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Changing Course: The Gender Gap in College Selectivity and Opportunities to Learn in the High School Curriculum

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Title: Changing Course: The Gender Gap in College Selectivity and Opportunities to Learn in the High School Curriculum
Language: English
Authors: Moller, Stephanie, Stearns, Elizabeth, Southworth, Stephanie, Potochnick, Stephanie
Source: Gender and Education. 2013 25(7):851-871.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 21
Publication Date: 2013
Document Type: Journal Articles
Reports - Research
Education Level: High Schools
Higher Education
Postsecondary Education
Descriptors: Gender Differences, Longitudinal Studies, Selective Admission, Academic Achievement, Advanced Placement, High School Students, Prediction, Admission Criteria, Educational Opportunities, Institutional Characteristics, Socioeconomic Status, Outcomes of Education, Regression (Statistics)
Assessment and Survey Identifiers: SAT (College Admission Test)
DOI: 10.1080/09540253.2013.853028
ISSN: 0954-0253
Abstract: Gender gaps in learning and education outcomes have changed dramatically over the last few years. However, researchers have not adequately assessed how the high school learning environment differentially affects boys and girls. An important component of the learning environment in US secondary school is the opportunity to learn in an Advanced Placement (AP) curriculum, which allows high school students to do college-level work. Using the US National Education Longitudinal Study 1988-2000, we explain how high school AP curriculum interacts with gender to predict the selectivity of colleges that students attend. The results show that girls and boys who attend high schools with a larger percentage of students in AP curriculum attend more selective colleges (that require higher standardised scores for admissions); yet the positive effect of the opportunity to learn in an AP curriculum is greater for girls than for boys. This research furthers the debate about the effects of school structure on gender stratification.
Abstractor: As Provided
Number of References: 72
Entry Date: 2014
Accession Number: EJ1021105
Database: ERIC
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  Value: <anid>AN0092943010;gae01dec.13;2019Feb21.13:13;v2.2.500</anid> <title id="AN0092943010-1">Changing course: the gender gap in college selectivity and opportunities to learn in the high school curriculum. </title> <p>Gender gaps in learning and education outcomes have changed dramatically over the last few years. However, researchers have not adequately assessed how the high school learning environment differentially affects boys and girls. An important component of the learning environment in US secondary school is the opportunity to learn in an Advanced Placement (AP) curriculum, which allows high school students to do college-level work. Using the US National Education Longitudinal Study 1988–2000, we explain how high school AP curriculum interacts with gender to predict the selectivity of colleges that students attend. The results show that girls and boys who attend high schools with a larger percentage of students in AP curriculum attend more selective colleges (that require higher standardised scores for admissions); yet the positive effect of the opportunity to learn in an AP curriculum is greater for girls than for boys. This research furthers the debate about the effects of school structure on gender stratification.</p> <p>Keywords: sociology; secondary education; higher education; girls</p> <p>Gender inequality in education has increasingly captivated the attention of researchers as women have begun to outpace men in secondary school achievement and post-secondary admissions and completion (Buchmann and DiPrete [<reflink idref="bib12" id="ref1">12</reflink>]). Accounts in the international media over the last two decades have reframed gender inequality in education from historical concerns over girls' relatively low achievement to a panic over boys' relatively low achievement and post-secondary educational attainment (Epstein et al. [<reflink idref="bib23" id="ref2">23</reflink>]). The new gender inequality imagery portrays the successful girl on the back of the failing boy. This panic has helped generate disparities in research funding in many countries because studies that emphasise the needs of boys are valued over similar studies focused on girls (Ringrose [<reflink idref="bib58" id="ref3">58</reflink>]). It has also created a political environment where feminists seemingly won their ongoing battle to attain gender equality in education and where the perceived need for feminist discourse is becoming obsolete (Pomerantz and Raby [<reflink idref="bib54" id="ref4">54</reflink>]). Yet, we propose that this imagery and these conclusions are inaccurate. In fact, we will argue that girls remain more vulnerable to some structural conditions than boys. As a result, researchers and policy-makers must thoroughly assess the gendered effects of educational structures – emphasising the effects on both boys and girls.</p> <p>We illustrate this point with research on students in the USA. One trend in the US educational system has been to expand the offering of rigorous coursework to secondary school students. The importance of academic rigour has been magnified since the end of the twentieth century as scholars and policy-makers became cognizant of the changing educational demands of the knowledge-based economy. The most rigorous coursework in the USA is often found in Advanced Placement (AP) courses, or post-secondary level courses taught in secondary school. Students who complete these courses are more likely to attend and graduate from post-secondary institutions (Moller et al. [<reflink idref="bib49" id="ref5">49</reflink>]; Stearns et al. [<reflink idref="bib66" id="ref6">66</reflink>]; Stearns, Jha, and Potochnick [<reflink idref="bib65" id="ref7">65</reflink>]). Yet, we do not know if this process is gendered. Therefore, we ask the question 'Does studying in a school with a broader AP curriculum have differential effects on boys and girls?'</p> <p>It is important to understand better how aspects of schools differentially affect post-secondary educational outcomes for boys and girls because girls have historically been less likely to attend selective colleges than boys (Buchmann and DiPrete [<reflink idref="bib12" id="ref8">12</reflink>]; Hearn [<reflink idref="bib30" id="ref9">30</reflink>]; Jacobs [<reflink idref="bib34" id="ref10">34</reflink>]), although today the gender distributions at many of the United States' most selective colleges are at or near parity (for example, at Duke, Harvard, Princeton, Stanford). There is limited research on gendered differences in college selectivity, as much of the extant literature explores why gender gaps in post-secondary educational attainment, in general, have shifted. These scholars focus on a variety of factors, including changes in gender roles, gendered attitudes and labour market opportunities that have altered both returns to masculine and feminine behaviour inside schools and gendered educational aspirations (Brewster and Padavic [<reflink idref="bib9" id="ref11">9</reflink>]; Brooks and Bolzendahl [<reflink idref="bib10" id="ref12">10</reflink>]; Buchmann and Dalton [<reflink idref="bib11" id="ref13">11</reflink>]; Buchmann, DiPrete, and McDaniel [<reflink idref="bib13" id="ref14">13</reflink>]; Jacob [<reflink idref="bib33" id="ref15">33</reflink>]). Yet, limited research has examined how secondary schools shape the selectivity of colleges that students attend. We expand on the literature by illustrating how opportunities to learn in an AP curriculum shape gender gaps in college selectivity. We demonstrate this association with multi-level modelling of data from the United States' National Education Longitudinal Study (1988–2000) (NELS), a nationally representative sample of eighth graders (around age 15) who are followed into young adulthood.</p> <hd id="AN0092943010-2">Schooling in the USA</hd> <p>Secondary school students in the USA have access to a wide variety of courses, but the rigour of the courses varies across schools. In 1955, some secondary schools began offering college-level courses, called AP courses, to their brightest students. Students who score highly on an exam at the conclusion of the course can count the course toward college credit. In 1955, only 104 high schools offered AP courses. By the turn of the century, more than half of US high schools offered AP courses to some of their students (The College Board [<reflink idref="bib67" id="ref16">67</reflink>]). There remains tremendous variability across secondary schools in the percentage of the student body that takes these courses. When the share of the student body taking AP courses is larger, a more rigorous curriculum is offered to a broader set of students.</p> <p>We investigate AP course-taking specifically because these courses are attractive to colleges' admissions committees, and the most selective colleges admit students with the highest scores. In addition, families have turned to rankings of US high schools that use AP curriculum as a foundational component of the ranking. Indeed, the availability of a rigorous curriculum to more students is an important part of the measurement of secondary school quality in the USA developed by Jay Mathews ([<reflink idref="bib46" id="ref17">46</reflink>]) and published annually in <emph>Newsweek</emph>. This measure, entitled the Challenge Index, has become the standard tool in the media – one that has been embraced by US parents – for ranking US high schools. It is defined as the percentage of graduating seniors who take AP and International Baccalaureate tests.[<reflink idref="bib1" id="ref18">1</reflink>] Mathews contends that the index reflects schools' efforts to expose students to challenging curriculum. It presumably gauges how well schools prepare students for post-secondary education. Indeed, 'star' high schools are nationally recognised for their effectiveness at placing students in the most selective post-secondary institutions (Mathews [<reflink idref="bib45" id="ref19">45</reflink>]).</p> <p>Post-secondary educational stratification generates long-term social stratification for the students who attend them, and for the society in which they are located. This stratification has long-term implications for social inequality. Many scholars contend that college prestige and selectivity influence the later opportunities and rewards that graduates will attain, including income and occupational status (Brewer, Eide, and Ehrenberg [<reflink idref="bib8" id="ref20">8</reflink>]; James et al. [<reflink idref="bib35" id="ref21">35</reflink>]; Monks [<reflink idref="bib50" id="ref22">50</reflink>]; Seymour and Lunde [<reflink idref="bib62" id="ref23">62</reflink>]; Thomas [<reflink idref="bib68" id="ref24">68</reflink>]; Trusheim and Crouse [<reflink idref="bib69" id="ref25">69</reflink>]).[<reflink idref="bib2" id="ref26">2</reflink>] Post-secondary institutions in the USA offer students status affiliations, and they are important locations for students to develop networks, both of weak ties of acquaintances that may help their future careers and of stronger ties that include friends and marriage partners (Granovetter [<reflink idref="bib27" id="ref27">27</reflink>]; Kanter [<reflink idref="bib36" id="ref28">36</reflink>]; Seymour and Lunde [<reflink idref="bib62" id="ref29">62</reflink>]). Admission to an elite institution is truly a valued and valuable reward for students in the USA.</p> <hd id="AN0092943010-3">Gender and academic outcomes</hd> <p>Post-secondary gender inequality has increasingly captivated the attention of researchers because women have attained parity in college admissions and completion, and even exceeded men in some domains (Buchmann and DiPrete [<reflink idref="bib12" id="ref30">12</reflink>]). We focus on the particular role of secondary schools in shaping the selectivity of colleges that men and women attend because scholars have clearly established that secondary schools offer students different opportunities to learn, and these opportunities either constrain or enhance students' learning outcomes. Yet the new gender political discourse in many countries suggests that concerns with girls' educational attainment are passé. Girls are perceived to no longer face structural constraints to academic success, implying that their success or failure results from individual actions (Pomerantz and Raby [<reflink idref="bib54" id="ref31">54</reflink>]; Ringrose [<reflink idref="bib58" id="ref32">58</reflink>]).[<reflink idref="bib3" id="ref33">3</reflink>]</p> <p>Structural theorists and gender theorists, of course, would baulk at this suggestion. Some schools have an environment in which more students are offered educational opportunities <emph>and</emph> where more students are encouraged and expected to take advantage of those opportunities. Offering a rigorous curriculum in public schools has implications for students, and we posit that there should be gender differences in outcomes depending on the percentage of students enrolled in AP courses.[<reflink idref="bib4" id="ref34">4</reflink>]</p> <p>We take this position because gender is socially constructed and contextually influenced (Connell [<reflink idref="bib16" id="ref35">16</reflink>]; Connell and Messerschmidt [<reflink idref="bib17" id="ref36">17</reflink>]; Mac an Ghaill [<reflink idref="bib42" id="ref37">42</reflink>]; Paechter [<reflink idref="bib53" id="ref38">53</reflink>]; Weaver-Hightower [<reflink idref="bib72" id="ref39">72</reflink>]). Indeed, boys and girls enter high schools as gendered bodies. Boys are more likely to portray masculine behaviour that includes competition and aspirations toward success (Warrington and Younger [<reflink idref="bib71" id="ref40">71</reflink>]). Dominant forms of masculinity, however, do not include studious behaviour (Lusher [<reflink idref="bib41" id="ref41">41</reflink>]). In contrast, girls are more likely to portray forms of femininity that include the valuation of close personal relationships (Lusher [<reflink idref="bib41" id="ref42">41</reflink>]). Girls also have more fragile academic identities in some domains that are heavily influenced by peers and broader social networks (Crosnoe, Riegle-Crumb, and Muller [<reflink idref="bib19" id="ref43">19</reflink>]; Crosnoe et al. [<reflink idref="bib18" id="ref44">18</reflink>]; Solomon, Lawson, and Croft [<reflink idref="bib64" id="ref45">64</reflink>]).</p> <p>At the same time, girls are also more likely to portray more academically oriented behaviours. Indeed, some scholars have suggested that behaviours associated with these gender differences explain gaps in college enrolment. Girls are more likely to enrol in college because they are more engaged in academics, they enrol in more rigorous courses, they have higher grades, and they score higher on achievement tests (Buchmann, DiPrete, and McDaniel [<reflink idref="bib13" id="ref46">13</reflink>]; Cho [<reflink idref="bib15" id="ref47">15</reflink>]; Goldin [<reflink idref="bib26" id="ref48">26</reflink>]; Jacob [<reflink idref="bib33" id="ref49">33</reflink>]). Indeed, girls outperform boys on a number of factors that are attractive to colleges (Buchmann, DiPrete, and McDaniel [<reflink idref="bib13" id="ref50">13</reflink>]). They participate in more cultural and extracurricular activities; they take more AP courses; and they score higher on AP exams (Bae et al. [<reflink idref="bib3" id="ref51">3</reflink>]; Dumais [<reflink idref="bib22" id="ref52">22</reflink>]). Each of these characteristics is indicative of academically-oriented femininity.</p> <p>It is also important to remember that as socially constructed identities, masculinity and femininity are contextually influenced, and the association between masculinity, femininity and student outcomes are also contextually specific (Lusher [<reflink idref="bib41" id="ref53">41</reflink>]; Weaver-Hightower [<reflink idref="bib72" id="ref54">72</reflink>]). Contextually, we contend that schools with a broader AP curriculum should disproportionately benefit girls because girls' decision-making is more heavily influenced by peers and social contexts (Crosnoe, Riegle-Crumb, and Muller [<reflink idref="bib19" id="ref55">19</reflink>]; Crosnoe et al. [<reflink idref="bib18" id="ref56">18</reflink>]; Han and Li [<reflink idref="bib29" id="ref57">29</reflink>]) and schools with a broader AP curriculum have a stronger academic press, as more students take rigorous courses. Therefore, students in these schools have access to a network of weak ties where academic rigour is more normative. Prior research (focused on peers in courses) has established that the academic press of the social context affects girls' self-perceptions, especially in the midst of failure, but this academic press is irrelevant to boys' self-perceptions (Crosnoe, Riegle-Crumb, and Muller [<reflink idref="bib19" id="ref58">19</reflink>]). Additionally, researchers have found that girls have higher achievement when course-mates (conceptualised as their weak ties) have higher achievement and when average achievement in the school is higher; the same is not true for boys (Crosnoe et al. [<reflink idref="bib18" id="ref59">18</reflink>]). We generalise this line of research to schools, arguing that when the AP curriculum is more broadly utilised among students in schools, peer networks, including strong (i.e. friends) and weak (i.e. school mates) ties are more academically oriented, and this should benefit girls' post-secondary educational outcomes, but not necessarily boys.</p> <p>If girls' success is also associated with boys' failure then one might also expect that boys could be disadvantaged in these schools. While it is irrational to assume that girls' success is inherently detrimental to boys, it is possible to imagine a scenario in which the social context could complement or reward components of femininity while rejecting or not complementing more masculine characteristics. For example, boys may experience a weakening self-conceptualisation in a more rigorous school because their frame or point of comparison (i.e. the achievement of their peers) becomes more competitive (Catsambis, Mulkey, and Crain [<reflink idref="bib14" id="ref60">14</reflink>]; Marsh et al. [<reflink idref="bib44" id="ref61">44</reflink>]). Some scholars have suggested that boys feel less distinguished when the majority of their peers are students of distinction. As a result, boys may be more likely falter in these environments (Catsambis, Mulkey, and Crain [<reflink idref="bib14" id="ref62">14</reflink>]). Daniels et al. ([<reflink idref="bib20" id="ref63">20</reflink>], 112) aptly describe this phenomenon:</p> <p>Girls seem to be able to succeed, albeit in different ways, in a variety of pedagogic environments. Boys' academic performance may be inhibited in contexts that support and privilege competitions.</p> <p>More inclusive schools with a broader AP curriculum generally offer a more competitive environment (Attewell [<reflink idref="bib2" id="ref64">2</reflink>]). As Attewell ([<reflink idref="bib2" id="ref65">2</reflink>], 267–268) notes, 'star high schools are caught in an assessment system in which top students vie for entry into selective colleges. Many [secondary] schools adapt to this system, seeking to maximise the chances of their strongest students'. In so doing, Attewell ([<reflink idref="bib2" id="ref66">2</reflink>]) found that these schools amplify stratification between high and low achieving students. In a study of 45,000 applications to three elite universities, Espenshade, Hale, and Chung ([<reflink idref="bib24" id="ref67">24</reflink>]) also find that students are less likely to be accepted to these universities if they are from 'high talent' high schools. This dynamic occurs because talented students from schools with a large pool of talented students are disadvantaged in college admissions relative to talented students from schools with a smaller pool of talented students. Thus, the opportunities provided to students in these schools with many talented students exacerbate inequalities in educational outcomes. This enhanced competition could perceivably diminish boys' self-concepts due to the higher-achieving frames of reference.</p> <p>Yet, returning to conceptualisations of masculinity where competition is central, this seems counterintuitive. Boys are more likely than girls to choose competitive environments, and they are more likely to thrive in these environments (Niederle and Vesterlund [<reflink idref="bib52" id="ref68">52</reflink>]). Thus, while the previous argument seems antithetical to the perception that boys are more competitive than girls, it is an empirical question. Do girls outperform boys in an environment that is more rigorous, and by extension, more competitive?</p> <hd id="AN0092943010-4">Data and methods</hd> <p>We utilise the NELS to examine how high school AP opportunities interact with gender to predict college selectivity in young adulthood. The NELS was conducted by the US Department of Education, National Center for Education Statistics (NCES) and follows a nationally representative sample of US students from the eighth grade (when they are approximately 14 years old) in 1988 to their late twenties in 2000. Data were gathered in 1988, 1990, 1992, 1994, and 2000. This study includes student, teacher, and administrator questionnaires in the eighth, tenth, and twelfth grades, transcript data, and student questionnaires after students complete secondary school (the last year of secondary school is the twelfth grade).</p> <hd id="AN0092943010-5">Dependent variable</hd> <p>Institutional selectivity is gathered from the Post-secondary Education Transcripts Study (PETS), which was conducted at the conclusion of the 2000 wave of NELS. The PETS was designed to capture the characteristics of post-secondary institutions attended by the NELS participants during the third and fourth waves after the students have completed secondary school (i.e. in 1994 and 2000; Adelman et al. [<reflink idref="bib1" id="ref69">1</reflink>]). The PETS includes a variable which characterises four-year post-secondary institutions as highly selective, moderately selective, and nonselective based on the math and verbal Scholastic Aptitude Test (SAT) scores of students in those institutions. The SAT is the most widely used college admissions test in the USA. Therefore, our measure of selectivity reflects average student performance on this test. This variable was originally created by the Higher Education Research Institute through the 1992 Freshman Survey. Highly selective institutions have the highest scores. We include all cases who participated in ranked, four-year post-secondary institutions. This excludes foreign colleges and specialty colleges such as art institutes and beauty colleges (these account for less than 4% of the sample).[<reflink idref="bib5" id="ref70">5</reflink>]</p> <hd id="AN0092943010-6">Primary independent variables</hd> <p>Our primary independent variables of interest are students' gender and the coverage of AP courses in their high schools. Gender is coded 1 for young women. High school AP opportunity is measured as the percentage of twelfth grade students taking at least one AP course. Our operationalisation of AP opportunity differs from that presented by <emph>Newsweek</emph> for two reasons. First, the measure in <emph>Newsweek</emph> is based on the number of AP exams taken in the school. Many schools only allow the highest-performing students to take AP exams in order to keep their scores on those tests high (Mathews [<reflink idref="bib47" id="ref71">47</reflink>]). Second, a small group of students can take many exams, masking the true opportunities available to students.[<reflink idref="bib6" id="ref72">6</reflink>] Therefore, we include a more general measure of AP opportunities, the per cent of twelfth grade students who take AP classes (i.e. the <emph>per cent AP</emph>). Since approximately one-fifth of the schools do not have any students taking AP courses, we also include a control variable measuring whether the school offered AP courses (coded 1 when 0% of students take AP courses in the twelfth grade).</p> <hd id="AN0092943010-7">Individual-level controls</hd> <p>All models control for individual-level variables, including students' race, socio-economic status (SES), age, grades, AP coursework, standardised test scores, and educational expectations. Race is coded as Asian-American, Latino, and African-American (with White as the reference category). Students self-report their gender, race, and their age. We also control for SES because students from lower socioeconomic classes often attend less selective colleges and universities than students from higher socioeconomic classes (Hearn [<reflink idref="bib30" id="ref73">30</reflink>]; Karabel and Astin [<reflink idref="bib37" id="ref74">37</reflink>]; Karen [<reflink idref="bib38" id="ref75">38</reflink>]). Parental SES is measured as a standardised composite of father's education and occupation, mother's education and occupation, and family earnings. This variable was calculated by the NCES, and is available as part of the data set. The scaled SES variable is measured similarly across NCES data sets, and the alpha is at least 0.8 across data sets (McLaughlin, Cohen, and Lee [<reflink idref="bib48" id="ref76">48</reflink>]).</p> <p>We also control for students' performance in high school and whether they take AP courses. High school performance is measured through average grades in math, English, science, and social studies courses during high school. This data were collected from high school transcripts.[<reflink idref="bib7" id="ref77">7</reflink>] In addition, cognitive tests were administered to students in the NELS sample in 1988, 1990, and 1992, when students were in eighth, tenth, and twelfth grades, to determine achievement in reading, math, science, and social studies. We utilise the math-reading composite from the twelfth grade, developed by the NCES, as a general indicator of achievement (Blau, Moller, and Jones [<reflink idref="bib6" id="ref78">6</reflink>]).[<reflink idref="bib8" id="ref79">8</reflink>]</p> <p>AP coursework is measured from the transcript file through a dichotomous indicator of whether the student has taken an AP course. Additionally, in the twelfth grade, students were asked how much education they expected to achieve. From their responses, we coded a series of dummy variables indicating whether they expected to achieve only a college education, more than a college education, or less than college (reference category). Finally, we include a control for participation in extracurricular activities because previous research has found a link between participating in extracurricular activities and attending more prestigious colleges (Hearn [<reflink idref="bib30" id="ref80">30</reflink>]; Karen [<reflink idref="bib38" id="ref81">38</reflink>]). In the twelfth grade, students reported whether they participated in extracurricular activities (a dummy variable coded 1 if they participated in extracurricular activities and 0 if they did not).</p> <hd id="AN0092943010-8">School-level controls</hd> <p>All models also control for school-level variables, including: school size, the per cent White, the per cent on free lunch, average math and reading scores, the standard deviation of math and reading scores, high school region, high school location, and school sector. The rationale for including per cent White and per cent on free lunch will be discussed in the selection bias section. We add controls, at the school level, for school size, measured as the log of the school population. We also include a measure of average achievement and the standard deviation in achievement in schools to control for the fact that some schools may have more students taking AP courses simply because these schools have a more homogeneous, high achieving student body. Average scores are measured as average math and reading scores of all students in the twelfth grade sample. Standard deviation of scores is measured as the standard deviation of math and reading scores of all students in the twelfth grade sample. We include region and area of the country because southern and rural schools have historically offered poorer quality public education due to their comparatively lower funding levels than other areas of the country (National Center for Education Statistics [<reflink idref="bib51" id="ref82">51</reflink>]; US Department of Education [<reflink idref="bib70" id="ref83">70</reflink>], Table 167). Region of the country is measured as Northeast, Midwest, West, and South (reference category). Urbanicity is measured as suburban, rural, and urban (reference category). Finally, students from public schools have lower achievement, on average, and are less likely to pursue post-secondary degrees than students from private schools (Blau [<reflink idref="bib5" id="ref84">5</reflink>]). Thus, we include a dichotomous measure of public schools (coded 1 for public high school and 0 for private). Means and standard deviations for the independent and dependent variables are shown in Table 1. Correlation matrices are presented in the appendices.</p> <p>Table 1. Descriptive statistics.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Mean</td><td>SD</td></tr></thead><tbody><tr><td><italic>Student variables</italic></td><td /><td /></tr><tr><td>Moderately selective colleges</td><td char=".">0.22</td><td char=".">0.41</td></tr><tr><td>Highly selective colleges</td><td char=".">0.06</td><td char=".">0.24</td></tr><tr><td>Female</td><td char=".">0.54</td><td char=".">0.5</td></tr><tr><td>Age</td><td char=".">18.24</td><td char=".">0.48</td></tr><tr><td>Average grades</td><td char=".">2.85</td><td char=".">0.68</td></tr><tr><td>SES</td><td char=".">0.34</td><td char=".">0.74</td></tr><tr><td>Asian-American</td><td char=".">0.1</td><td char=".">0.29</td></tr><tr><td>Latino</td><td char=".">0.08</td><td char=".">0.28</td></tr><tr><td>African-American</td><td char=".">0.09</td><td char=".">0.28</td></tr><tr><td>Extracurricular participation</td><td char=".">0.93</td><td char=".">0.25</td></tr><tr><td>AP coursework</td><td char=".">0.57</td><td char=".">0.49</td></tr><tr><td>Expect college</td><td char=".">0.41</td><td char=".">0.49</td></tr><tr><td>Expect more than college</td><td char=".">0.51</td><td char=".">0.5</td></tr><tr><td>Math and reading scores</td><td char=".">57.12</td><td char=".">7.94</td></tr><tr><td>Mills ratio</td><td char=".">0.83</td><td char=".">0.48</td></tr><tr><td><italic>School variables</italic></td><td /><td /></tr><tr><td>Per cent AP</td><td char=".">22.73</td><td char=".">0.58</td></tr><tr><td>Public school</td><td char=".">0.82</td><td char=".">0.38</td></tr><tr><td>School population</td><td char=".">6.84</td><td char=".">0.7</td></tr><tr><td>Per cent White</td><td char=".">74.03</td><td char=".">9.32</td></tr><tr><td>Free lunch</td><td char=".">18.57</td><td char=".">0.23</td></tr><tr><td>Suburban</td><td char=".">0.39</td><td char=".">0.49</td></tr><tr><td>Rural</td><td char=".">0.31</td><td char=".">0.46</td></tr><tr><td>Western</td><td char=".">0.17</td><td char=".">0.37</td></tr><tr><td>Northeast</td><td char=".">0.21</td><td char=".">0.41</td></tr><tr><td>Midwest</td><td char=".">0.28</td><td char=".">0.45</td></tr><tr><td>Offers AP</td><td char=".">0.18</td><td char=".">0.38</td></tr><tr><td>Average scores</td><td char=".">52.78</td><td char=".">5.58</td></tr><tr><td>Standard deviation of scores</td><td char=".">8.18</td><td char=".">3.46</td></tr></tbody></table> </ephtml> </p> <p>Note: <emph>N</emph> = 3290 students in 662 schools.</p> <hd id="AN0092943010-9">Modelling strategy</hd> <p>To examine the impact of schools' AP opportunity on college selectivity, we employ multilevel models because they adjust the standard errors to account for multiple, dependent levels of analyses, and they allow a decomposition of the variation in the dependent variable (Raudenbush and Bryk [<reflink idref="bib55" id="ref85">55</reflink>]; Snijders and Bosker [<reflink idref="bib63" id="ref86">63</reflink>]). The dependent variable, college selectivity, is an ordinal variable with three categories: highly selective, selective, and nonselective. We analyze college selectivity through multilevel multinomial logistic regressions. We choose multinomial logistic regression, as opposed to ordinal logistic regression, because ordinal logistic regression assumes that the associations between the independent and dependent variables are parallel across categories. We tested this assumption and find that the slope parameters vary significantly across categories. Thus, multinomial logistic regression offers a better fit to the data.</p> <hd id="AN0092943010-10">Selection bias</hd> <p>Two forms of selection bias may impact our results. First, parents and students select into schools. Indeed, it is common in the USA for economically-able parents to choose a residential neighbourhood based on the quality of the school, or they may choose to send their children to private or magnet schools. A number of studies have examined the factors that influence school choice. Maddus ([<reflink idref="bib43" id="ref87">43</reflink>]) found that 50–60% of parents with children in public schools considered the school in residential decisions, and White and Latino parents are substantially more likely to consider schools in residential decisions than African-American parents. A number of scholars have also found that the racial composition of the school is the most important factor predicting school choice (Glazerman [<reflink idref="bib25" id="ref88">25</reflink>]; Holme [<reflink idref="bib32" id="ref89">32</reflink>]; Salvatore and Lareau [<reflink idref="bib59" id="ref90">59</reflink>]; Saporito and Sohoni [<reflink idref="bib60" id="ref91">60</reflink>], [<reflink idref="bib61" id="ref92">61</reflink>]). Indeed, these studies find that parents (both upper income and lower income) are not generally aware of schools' curricula or test scores when they choose or reject schools. Upper-SES parents are most likely to avoid schools with large nonwhite and low income populations (Holme [<reflink idref="bib32" id="ref93">32</reflink>]; Salvatore and Lareau [<reflink idref="bib59" id="ref94">59</reflink>]); and African-American families, when possible, avoid schools with high poverty rates (Salvatore and Lareau [<reflink idref="bib59" id="ref95">59</reflink>]). This is true even if parents indicate that they prefer schools with a strong curriculum (Maddus [<reflink idref="bib43" id="ref96">43</reflink>]). Thus, selection is based on parents' perceptions of the racial and SES of peers.</p> <p>To reduce selection bias, we control for covariates that measure the signals that parents often use to determine where their students go to school (see Raudenbush and Willms [<reflink idref="bib56" id="ref97">56</reflink>]).[<reflink idref="bib9" id="ref98">9</reflink>] Given that researchers have found that racial and socio-economic composition of schools are by far the most important determinants of school choice, we control for the per cent White and the per cent on free and reduced price lunch. In addition, the control for SES at the student level accounts for the extent that parents may relocate to a new neighbourhood to access a new school, and the control for private school accounts for whether parents choose private over public education. While these variables do not exhaust the possibility that parents may choose to send their children to the most rigorous schools, they certainly minimise this possibility. Furthermore, to the extent that this type of selection bias remains in the analysis, it should not impact our results regarding gender and educational outcomes because parents generally choose the same schools for their children, regardless of gender. Thus, findings regarding differences amongst genders should not simply reflect differences in school choice. However, we recognise that the value placed on women's education may vary across SES. Thus, to help verify that our results do not simply reflect selection effects, we ran interactions between SES and gender. This interaction does not change our results regarding AP opportunity and gender.</p> <p>Our samples are also potentially biased because they exclude students who do not attend ranked four-year institutions. However, multilevel modelling programmes do not currently offer corrections for this type of sample selection bias. Thus, we add a variable to the analyses that corrects for selection bias (Devine, Brody, and Wright [<reflink idref="bib21" id="ref99">21</reflink>]; Heckman [<reflink idref="bib31" id="ref100">31</reflink>]). This variable, the inverse Mills ratio, is calculated through a probit model, where a dichotomous measure of 'students who attend ranked universities' is predicted by variables found in prior research to predict whether students went to college. We added to the selection model the scores from a principal components analysis of average grades in math, English, science, and social studies; class rank; rigorous academic track;[<reflink idref="bib10" id="ref101">10</reflink>] and twelfth grade math and reading scores. We also added participation in extracurricular activities, as this is a clear predictor of college attendance (Guest and Schneider [<reflink idref="bib28" id="ref102">28</reflink>]; Kaufman and Gabler [<reflink idref="bib39" id="ref103">39</reflink>]). Finally, the selection model controls for students' race, gender, SES, and educational expectations. These inverse Mills ratios are added to the multilevel models to control for selection bias. These ratios represent controls for the probability that an observation is included in the sample (Heckman [<reflink idref="bib31" id="ref104">31</reflink>]).</p> <hd id="AN0092943010-11">Results</hd> <p>Prior to turning to the regression results, we will clarify the meaning of AP opportunity (measured as per cent AP). As previous scholars and journalists have argued, the size of the AP curriculum appears to reflect rigorous standards and greater opportunities to learn. Table 2 presents descriptive statistics from the student and administrator questionnaires. The data are compared for students who study in schools in the bottom third of the per cent AP distribution (where less than 13% of students take AP courses), in the middle third of the distribution (where 13–30% of students take AP courses), and in the top third (where more than 30% of students take AP courses). Among respondents who study in schools with a small percentage of students studying in AP courses, 65% report that their friends believe that it is very important to continue their education past high school. This is significantly lower than students who study in schools where more than one-third of students take AP courses. In those schools, 74% state that friends believe it is very important to continue education past high school. This suggests that peer culture is much more academically oriented in schools with a broader usage of the AP curriculum.</p> <p>Table 2. Characteristics of schools by size of AP curriculum.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Per cent AP</td><td /></tr><tr><td /><td><13%</td><td>13–30%</td><td>>30%</td><td /></tr></thead><tbody><tr><td>Among friends, it is very important to continue education past high school</td><td>64.8%</td><td>71.9%</td><td>74.3%</td><td>***</td></tr><tr><td>Administrators reports that students place a high priority on learning</td><td>38.6%</td><td>42.4%</td><td>72.8%</td><td>***</td></tr><tr><td>Administrators report that teachers encourage all students to achieve academically</td><td>60.7%</td><td>69.7%</td><td>84.7%</td><td>***</td></tr><tr><td>Administrators report that academic standards influence students to drop out</td><td>3.8%</td><td>7.7%</td><td>13.8%</td><td>***</td></tr></tbody></table> </ephtml> </p> <p>***Chi square significant at <emph>p</emph> < 0.001.</p> <p>This table also presents administrator comments across schools. Only 39% of administrators in schools where relatively few students take AP courses perceive that students place a high priority on learning. This is substantially and significantly lower than the perception of administrators in schools where more than one-third of students take AP courses: 73% of those administrators perceive that students place a high priority on learning. Administrators' responses corroborate students' responses as schools with a broader usage of the AP curriculum (i.e. higher AP opportunity) appear to be more academically oriented.</p> <p>The extant literature also suggests that broader usage of the AP curriculum reflects greater opportunities to learn among more students. The statistics presented in Table 2 support this assumption, as 85% of administrators in high-AP-opportunity schools where there are greater opportunities for students to take AP courses (i.e. where greater than one-third of students take AP courses) believe that teachers encourage all students to achieve, compared to only 61% of administrators in low-AP-opportunity schools (where fewer students take AP courses). This statistic certainly does not prove the point, but it helps to support it. Finally, the use of AP curriculum as an indicator of school quality has been criticised due to high dropout rates of these schools. Administrators were asked to assess why students drop out of school. Interestingly, 14% of administrators believe that dropout reflects high academic standards in high-AP-opportunity schools, compared to only 4% in low-AP-opportunity schools with less than 13% in AP courses. Thus, the sources of dropout may differ across these schools. Together, these descriptive statistics suggest that schools with greater AP opportunity (where a larger percentage of students take AP courses) are more academically focused, and they offer more opportunities to learn. Yet, some students face severe challenges in these schools due to high academic standards.</p> <p>Multilevel models are presented in Table 3. Models 1a and 1b present the results for gender without controls; Models 2a and 2b present the results for per cent AP without controls; Models 3a and 3b include interactions between per cent AP and female; Models 4a and 4b add all student and school-level controls, and models 5a and 5b control for selection bias, measured through the inverse Mills Ratio.</p> <p>Table 3. Unstandardised coefficients from multilevel multinomial logistic regression predicting institutional selectivity.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Highly selective</td><td>Selective</td></tr><tr><td>Model 1a</td><td>Model 2a</td><td>Model 3a</td><td>Model 4a</td><td>Model 5a</td><td>Model 1b</td><td>Model 2b</td><td>Model 3b</td><td>Model 4b</td><td>Model 5b</td></tr></thead><tbody><tr><td>Female</td><td>−0.12 (0.21)</td><td>–</td><td>0.07(0.37)</td><td>−0.13(0.45)</td><td>−0.36(0.45)</td><td>−0.08(0.11)</td><td>–</td><td>−0.53**(0.18)</td><td>−0.84***(0.19)</td><td>−0.83***(0.19)</td></tr><tr><td>Per cent AP</td><td>–</td><td>0.05***(0.01)</td><td>0.05***(0.01)</td><td>0.03**(0.01)</td><td>0.03**(0.01)</td><td>–</td><td>0.03***(0.00)</td><td>0.02***(0.00)</td><td>0.01(0.01)</td><td>0.01(0.01)</td></tr><tr><td>Female*Per cent AP</td><td>–</td><td>–</td><td>0.00(0.01)</td><td>0.00(0.01)</td><td>0.00(0.01)</td><td>–</td><td>–</td><td>0.01**(0.01)</td><td>0.02**(0.01)</td><td>0.02**(0.01)</td></tr><tr><td>Intercept</td><td>−2.19***(0.19)</td><td>−3.99***(0.26)</td><td>−4.02***(0.34)</td><td>−5.79***(0.44)</td><td>−5.48***(0.43)</td><td>−0.97***(0.10)</td><td>−1.80***(0.15)</td><td>−1.55***(0.18)</td><td>−1.48***(0.19)</td><td>−1.49***(0.19)</td></tr><tr><td>Public school</td><td>–</td><td>–</td><td>–</td><td>−1.41**(0.53)</td><td>−1.44**(0.52)</td><td>–</td><td>–</td><td>–</td><td>−0.58(0.30)</td><td>−0.58(0.30)</td></tr><tr><td>School population</td><td>–</td><td>–</td><td>–</td><td>0.85**(0.27)</td><td>0.88**(0.27)</td><td>–</td><td>–</td><td>–</td><td>0.54**(0.16)</td><td>0.54**(0.16)</td></tr><tr><td>Per cent White</td><td>–</td><td>–</td><td>–</td><td>−0.02*(0.01)</td><td>−0.02**(0.01)</td><td>–</td><td>–</td><td>–</td><td>−0.01(0.00)</td><td>−0.01(0.00)</td></tr><tr><td>Free lunch</td><td>–</td><td>–</td><td>–</td><td>0.00(0.01)</td><td>0.00(0.01)</td><td>–</td><td>–</td><td>–</td><td>0.00(0.01)</td><td>0.00(0.01)</td></tr><tr><td>Suburban</td><td>–</td><td>–</td><td>–</td><td>0.77(0.42)</td><td>0.76(0.41)</td><td>–</td><td>–</td><td>–</td><td>0.60**(0.21)</td><td>0.61**(0.21)</td></tr><tr><td>Rural</td><td>–</td><td>–</td><td>–</td><td>−0.18(0.54)</td><td>−0.08(0.53)</td><td>–</td><td>–</td><td>–</td><td>0.17(0.28)</td><td>0.18(0.28)</td></tr><tr><td>Western</td><td>–</td><td>–</td><td>–</td><td>1.94***(0.42)</td><td>1.95***(0.41)</td><td>–</td><td>–</td><td>–</td><td>0.61**(0.23)</td><td>0.60**(0.23)</td></tr><tr><td>Northeast</td><td>–</td><td>–</td><td>–</td><td>1.60**(0.48)</td><td>1.63**(0.47)</td><td>–</td><td>–</td><td>–</td><td>0.59*(0.23)</td><td>0.59*(0.23)</td></tr><tr><td>Midwest</td><td>–</td><td>–</td><td>–</td><td>0.25(0.43)</td><td>0.18(0.43)</td><td>–</td><td>–</td><td>–</td><td>0.38(0.22)</td><td>0.39(0.22)</td></tr><tr><td>Offers AP</td><td>–</td><td>0.69(0.66)</td><td>0.65(0.67)</td><td>0.20(0.57)</td><td>0.32(0.57)</td><td>–</td><td>−0.07(0.26)</td><td>−0.05(0.27)</td><td>0.10(0.28)</td><td>0.10(0.28)</td></tr><tr><td>Average scores</td><td>–</td><td>–</td><td>–</td><td>0.29***(0.05)</td><td>0.27***(0.05)</td><td>–</td><td>–</td><td>–</td><td>0.13***(0.02)</td><td>0.13***(0.02)</td></tr><tr><td>Standard deviation of scores</td><td>–</td><td>–</td><td>–</td><td>−0.02(0.06)</td><td>−0.03(0.06)</td><td>–</td><td>–</td><td>–</td><td>0.00(0.03)</td><td>0.00(0.03)</td></tr><tr><td>Age</td><td>–</td><td>–</td><td>–</td><td>0.18(0.34)</td><td>0.23(0.35)</td><td>–</td><td>–</td><td>–</td><td>0.06(0.15)</td><td>0.05(0.15)</td></tr><tr><td>Average grades</td><td>–</td><td>–</td><td>–</td><td>3.20***(0.33)</td><td>4.37***(0.53)</td><td>–</td><td>–</td><td>–</td><td>1.09***(0.15)</td><td>1.03***(0.28)</td></tr><tr><td>SES</td><td>–</td><td>–</td><td>–</td><td>0.48*(0.22)</td><td>1.25**(0.39)</td><td>–</td><td>–</td><td>–</td><td>0.27*(0.11)</td><td>0.23(0.18)</td></tr><tr><td>Asian</td><td>–</td><td>–</td><td>–</td><td>0.82*(0.41)</td><td>0.87*(0.41)</td><td>–</td><td>–</td><td>–</td><td>0.43(0.26)</td><td>0.44(0.26)</td></tr><tr><td>Hispanic</td><td>–</td><td>–</td><td>–</td><td>2.24***(0.55)</td><td>1.94**(0.61)</td><td>–</td><td>–</td><td>–</td><td>0.03(0.35)</td><td>0.03(0.36)</td></tr><tr><td>Black</td><td>–</td><td>–</td><td>–</td><td>1.22(0.65)</td><td>1.35*(0.64)</td><td>–</td><td>–</td><td>–</td><td>0.52(0.38)</td><td>0.51(0.38)</td></tr><tr><td>Extracurricular participation</td><td>–</td><td>–</td><td>–</td><td>0.75(0.56)</td><td>2.07**(0.61)</td><td>–</td><td>–</td><td>–</td><td>0.21(0.24)</td><td>0.15(0.30)</td></tr><tr><td>AP coursework</td><td>–</td><td>–</td><td>–</td><td>0.69(0.41)</td><td>0.94*(0.47)</td><td>–</td><td>–</td><td>–</td><td>0.42**(0.16)</td><td>0.40*(0.17)</td></tr><tr><td>Expect college</td><td>–</td><td>–</td><td>–</td><td>−0.71(0.47)</td><td>2.04*(0.99)</td><td>–</td><td>–</td><td>–</td><td>−0.34(0.24)</td><td>−0.47(0.53)</td></tr><tr><td>Expect more than college</td><td>–</td><td>–</td><td>–</td><td>−0.17(0.37)</td><td>2.76**(1.01)</td><td>–</td><td>–</td><td>–</td><td>−0.04(0.25)</td><td>−0.17(0.56)</td></tr><tr><td>Math and reading scores</td><td>–</td><td>–</td><td>–</td><td>0.09**(0.03)</td><td>0.18***(0.04)</td><td>–</td><td>–</td><td>–</td><td>0.04**(0.01)</td><td>0.04*(0.02)</td></tr><tr><td>Mills ratio</td><td>–</td><td>–</td><td>–</td><td>–</td><td>5.47**(1.67)</td><td>–</td><td>–</td><td>–</td><td>–</td><td>−0.27(0.80)</td></tr></tbody></table> </ephtml> </p> <p>Note: Weighted, <emph>n</emph> = 3289 students in 662 schools. *<emph>p</emph> < 0.05. **<emph>p</emph> < 0.01. ***<emph>p</emph> < 0.001.</p> <p>Models 1a and 1b illustrate that, without any controls, there is no gender difference in the selectivity of colleges that students attend. Men and women are equally likely to pursue education at moderately selective and highly selective colleges, compared to nonselective colleges. This is sensible given that many, if not most colleges have moved toward gender parity in admissions. Table 3 also illustrates that, without any controls, students who attend schools with greater AP opportunities, measured through per cent AP, are more likely to attend moderately selective (model 2a) and highly selective (model 2b) colleges. To test our hypotheses, we must examine an interaction between per cent AP and gender. Indeed, the absence of gender effects in Models 1a and 1b do not account for any differences that gender may have across schools. The interaction effects presented in Models 3a and 4a suggest that there are not significant gender differences in the impact of per cent AP on attendance at highly selective colleges. Boys <emph>and</emph> girls who study in schools with higher AP opportunities are more likely to attend highly selective post-secondary institutions immediately following high school.</p> <p>In contrast to the results for highly selective colleges, the influence of per cent AP on attendance at moderately selective universities differs by gender. Model 3b illustrates through an interaction term that girls are less likely to go to moderately selective colleges (as opposed to nonselective colleges) than boys when they study in high schools with fewer opportunities for AP curricula. Yet, the male advantage in moderately selective college attendance diminishes when opportunities for AP curriculum are greater (as seen with the significant, positive interaction effect). These results are robust to the control for student and school characteristics introduced in model 4b and to the control for selection bias introduced in model 5b.[<reflink idref="bib11" id="ref105">11</reflink>] These results are important because 22% of our sample attend moderately selective colleges, whereas only 6% attend highly selective colleges.</p> <p>Figure 1 presents the results from Table 3, model 5b for moderately selective schools. This figure graphs the predicted probability of attending moderately selective post-secondary institutions by high school per cent AP for boys and girls. Per cent AP is plotted from the fifth percentile (where 0% of students in the school take AP courses) to the 95th percentile (where 67% of students take AP courses). The figure illustrates that schools with the smallest percentage of students in AP courses (i.e. those falling at the fifth percentile of the per cent AP distribution) are predicted to send a higher proportion of boys compared with girls to moderately selective colleges. However, the gap in the probability of attending a moderately selective post-secondary institution diminishes as the coverage of the AP curriculum increases. In fact, girls are more likely than boys to attend moderately selective colleges when they study in schools where 50% or more of students take AP courses.[<reflink idref="bib12" id="ref106">12</reflink>] It is important to note that boys are equally likely to attend a moderately selective institution whether they studied in schools with a small per cent AP or a large per cent AP (Figure 1). Thus, boys are not faltering in schools with a larger per cent AP. Instead, they are simply failing to reap the rewards that girls receive in these schools.</p> <p>Graph: Figure 1. Predicted probability of attending a moderately selective post-secondary institution by the high school AP opportunity for boys and girls. Note: From Table 2, Model 5b. Control variables constrained to their means.</p> <p>Returning to Table 3, the significant Mills ratio in model 5a for highly selective colleges means that selection bias was a problem in our model. Since the Mills Ratio controls for the probability that a respondent is included in the sample, the significant effect suggests that students who entered our sample, compared to those who did not, are more likely to attend highly selective institutions. Thus, the control for selection bias is necessary. The Mills Ratio is not significant for moderately selective institutions (see model 5b), suggesting that selection bias is not a problem in that the component of the model. Taken together, these results suggest that our modelling approach, which includes a Heckman selection measure, is appropriate for this analysis. Controlling for selection bias does not alter the key results surrounding gender and per cent AP.</p> <hd id="AN0092943010-12">Conclusions</hd> <p>This paper has examined whether gender differences in the likelihood that students attend selective post-secondary institutions in the USA is conditioned on AP opportunity, or the percentage of students taking AP courses, in secondary school. AP opportunity is a critical component of secondary schools' organisation in the USA because it reflects the extent that schools offer students more rigorous educational opportunities. The curriculum has become more rigorous because US educators are trying to move more students into post-secondary institutions in order for the USA to remain competitive in the global economy. The expansion of an academically rigorous curriculum was not designed as a gendered strategy, but it clearly has gendered effects.</p> <p>We argue for the possibility of two gendered outcomes. AP opportunity could minimise gender inequality by helping girls; schools with greater AP opportunity complement components of femininity in that studious behaviour is often considered feminine and social context is more influential for girls than boys. AP opportunity could also minimise gender inequality by harming boys because some researchers have argued that boys are more vulnerable to rigorous contexts. We find support for the first outcome, as women clearly thrive in schools with greater AP opportunity, but boys are relatively unaffected.</p> <p>This research challenges that argument that girls are succeeding on the backs of boys and that the need for feminism is obsolete. Boys have consistent achievement across school context. In contrast, girls thrive in a more rigorous context, and they falter in a less rigorous context. Clearly, this is not a zero-sum game. Girls can succeed, without undermining boys' academic success. At the upper end of AP opportunity, girls are outperforming boys in terms of the prestige of their post-secondary placement, but NOT because boys are disadvantaged. Thus, while discourse has framed girls' success as a detriment to boys, empirically this is not supported, at least not by this study. This research, then, contributes to a growing body of research that illustrates that successful women do not necessarily breed unsuccessful men.</p> <p>This paper also challenges the notion that the social context is becoming less relevant to girls. Clearly, in this instance, the social context is more important for girls than boys. Attendance at a post-secondary institution is not merely an outcome of girls' behaviours, it is an outcome that is influenced by the social context. Given that girls are more vulnerable to the social context in this study, policy-makers must be very careful in ordering changes in school contexts, which could have profound implications for girls' outcomes. Gender researchers must continue to uncover the gendered effects of seemingly ungendered social structures.</p> <p>This is not to say that context is irrelevant to boys. The exact context studied here is irrelevant to boys, but other measures of context could be quite predictive of boys' success or failure (Legewie and DiPrete [<reflink idref="bib40" id="ref107">40</reflink>]). This is clearly an avenue for future research. Future research should also help explain <emph>why</emph> men and women have divergent outcomes under different contextual environments. We have identified possible mechanisms descriptively, but qualitative research is better equipped to more thoroughly articulate these mechanisms. Such future research could also focus on the role of popular culture, specifically popular youth culture, its interpretation and enactment of various masculinities and femininities, and their relation with academically-oriented behaviours, to complement the analyses reported here.</p> <p>This paper establishes both the on-going importance of the social context and the role that rigorous curriculum plays in gendered post-secondary outcomes. In separate analyses, we examined outcomes by race and class and found that this story is more of a gender story. However, it is important to note that the size of the sample of some groups was too small when dividing into race, class, gender categories, and therefore we did not expect to find significant results. Future research, based on a larger sample, should also take a more intersectional approach. In the meantime, we have established that in the USA, the school context is designed to move more students into selective post-secondary institutions has gendered effects. Context continues to be important for women's success, and feminists must resist arguments that suggest the opposite. There is an ongoing need for feminist discourse in education, and this discourse should more broadly clarify the role of the social context in creating gender relations and gender outcomes.</p> <hd id="AN0092943010-13">Funding</hd> <p>Funded by the Spencer Foundation.</p> <hd id="AN0092943010-14">Acknowledgements</hd> <p>The authors acknowledge the helpful comments of Roslyn Mickelson.</p> <p>Appendix 1. Correlation matrix; student variables</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>(1)</td><td>(2)</td><td>(3)</td><td>(4)</td><td>(5)</td><td>(6)</td><td>(7)</td><td>(8)</td><td>(9)</td><td>(10)</td><td>(11)</td><td>(12)</td><td>(13)</td></tr></thead><tbody><tr><td>(1) College selectivity</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(2) Female</td><td char=".">0.03</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(3) Age</td><td char=".">0.04</td><td char=".">−0.12</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(4) Average grades</td><td char=".">−0.35</td><td char=".">0.11</td><td char=".">−0.07</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(5) SES</td><td char=".">−0.31</td><td char=".">−0.05</td><td char=".">−0.09</td><td char=".">0.22</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(6) Asian-American</td><td char=".">−0.21</td><td char=".">0.01</td><td char=".">−0.01</td><td char=".">0.13</td><td char=".">0.05</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(7) Latino</td><td char=".">0.04</td><td char=".">−0.02</td><td char=".">0.03</td><td char=".">−0.12</td><td char=".">−0.21</td><td char=".">−0.1</td><td char=".">1</td><td /><td /><td /><td /><td /><td /></tr><tr><td>(8) African-American</td><td char=".">0.07</td><td char=".">0.04</td><td char=".">0</td><td char=".">−0.22</td><td char=".">−0.14</td><td char=".">−0.1</td><td char=".">−0.09</td><td char=".">1</td><td /><td /><td /><td /><td /></tr><tr><td>(9) Extracurricular participation</td><td char=".">−0.08</td><td char=".">0.02</td><td char=".">0.02</td><td char=".">0.14</td><td char=".">0.09</td><td char=".">−0.03</td><td char=".">−0.02</td><td char=".">−0.02</td><td char=".">1</td><td /><td /><td /><td /></tr><tr><td>(10) AP coursework</td><td char=".">−0.3</td><td char=".">0.03</td><td char=".">−0.05</td><td char=".">0.32</td><td char=".">0.19</td><td char=".">0.11</td><td char=".">0</td><td char=".">−0.05</td><td char=".">0.12</td><td char=".">1</td><td /><td /><td /></tr><tr><td>(11) Expect college</td><td char=".">0.19</td><td char=".">−0.03</td><td char=".">0.02</td><td char=".">−0.12</td><td char=".">−0.14</td><td char=".">−0.06</td><td char=".">v0.02</td><td char=".">−0.04</td><td char=".">−0.04</td><td char=".">−0.17</td><td char=".">1</td><td /><td /></tr><tr><td>(12) Expect more than college</td><td char=".">−0.25</td><td char=".">0.05</td><td char=".">−0.04</td><td char=".">0.24</td><td char=".">0.22</td><td char=".">0.08</td><td char=".">0.01</td><td char=".">0.02</td><td char=".">0.09</td><td char=".">0.26</td><td char=".">−0.84</td><td char=".">1</td><td /></tr><tr><td>(13) Math and reading scores</td><td char=".">−0.39</td><td char=".">0.01</td><td char=".">−0.13</td><td char=".">0.59</td><td char=".">0.35</td><td char=".">0.09</td><td char=".">−0.14</td><td char=".">−0.25</td><td char=".">0.1</td><td char=".">0.36</td><td char=".">−0.15</td><td char=".">0.27</td><td char=".">1</td></tr><tr><td>(14) Mills ratio</td><td char=".">0.39</td><td char=".">0</td><td char=".">0.11</td><td char=".">−0.74</td><td char=".">−0.56</td><td char=".">−0.11</td><td char=".">0.18</td><td char=".">0.19</td><td char=".">−0.28</td><td char=".">−0.38</td><td char=".">0.08</td><td char=".">−0.41</td><td char=".">−0.73</td></tr></tbody></table> </ephtml> </p> <p>Appendix 2. Correlation matrix, school-level variables</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>(1)</td><td>(2)</td><td>(3)</td><td>(4)</td><td>(5)</td><td>(6)</td><td>(7)</td><td>(8)</td><td>(9)</td><td>(10)</td><td>(11)</td><td>(12)</td></tr></thead><tbody><tr><td>(1) Per cent AP</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(2) Public</td><td char=".">−0.38</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(3) School population</td><td char=".">0.04</td><td char=".">0.35</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(4) Per cent White</td><td char=".">0.06</td><td char=".">−0.06</td><td char=".">−0.34</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(5) Free lunch</td><td char=".">−0.28</td><td char=".">0.36</td><td char=".">0.09</td><td char=".">−0.46</td><td char=".">1</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>(6) Suburban</td><td char=".">0.04</td><td char=".">0.12</td><td char=".">0.12</td><td char=".">0.13</td><td char=".">−0.22</td><td char=".">1</td><td /><td /><td /><td /><td /><td /></tr><tr><td>(7) Rural</td><td char=".">−0.25</td><td char=".">0.26</td><td char=".">−0.32</td><td char=".">0.19</td><td char=".">0.26</td><td char=".">−0.53</td><td char=".">1</td><td /><td /><td /><td /><td /></tr><tr><td>(8) Western</td><td char=".">0.08</td><td char=".">0.03</td><td char=".">0.17</td><td char=".">−0.15</td><td char=".">−0.02</td><td char=".">0.01</td><td char=".">−0.06</td><td char=".">1</td><td /><td /><td /><td /></tr><tr><td>(9) Northeastern</td><td char=".">0.07</td><td char=".">−0.16</td><td char=".">−0.12</td><td char=".">0.13</td><td char=".">−0.18</td><td char=".">0.12</td><td char=".">−0.09</td><td char=".">−0.23</td><td char=".">1</td><td /><td /><td /></tr><tr><td>(10) Midwest</td><td char=".">−0.11</td><td char=".">0.04</td><td char=".">−0.17</td><td char=".">0.28</td><td char=".">−0.08</td><td char=".">0.02</td><td char=".">0.06</td><td char=".">−0.28</td><td char=".">−0.32</td><td char=".">1</td><td /><td /></tr><tr><td>(11) Average score</td><td char=".">0.41</td><td char=".">−0.42</td><td char=".">−0.08</td><td char=".">0.34</td><td char=".">−0.47</td><td char=".">0.09</td><td char=".">−0.22</td><td char=".">0.05</td><td char=".">0.17</td><td char=".">0.06</td><td char=".">1</td><td /></tr><tr><td>(12) SD of scores</td><td char=".">−0.2</td><td char=".">0.37</td><td char=".">0.1</td><td char=".">0.02</td><td char=".">0.04</td><td char=".">0.04</td><td char=".">0.09</td><td char=".">−0.02</td><td char=".">−0.07</td><td char=".">0.07</td><td char=".">−0.32</td><td char=".">1</td></tr><tr><td>(13) Offers AP</td><td char=".">−0.51</td><td char=".">0.08</td><td char=".">−0.31</td><td char=".">0.06</td><td char=".">0.12</td><td char=".">−0.07</td><td char=".">0.22</td><td char=".">−0.07</td><td char=".">−0.04</td><td char=".">0.18</td><td char=".">−0.16</td><td char=".">−0.03</td></tr></tbody></table> </ephtml> </p> <ref id="AN0092943010-15"> <title> Notes </title> <blist> <bibl id="bib1" idref="ref18" type="bt">1</bibl> <bibtext> We do not focus on IB tests because they are less widely utilised across schools.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref26" type="bt">2</bibl> <bibtext> Of course, some scholars question the long-term implications of attending selective colleges (Black and Smith [4]; Brand and Halaby [7]).</bibtext> </blist> <blist> <bibl id="bib3" idref="ref33" type="bt">3</bibl> <bibtext> It is important to note that while concerns over access to college are minimal, there are still major concerns over college major. Boys are still substantially more likely than girls to pursue science and math-oriented majors. This paper does not address that topic.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref34" type="bt">4</bibl> <bibtext> Feminists would also challenge the supposition that gender is no longer relevant to academic success because recent studies have found that within schools traditional gender relations emerge in peer groups, even if simultaneously accompanied by more egalitarian norms (Reay [57]). Furthermore, even if schools provide equal opportunities, girls might be actively discouraged from acting on these opportunities by the actions of boys looking to maintain the status quo.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref70" type="bt">5</bibl> <bibtext> It is important to note that the exclusion of specialty colleges and foreign colleges means that our results are not generalizable to the population of students attending those colleges.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref72" type="bt">6</bibl> <bibtext> The number of students who took AP tests is also not available in the NELS database.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref77" type="bt">7</bibl> <bibtext> If grades from one of these categories were missing, we took the average of the three remaining categories.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref20" type="bt">8</bibl> <bibtext> We utilise data on achievement tests rather than the scholastic aptitude test because we lose three times as many cases when we utilise SAT data. Furthermore, SAT data introduce a form of selection bias because students not planning to attend college do not usually take these tests. This would lower our sample. Thus, following Blau, Moller, and Jones ([6]) we rely on achievement data.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref11" type="bt">9</bibl> <bibtext> These covariates allow us to control for Type A effects associated with school choice (i.e. school context; Raudenbush and Willms [56]).</bibtext> </blist> <blist> <bibtext> Rigorous academic track reflects the kind of courses that the student took in school. Within schools in the USA, students can take very different courses. Some students take remedial courses, some take courses that focus on trades, such as cosmetology, and some take more rigorous, college-bound courses, such as AP courses and honours courses.</bibtext> </blist> <blist> <bibtext> In separate analyses (not shown), we include an interaction between SES and gender. We find that the interaction is not significant. The differences between boys and girls in college selectivity do not vary by parental SES.</bibtext> </blist> <blist> <bibtext> In separate analyses (not shown), we test an interaction between gender and whether the student takes AP classes. The interaction term is not significant. Girls who take AP courses are not more likely to attend moderately selective colleges than boys who take AP courses. In addition, there is no difference in the type of college attended between girls who do and do not take AP courses, net of other factors. Thus, the effect of per cent AP is not simply an artifact of an individual's course load. This supports, or at least does not contradict, our proposition that per cent AP reflects broader opportunities to learn in a rigorous curriculum.</bibtext> </blist> </ref> <ref id="AN0092943010-16"> <title> References </title> <blist> <bibtext> Adelman, C., B. Daniel, I. Berkovits, and J. Owings. 2003. 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  Data: Changing Course: The Gender Gap in College Selectivity and Opportunities to Learn in the High School Curriculum
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  Data: <searchLink fieldCode="AR" term="%22Moller%2C+Stephanie%22">Moller, Stephanie</searchLink><br /><searchLink fieldCode="AR" term="%22Stearns%2C+Elizabeth%22">Stearns, Elizabeth</searchLink><br /><searchLink fieldCode="AR" term="%22Southworth%2C+Stephanie%22">Southworth, Stephanie</searchLink><br /><searchLink fieldCode="AR" term="%22Potochnick%2C+Stephanie%22">Potochnick, Stephanie</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Gender+and+Education%22"><i>Gender and Education</i></searchLink>. 2013 25(7):851-871.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
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  Data: Y
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  Data: 21
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  Data: 2013
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  Data: Journal Articles<br />Reports - Research
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  Label: Education Level
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  Data: <searchLink fieldCode="EL" term="%22High+Schools%22">High Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Label: Descriptors
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  Data: <searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Longitudinal+Studies%22">Longitudinal Studies</searchLink><br /><searchLink fieldCode="DE" term="%22Selective+Admission%22">Selective Admission</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Advanced+Placement%22">Advanced Placement</searchLink><br /><searchLink fieldCode="DE" term="%22High+School+Students%22">High School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction%22">Prediction</searchLink><br /><searchLink fieldCode="DE" term="%22Admission+Criteria%22">Admission Criteria</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Opportunities%22">Educational Opportunities</searchLink><br /><searchLink fieldCode="DE" term="%22Institutional+Characteristics%22">Institutional Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+Status%22">Socioeconomic Status</searchLink><br /><searchLink fieldCode="DE" term="%22Outcomes+of+Education%22">Outcomes of Education</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+%28Statistics%29%22">Regression (Statistics)</searchLink>
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  Data: 10.1080/09540253.2013.853028
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  Data: 0954-0253
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Gender gaps in learning and education outcomes have changed dramatically over the last few years. However, researchers have not adequately assessed how the high school learning environment differentially affects boys and girls. An important component of the learning environment in US secondary school is the opportunity to learn in an Advanced Placement (AP) curriculum, which allows high school students to do college-level work. Using the US National Education Longitudinal Study 1988-2000, we explain how high school AP curriculum interacts with gender to predict the selectivity of colleges that students attend. The results show that girls and boys who attend high schools with a larger percentage of students in AP curriculum attend more selective colleges (that require higher standardised scores for admissions); yet the positive effect of the opportunity to learn in an AP curriculum is greater for girls than for boys. This research furthers the debate about the effects of school structure on gender stratification.
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  Data: 2014
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  Label: Accession Number
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  Data: EJ1021105
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        Value: 10.1080/09540253.2013.853028
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 851
    Subjects:
      – SubjectFull: Gender Differences
        Type: general
      – SubjectFull: Longitudinal Studies
        Type: general
      – SubjectFull: Selective Admission
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Advanced Placement
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      – SubjectFull: High School Students
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      – SubjectFull: Prediction
        Type: general
      – SubjectFull: Admission Criteria
        Type: general
      – SubjectFull: Educational Opportunities
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      – SubjectFull: Institutional Characteristics
        Type: general
      – SubjectFull: Socioeconomic Status
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      – SubjectFull: Outcomes of Education
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      – SubjectFull: Regression (Statistics)
        Type: general
      – SubjectFull: SAT (College Admission Test)
        Type: general
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      – TitleFull: Changing Course: The Gender Gap in College Selectivity and Opportunities to Learn in the High School Curriculum
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