><td>1.062</td><td /><td /><td>0.984</td><td /><td /><td>1.013</td><td /></tr><tr><td>Hispanic</td><td>1.167</td><td /><td /><td>1.103</td><td /><td /><td>1.164</td><td /><td /><td>1.108</td><td /><td /><td>0.735</td><td /><td /><td>0.766</td><td /><td /><td>0.727</td><td /><td /><td>0.758</td><td /></tr><tr><td>Asian</td><td>2.264</td><td>***</td><td /><td>2.412</td><td>***</td><td /><td>2.250</td><td>***</td><td /><td>2.417</td><td>***</td><td /><td>2.125</td><td>***</td><td /><td>2.347</td><td>***</td><td /><td>2.108</td><td>***</td><td /><td>2.314</td><td>***</td></tr><tr><td>American Indian</td><td>3.089</td><td>***</td><td /><td>2.603</td><td>***</td><td /><td>3.064</td><td>***</td><td /><td>2.621</td><td>***</td><td /><td>2.303</td><td>**</td><td /><td>2.878</td><td>***</td><td /><td>2.281</td><td>**</td><td /><td>2.482</td><td>***</td></tr><tr><td>Other</td><td>0.752</td><td /><td /><td>0.982</td><td /><td /><td>0.756</td><td /><td /><td>0.981</td><td /><td /><td>1.007</td><td /><td /><td>1.324</td><td /><td /><td>1.028</td><td /><td /><td>1.327</td><td /></tr><tr><td>Did NOT Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td>0.950</td><td /><td /><td>0.950</td><td /><td /><td>0.962</td><td /><td /><td>0.918</td><td /><td /><td>0.811</td><td /><td /><td>0.772</td><td /><td /><td>0.842</td><td /><td /><td>0.819</td><td /></tr><tr><td>Received Free/Reduced Lunch & NOT First-Generation College Students</td><td>0.959</td><td /><td /><td>0.995</td><td /><td /><td>0.942</td><td /><td /><td>0.943</td><td /><td /><td>0.783</td><td /><td /><td>0.783</td><td /><td /><td>0.779</td><td /><td /><td>0.805</td><td /></tr><tr><td>Did NOT Receive Free/Reduced Lunch & First-Generation College Student</td><td>0.826</td><td /><td /><td>0.782</td><td>*</td><td /><td>0.834</td><td /><td /><td>0.766</td><td /><td /><td>0.663</td><td>*</td><td /><td>0.624</td><td>**</td><td /><td>0.681</td><td>*</td><td /><td>0.673</td><td>**</td></tr><tr><td>Intention to Major in STEM</td><td>4.137</td><td>***</td><td /><td /><td /><td /><td>4.137</td><td>***</td><td /><td /><td /><td /><td>4.332</td><td>***</td><td /><td /><td /><td /><td>4.321</td><td>***</td><td /><td /><td /></tr><tr><td>Math EOG (standardized test)</td><td>1.024</td><td>***</td><td /><td>1.033</td><td>***</td><td /><td>1.024</td><td>***</td><td /><td>1.033</td><td>***</td><td /><td>1.025</td><td>***</td><td /><td>1.032</td><td>***</td><td /><td>1.025</td><td>***</td><td /><td>1.033</td><td>***</td></tr><tr><td>High School GPA</td><td>1.006</td><td>***</td><td /><td>1.007</td><td>***</td><td /><td>1.006</td><td>***</td><td /><td>1.007</td><td>***</td><td /><td>1.008</td><td>***</td><td /><td>1.009</td><td>***</td><td /><td>1.008</td><td>***</td><td /><td>1.009</td><td>***</td></tr><tr><td>Took Physics in High School</td><td>1.648</td><td>***</td><td /><td>1.800</td><td>***</td><td /><td>1.640</td><td>***</td><td /><td>1.794</td><td>***</td><td /><td>1.603</td><td>***</td><td /><td>1.768</td><td>***</td><td /><td>1.607</td><td>***</td><td /><td>1.746</td><td>***</td></tr><tr><td>English EOC (standardized test)</td><td>0.999</td><td /><td /><td>0.992</td><td /><td /><td>0.999</td><td /><td /><td>0.992</td><td /><td /><td>0.992</td><td /><td /><td>0.989</td><td>*</td><td /><td>0.992</td><td /><td /><td>0.988</td><td>*</td></tr><tr><td>Started at CC</td><td>2.427</td><td>***</td><td /><td>2.432</td><td>***</td><td /><td>2.499</td><td>**</td><td /><td>1.919</td><td>*</td><td /><td>2.080</td><td>***</td><td /><td>2.125</td><td>***</td><td /><td>2.636</td><td>*</td><td /><td>3.061</td><td>***</td></tr><tr><td>Attended NCSU</td><td>2.429</td><td>**</td><td /><td>2.535</td><td>**</td><td /><td>2.428</td><td>**</td><td /><td>2.532</td><td>**</td><td /><td>2.167</td><td>*</td><td /><td>2.330</td><td>**</td><td /><td>2.170</td><td>*</td><td /><td>2.345</td><td>**</td></tr><tr><td>Percent Female Professors Teaching STEM</td><td>0.973</td><td>**</td><td /><td>0.970</td><td>**</td><td /><td>0.973</td><td>**</td><td /><td>0.970</td><td>**</td><td /><td>0.967</td><td>**</td><td /><td>0.965</td><td>**</td><td /><td>0.967</td><td>**</td><td /><td>0.965</td><td>**</td></tr><tr><td>Attended Historically Black College</td><td>1.878</td><td>***</td><td /><td>1.665</td><td>**</td><td /><td>1.886</td><td>***</td><td /><td>1.663</td><td>**</td><td /><td>2.056</td><td>***</td><td /><td>1.738</td><td>**</td><td /><td>2.084</td><td>***</td><td /><td>1.804</td><td>**</td></tr><tr><td><bold><italic>High School Level Variables</italic></bold></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Percent of Teachers with Advanced Degrees</td><td>0.729</td><td /><td /><td>0.950</td><td /><td /><td>0.730</td><td /><td /><td>0.949</td><td /><td /><td>1.038</td><td /><td /><td>1.096</td><td /><td /><td>1.042</td><td /><td /><td>1.087</td><td /></tr><tr><td>Percent of Students who are White</td><td>0.818</td><td /><td /><td>0.992</td><td /><td /><td>0.828</td><td /><td /><td>0.990</td><td /><td /><td>0.621</td><td>**</td><td /><td>0.712</td><td /><td /><td>0.624</td><td>**</td><td /><td>0.769</td><td /></tr><tr><td>Percent of Experienced Teachers</td><td>1.189</td><td /><td /><td>1.416</td><td /><td /><td>1.187</td><td /><td /><td>1.401</td><td /><td /><td>1.187</td><td /><td /><td>1.277</td><td /><td /><td>1.172</td><td /><td /><td>1.301</td><td /></tr><tr><td>Percent of Licensed Teachers</td><td>4.239</td><td>***</td><td /><td>3.193</td><td>**</td><td /><td>4.249</td><td>***</td><td /><td>3.209</td><td>**</td><td /><td>5.641</td><td>***</td><td /><td>5.710</td><td>***</td><td /><td>5.729</td><td>***</td><td /><td>5.813</td><td>***</td></tr><tr><td>Percent of Female Students</td><td>0.068</td><td /><td /><td>0.322</td><td /><td /><td>0.069</td><td /><td /><td>0.319</td><td /><td /><td>0.072</td><td /><td /><td>0.846</td><td /><td /><td>0.076</td><td /><td /><td>0.859</td><td /></tr><tr><td>Average SAT Score</td><td>1.001</td><td /><td /><td>1.000</td><td /><td /><td>1.001</td><td /><td /><td>0.999</td><td /><td /><td>1.000</td><td /><td /><td>1.000</td><td /><td /><td>1.000</td><td /><td /><td>0.999</td><td /></tr><tr><td><bold><italic>Interaction Terms</italic></bold></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Started at Community College* Did NOT Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td /><td /><td /><td /><td /><td /><td>0.926</td><td /><td /><td>1.276</td><td /><td /><td /><td /><td /><td /><td /><td /><td>0.732</td><td /><td /><td>0.692</td><td /></tr><tr><td>Started at Community College* Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td /><td /><td /><td /><td /><td /><td>1.182</td><td /><td /><td>1.464</td><td /><td /><td /><td /><td /><td /><td /><td /><td>1.232</td><td /><td /><td>0.962</td><td /></tr><tr><td>Started at Community College* Receive Free/Reduced Lunch and is NOT First-Generation College Student</td><td /><td /><td /><td /><td /><td /><td>0.960</td><td /><td /><td>1.177</td><td /><td /><td /><td /><td /><td /><td /><td /><td>0.814</td><td /><td /><td>0.657</td><td /></tr></tbody></table> </ephtml> </p> <p>9 ***<emph>p</emph> <.001, **<emph>p</emph> <.05 and *<emph>p</emph> <.90.</p> <ref id="AN0146366020-27"> <title> References </title> <blist> <bibl id="bib1" idref="ref28" type="bt">1</bibl> <bibtext> Alexander, K. L., Entwisle, D. R., & Olson, L. S. (2007). Lasting consequences of the summer learning gap. American Sociological Review, 72 (2), 167 – 180. https://doi.org/10.1177/000312240707200202</bibtext> </blist> <blist> <bibl id="bib2" idref="ref55" type="bt">2</bibl> <bibtext> Amelink, C. T., Artis, S., & King Liu, T. J. (2015). Examining the self-efficacy of community college STEM majors: Factors related to four-year degree attainment. Community College Journal of Research and Practice, 39 (12), 1111 – 1124. https://doi.org/10.1080/10668926.2014.941514</bibtext> </blist> <blist> <bibl id="bib3" idref="ref95" type="bt">3</bibl> <bibtext> American Association of Community Colleges. (2000). History of the association, the twenty-first-century community college. Retrieved from https://education.stateuniversity.com/pages/1753/American-Association-Community-Colleges.html</bibtext> </blist> <blist> <bibl id="bib4" idref="ref51" type="bt">4</bibl> <bibtext> Bahr, P. R., Jackson, G., McNaughtan, J., Oster, M., & Gross, J. (2017). Unrealized potential: Community college pathways to STEM baccalaureate degrees. The Journal of Higher Education, 88 (3), 430 – 478. https://doi.org/10.1080/00221546.2016.1257313</bibtext> </blist> <blist> <bibl id="bib5" idref="ref75" type="bt">5</bibl> <bibtext> Bettinger, E. P., & Long, B. T. (2005). Do faculty serve as role models? The impact of instructor gender on female students. American Economic Review, 95 (2), 152 – 157. https://doi.org/10.1257/000282805774670149</bibtext> </blist> <blist> <bibl id="bib6" idref="ref70" type="bt">6</bibl> <bibtext> Borman, K. M., Eitle, T. M., Michael, D., Eitle, D. J., Lee, R., Johnson, L., & Shircliffe, B. (2004). Accountability in a postdesegregation era: The continuing significance of racial segregation in Florida's schools. American Educational Research Journal, 41 (3), 605 – 631. https://doi.org/10.3102/00028312041003605</bibtext> </blist> <blist> <bibl id="bib7" idref="ref31" type="bt">7</bibl> <bibtext> Bottia, M. C., Mickelson, R., Giersch, J., Stearns, E., & Moller, S. (2018). The role of high school racial composition and opportunities to learn in students' STEM college participation. Journal of Research in Science Teaching, 55 (3), 446 – 473. https://doi.org/10.1002/tea.21426</bibtext> </blist> <blist> <bibl id="bib8" idref="ref30" type="bt">8</bibl> <bibtext> Bottia, M. C., Stearns, E., Mickelson, R. A., Moller, S., & Parker, A. (2015a). The relationships among high school STEM learning experiences and students' intent to declare and declaration of a STEM major in college. Teachers College Record, 17 (3), 1 – 46. https://<ulink href="http://www.tcrecord.org/Content.asp?ContentId=17806">www.tcrecord.org/Content.asp?ContentId=17806</ulink></bibtext> </blist> <blist> <bibl id="bib9" idref="ref40" type="bt">9</bibl> <bibtext> Bottia, M. C., Stearns, E., Mickelson, R. A., Moller, S., & Valentino, L. (2015b). Growing the roots of STEM majors: Female math and science high school faculty and the participation of students in STEM. Economics of Education Review, 45, 14 – 27. https://doi.org/10.1016/j.econedurev.2015.01.002</bibtext> </blist> <blist> <bibtext> Bourdieu, P. (1986). The forms of capital. In J. Richardson (Ed.), Handbook of Theory and Research for the Sociology of Education (pp. 241–258). New York: Greenwood.</bibtext> </blist> <blist> <bibtext> Brint, S., & Karabel, J. (1989). The diverted dream: Community colleges and the promise of educational opportunity in America, 1900–1985. Oxford University Press.</bibtext> </blist> <blist> <bibtext> Cabrera, A. F., & La Nasa, S. M. (2001). On the path to college: Three critical tasks facing America's disadvantaged. Research in Higher Education, 42 (2), 119 – 149. https://doi.org/10.1023/A:1026520002362</bibtext> </blist> <blist> <bibtext> Chang, M. J., Sharkness, J., Hurtado, S., & Newman, C. B. (2014). What matters in college for retaining aspiring scientists and engineers from underrepresented racial groups. Journal of Research in Science Teaching, 51 (5), 555 – 580. https://doi.org/10.1002/tea.v51.5</bibtext> </blist> <blist> <bibtext> Clark, B. R. (1960). The "Cooling-out" function in higher education. American Journal of Sociology, 65 (6), 569 – 576. https://doi.org/10.1086/222787</bibtext> </blist> <blist> <bibtext> Clotfelter, C. T., Ladd, H. F., Muschkin, C. G., & Vigdor, J. L. (2013). Success in community college: Do institutions differ? Research in Higher Education, 54 (7), 805 – 824. https://doi.org/10.1007/s11162-013-9295-6</bibtext> </blist> <blist> <bibtext> DiPrete, T. A., & Eirich, G. M. (2006). Cumulative advantage as a mechanism for inequality: A review of theoretical and empirical developments. Annual Review of Sociology, 32 (1), 271 – 297. https://doi.org/10.1146/annurev.soc.32.061604.123127</bibtext> </blist> <blist> <bibtext> Doyle, W. R. (2009). The effect of community college enrollment on bachelor's degree completion. Economics of Education Review, 28 (2), 199 – 206. https://doi.org/10.1016/j.econedurev.2008.01.006</bibtext> </blist> <blist> <bibtext> Engberg, M. E., & Wolniak, G. C. (2013). College student pathways to the STEM disciplines. Teachers College Record, 115 (1), 1 – 27. <ulink href="http://www.tcrecord.org.eu1.proxy.openathens.net/library/content.asp?contentid=16740">http://www.tcrecord.org.eu1.proxy.openathens.net/library/content.asp?contentid=16740</ulink></bibtext> </blist> <blist> <bibtext> Erola, J., Jalonen, S., & Lehti, H. (2016). Parental education, class and income over early life course and children's achievement. Research in Social Stratification and Mobility, 44, 33 – 43. https://doi.org/10.1016/j.rssm.2016.01.003</bibtext> </blist> <blist> <bibtext> Galotti, K. M., & Mark, M. C. (1994). How do high school students structure an important life decision? A short-term longitudinal study of the college decision-making process. Research in Higher Education, 35 (5), 589 – 607. https://doi.org/10.1007/BF02497089</bibtext> </blist> <blist> <bibtext> Grilli, L., & Rampichini, C. (2006). A review of random effects modelling using gllamm in Stata. Department of Statistics, University of Florence.</bibtext> </blist> <blist> <bibtext> Hanushek, E. A., Kain, J. F., & Rivkin, S. G. (2009). New evidence about Brown v. Board of Education: The complex effects of school racial composition on achievement. Journal of Labor Economics, 27 (3), 349 – 383. https://doi.org/10.1086/600386</bibtext> </blist> <blist> <bibtext> Hilmer, M. J. (1998). Post-secondary fees and the decision to attend a university or a community college. Journal of Public Economics, 67 (3), 329 – 348. https://doi.org/10.1016/S0047-2727(97)00075-3</bibtext> </blist> <blist> <bibtext> LaSota, R. R., & Zumeta, W. (2016). What matters in increasing community college students' upward transfer to the baccalaureate degree: Findings from the beginning postsecondary study 2003–2009. Research in Higher Education, 57 (2), 152 – 189. https://doi.org/10.1007/s11162-015-9381-z</bibtext> </blist> <blist> <bibtext> Leigh, D. E., & Gill, A. M. (2003). Do community colleges really divert students from earning bachelor's degrees? Economics of Education Review, 22 (1), 23 – 30. https://doi.org/10.1016/S0272-7757(01)00057-7</bibtext> </blist> <blist> <bibtext> Lleras, C. (2008). Hostile school climates: Explaining differential risk of student exposure to disruptive learning environments in high school. Journal of School Violence, 7 (3), 105 – 135. https://doi.org/10.1080/15388220801955604</bibtext> </blist> <blist> <bibtext> Ma, Y. (2009). Family socioeconomic status, parental involvement, and college major choices—Gender, race/ ethnic,and nativity patterns. Sociological Perspectives, 52 (2), 211 – 234. https://doi.org/10.1525/sop.2009.52.2.211</bibtext> </blist> <blist> <bibtext> Malcom, L. E., & Dowd, A. C. (2012). The impact of undergraduate debt on the graduate school enrollment of STEM baccalaureates. The Review of Higher Education, 35 (2), 265 – 305. https://doi.org/10.1353/rhe.2012.0007</bibtext> </blist> <blist> <bibtext> Maltese, A. V., & Tai, R. H. (2011). Pipeline persistence: Examining the association of educational experiences with earned degrees in STEM among US students. Science Education, 95 (5), 877 – 907. https://doi.org/10.1002/sce.v95.5</bibtext> </blist> <blist> <bibtext> Merton, R. K. (1968). The Matthew effect in science: The reward and communication systems of science are considered. Science, 159 (3810), 56 – 63. https://doi.org/10.1126/science.159.3810.56</bibtext> </blist> <blist> <bibtext> Mickelson, R. A. (2015). The cumulative disadvantages of first- and second-generation segregation for middle school achievement. American Educational Research Journal, 52 (4), 657 – 692. https://doi.org/10.3102/0002831215587933</bibtext> </blist> <blist> <bibtext> Mickelson, R. A., Bottia, M. C., & Lambert, R. (2013). Effects of school racial composition on K–12 mathematics outcomes: A metaregression analysis. Review of Educational Research, 83 (1), 121 – 158. https://doi.org/10.3102/0034654312475322</bibtext> </blist> <blist> <bibtext> Monaghan, D. B., & Attewell, P. (2015). The community college route to the bachelor's degree. Educational Evaluation and Policy Analysis, 37 (1), 70 – 91. https://doi.org/10.3102/0162373714521865</bibtext> </blist> <blist> <bibtext> Montmarquette, C., Cannings, K., & Mahseredjian, S. (2002). How do young people choose college majors? Economics of Education Review, 21 (6), 543 – 556. https://doi.org/10.1016/S0272-7757(01)00054-1</bibtext> </blist> <blist> <bibtext> Mooney, G. M., & Foley, D. J. (2011). Community colleges: Playing an important role in the education of science, engineering, and health graduates. National Center for Science and Engineering Statistics, NSF 11-317.</bibtext> </blist> <blist> <bibtext> Moschetti, R., & Hudley, C. (2008). Measuring social capital among first-generation and non-first-generation, working-class, white males. Journal of College Admission, 198, 25 – 30.</bibtext> </blist> <blist> <bibtext> National Science Board. (2014). Higher education in science and education. In Science and engineering indicators. National Science Foundation.</bibtext> </blist> <blist> <bibtext> National Science Foundation. (2013). Women, minorities, and persons with disabilities in science and engineering: 2013 (Special Report NSF 13-304).</bibtext> </blist> <blist> <bibtext> Oakes, J. (2005). Keeping track. Yale University Press.</bibtext> </blist> <blist> <bibtext> Pascarella, E. T., Pierson, C. T., Wolniak, G. C., & Terenzini, P. T. (2004). First-generation college students: Additional evidence on college experiences and outcomes. The Journal of Higher Education, 75 (3), 249 – 284.</bibtext> </blist> <blist> <bibtext> Pearson, W., Jr, & Miller, J. D. (2012). Pathways to an engineering career. Peabody Journal of Education, 87 (1), 46 – 61. https://doi.org/10.1080/0161956X.2012.642270</bibtext> </blist> <blist> <bibtext> Perez-Felkner, L., Thomas, K., Nix, S., Hopkins, J., & D'Sa, M. (2019). Are 2-year colleges the key? Institutional variation and the gender gap in undergraduate STEM degrees. The Journal of Higher Education, 90 (2), 181 – 209. https://doi.org/10.1080/00221546.2018.1486641</bibtext> </blist> <blist> <bibtext> Perna, L. W. (2006). Studying college access and choice: A proposed conceptual model. In J. C. Smart (Ed.), Higher Education: Handbook of Theory and Research (pp. 99 – 157). Dordrecht: Springer Science & Business Media.</bibtext> </blist> <blist> <bibtext> Perna, L. W., & Titus, M. A. (2005). The relationship between parental involvement as social capital and college enrollment: An examination of racial/ethnic group differences. Journal of Higher Education, 76 (5), 485 – 518. https://doi.org/10.1353/jhe.2005.0036</bibtext> </blist> <blist> <bibtext> Provasnik, S., & Planty, M. (2008). Community colleges: Special supplement to the condition of education 2008 Statistical analysis report (NCES 2008-033). National Center for Education Statistics.</bibtext> </blist> <blist> <bibtext> Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. SAGE Publications.</bibtext> </blist> <blist> <bibtext> Reardon, S. F. (2016). School segregation and racial academic achievement gaps. RSF: The Russell Sage Foundation Journal of the Social Sciences, 2 (5), 34 – 57. https://doi.org/10.7758/rsf.2016.2.5.03</bibtext> </blist> <blist> <bibtext> Reardon, S. F., Cheadle, J. E., & Robinson, J. P. (2009). The effects of Catholic school attendance on reading and math achievement in kindergarten through fifth grade. Journal of Research on Educational Effectiveness, 2 (1), 45 – 87. https://doi.org/10.1080/19345740802539267</bibtext> </blist> <blist> <bibtext> Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experi-mental designs for generalized causal inference. Houghton Mifflin.</bibtext> </blist> <blist> <bibtext> Stanton-Salazar, R. (1997). A social capital framework for understanding the socialization of racial minority children and youths. Harvard Educational Review, 67 (1), 1 – 40. https://doi.org/10.17763/haer.67.1.140676g74018u73k</bibtext> </blist> <blist> <bibtext> Stearns, E., Bottía, M. C., Davalos, E., Mickelson, R. A., Moller, S., & Valentino, L. (2016). Demographic characteristics of high school math and science teachers and girls' success in STEM. Social Problems, 63 (1), 87 – 110. https://doi.org/10.1093/socpro/spv027</bibtext> </blist> <blist> <bibtext> Stearns, E., Mickelson, R. A., Moller, S., & Bottia, M. S. (2013). Training tool and codebook ROOTS of STEM: A dataset on students who attended North Carolina public schools, grades 6 through 16. Unpublished document.</bibtext> </blist> <blist> <bibtext> Steiner, P. M., & Cook, D. (2013). Matching and propensity scores. In T. D. Little (Ed.), The Oxford handbook of quantitative methods (pp. 237–259). New York, NY: Oxford University Press.</bibtext> </blist> <blist> <bibtext> Stephens, N. M., Fryberg, S. A., Markus, H. R., Johnson, C. S., & Covarrubias, R. (2012). Unseen disadvantage: How American universities' focus on independence undermines the academic performance of first-generation college students. Journal of Personality and Social Psychology, 102 (6), 1178 – 1197. https://doi.org/10.1037/a0027143</bibtext> </blist> <blist> <bibtext> Tierney, W. G., & Venegas, K. M. (2009). Finding money on the table: Information, financial aid, and access to college. The Journal of Higher Education, 80 (4), 363 – 388. https://doi.org/10.1080/00221546.2009.11779021</bibtext> </blist> <blist> <bibtext> Townsend, B. K., & Dever, J. T. (1999). What do we know about reverse transfer students? New Directions for Community Colleges, ((106)), 5 – 14. https://doi.org/10.1002/cc.10601</bibtext> </blist> <blist> <bibtext> Wang, X. (2013a). Modeling entrance into STEM fields of study among students beginning at community colleges and four-year institutions. Research in Higher Education, 54 (6), 664 – 692. https://doi.org/10.1007/s11162-013-9291-x</bibtext> </blist> <blist> <bibtext> Wang, X. (2013b). Why students choose STEM majors motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50 (5), 1081 – 1121. https://doi.org/10.3102/0002831213488622</bibtext> </blist> <blist> <bibtext> Wang, X. (2015). Pathway to a baccalaureate in STEM fields are community colleges a viable route and does early STEM Momentum matter? Educational Evaluation and Policy Analysis, 37 (3), 376 – 393. https://doi.org/10.3102/0162373714552561</bibtext> </blist> <blist> <bibtext> Wang, X., Lee, Y., & Wickersham, K. (2019). The role of community college attendance in shaping baccalaureate recipients' access to graduate and professional education. Educational Researcher, 48 (2), 84 – 100. https://doi.org/10.3102/0013189X19825659</bibtext> </blist> <blist> <bibtext> Weidman, J. (1989). Undergraduate socialization: A conceptual approach. Higher Education: Handbook of Theory and Research, 5 (2), 289 – 322.</bibtext> </blist> <blist> <bibtext> Xie, Y., Fang, M., & Shauman, K. (2015). Stem Education. Annual Review of Sociology, 41 (1), 331 – 357. https://doi.org/10.1146/annurev-soc-071312-145659</bibtext> </blist> <blist> <bibtext> Zhang, Y. L., Adamuti-Trache, M., & Connolly, J. (2019). From community college attendants to baccalaureate recipients: A planned behavior model for transfer students in STEM fields of study. The Journal of Higher Education, 90 (3), 373 – 401. https://doi.org/10.1080/00221546.2018.1536935</bibtext> </blist> </ref> <aug> <p>By Martha Cecilia Bottia; Elizabeth Stearns; Roslyn Arlin Mickelson; Stephanie Moller and Cayce Jamil</p> <p>Reported by Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib38" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib62" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib56" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib59" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib28" firstref="ref5"></nolink> <nolink nlid="nl6" bibid="bib17" firstref="ref6"></nolink> <nolink nlid="nl7" bibid="bib60" firstref="ref7"></nolink> <nolink nlid="nl8" bibid="bib57" firstref="ref8"></nolink> <nolink nlid="nl9" bibid="bib42" firstref="ref10"></nolink> <nolink nlid="nl10" bibid="bib45" firstref="ref11"></nolink> <nolink nlid="nl11" bibid="bib55" firstref="ref12"></nolink> <nolink nlid="nl12" bibid="bib23" firstref="ref14"></nolink> <nolink nlid="nl13" bibid="bib16" firstref="ref15"></nolink> <nolink nlid="nl14" bibid="bib30" firstref="ref16"></nolink> <nolink nlid="nl15" bibid="bib20" firstref="ref17"></nolink> <nolink nlid="nl16" bibid="bib34" firstref="ref18"></nolink> <nolink nlid="nl17" bibid="bib12" firstref="ref19"></nolink> <nolink nlid="nl18" bibid="bib43" firstref="ref20"></nolink> <nolink nlid="nl19" bibid="bib10" firstref="ref22"></nolink> <nolink nlid="nl20" bibid="bib19" firstref="ref23"></nolink> <nolink nlid="nl21" bibid="bib44" firstref="ref24"></nolink> <nolink nlid="nl22" bibid="bib54" firstref="ref25"></nolink> <nolink nlid="nl23" bibid="bib50" firstref="ref26"></nolink> <nolink nlid="nl24" bibid="bib31" firstref="ref27"></nolink> <nolink nlid="nl25" bibid="bib39" firstref="ref29"></nolink> <nolink nlid="nl26" bibid="bib13" firstref="ref32"></nolink> <nolink nlid="nl27" bibid="bib18" firstref="ref33"></nolink> <nolink nlid="nl28" bibid="bib27" firstref="ref34"></nolink> <nolink nlid="nl29" bibid="bib29" firstref="ref35"></nolink> <nolink nlid="nl30" bibid="bib58" firstref="ref36"></nolink> <nolink nlid="nl31" bibid="bib51" firstref="ref46"></nolink> <nolink nlid="nl32" bibid="bib32" firstref="ref47"></nolink> <nolink nlid="nl33" bibid="bib47" firstref="ref48"></nolink> <nolink nlid="nl34" bibid="bib63" firstref="ref49"></nolink> <nolink nlid="nl35" bibid="bib61" firstref="ref50"></nolink> <nolink nlid="nl36" bibid="bib35" firstref="ref53"></nolink> <nolink nlid="nl37" bibid="bib24" firstref="ref57"></nolink> <nolink nlid="nl38" bibid="bib14" firstref="ref61"></nolink> <nolink nlid="nl39" bibid="bib37" firstref="ref65"></nolink> <nolink nlid="nl40" bibid="bib52" firstref="ref66"></nolink> <nolink nlid="nl41" bibid="bib41" firstref="ref67"></nolink> <nolink nlid="nl42" bibid="bib36" firstref="ref68"></nolink> <nolink nlid="nl43" bibid="bib40" firstref="ref69"></nolink> <nolink nlid="nl44" bibid="bib22" firstref="ref73"></nolink> <nolink nlid="nl45" bibid="bib26" firstref="ref74"></nolink> <nolink nlid="nl46" bibid="bib46" firstref="ref76"></nolink> <nolink nlid="nl47" bibid="bib21" firstref="ref77"></nolink> <nolink nlid="nl48" bibid="bib53" firstref="ref78"></nolink> <nolink nlid="nl49" bibid="bib48" firstref="ref79"></nolink> <nolink nlid="nl50" bibid="bib49" firstref="ref81"></nolink> <nolink nlid="nl51" bibid="bib33" firstref="ref82"></nolink> <nolink nlid="nl52" bibid="bib15" firstref="ref89"></nolink> <nolink nlid="nl53" bibid="bib25" firstref="ref92"></nolink> <nolink nlid="nl54" bibid="bib11" firstref="ref93"></nolink>
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  Data: The Importance of Community Colleges in Students' Choice to Major in STEM
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  Data: <searchLink fieldCode="AR" term="%22Bottia%2C+Martha+Cecilia%22">Bottia, Martha Cecilia</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-5150-520X">0000-0001-5150-520X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Stearns%2C+Elizabeth%22">Stearns, Elizabeth</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-9678-2160">0000-0002-9678-2160</externalLink>)<br /><searchLink fieldCode="AR" term="%22Mickelson%2C+Roslyn+Arlin%22">Mickelson, Roslyn Arlin</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-2578-0659">0000-0003-2578-0659</externalLink>)<br /><searchLink fieldCode="AR" term="%22Moller%2C+Stephanie%22">Moller, Stephanie</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-8239-719X">0000-0002-8239-719X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jamil%2C+Cayce%22">Jamil, Cayce</searchLink>
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: <searchLink fieldCode="DE" term="%22North+Carolina%22">North Carolina</searchLink>
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  Data: 10.1080/00221546.2020.1742032
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  Data: 0022-1546
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  Label: Abstract
  Group: Ab
  Data: This article investigates whether attending a community college is related to an increase in the number of students majoring and graduating with degrees in science, technology, engineering and mathematics (STEM) at four-year colleges. We follow a longitudinal sample of students in North Carolina from middle school through college graduation, including some who attended a community college. Our multilevel models indicate that for our sample of students, who attended a four-year institution and declared a major within 6 years of high school graduation, ever attending a community college and/or starting post-secondary education at a community college have a significant positive relationship with their likelihood of declaring and graduating with a STEM major. Results hold true even after controlling for sample self-selection through propensity score matching techniques. Our findings also show that the benefits of community college attendance on students' likelihood of declaring and graduating with a STEM major are not restricted to only low-SES students. Overall, this study supports the notion that two-year colleges could work as means of helping push students from diverse socioeconomic backgrounds into STEM.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2020
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1271732
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1271732
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/00221546.2020.1742032
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 33
        StartPage: 1116
    Subjects:
      – SubjectFull: Community Colleges
        Type: general
      – SubjectFull: College Attendance
        Type: general
      – SubjectFull: Majors (Students)
        Type: general
      – SubjectFull: STEM Education
        Type: general
      – SubjectFull: Longitudinal Studies
        Type: general
      – SubjectFull: High School Graduates
        Type: general
      – SubjectFull: State Universities
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: College Transfer Students
        Type: general
      – SubjectFull: First Generation College Students
        Type: general
      – SubjectFull: Economically Disadvantaged
        Type: general
      – SubjectFull: Socioeconomic Status
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Graduation Rate
        Type: general
      – SubjectFull: Educational Attainment
        Type: general
      – SubjectFull: North Carolina
        Type: general
    Titles:
      – TitleFull: The Importance of Community Colleges in Students' Choice to Major in STEM
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Bottia, Martha Cecilia
      – PersonEntity:
          Name:
            NameFull: Stearns, Elizabeth
      – PersonEntity:
          Name:
            NameFull: Mickelson, Roslyn Arlin
      – PersonEntity:
          Name:
            NameFull: Moller, Stephanie
      – PersonEntity:
          Name:
            NameFull: Jamil, Cayce
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2020
          Identifiers:
            – Type: issn-print
              Value: 0022-1546
          Numbering:
            – Type: volume
              Value: 91
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: Journal of Higher Education
              Type: main
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