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Does It Matter How the Rigor of High School Coursework Is Measured? Gaps in Coursework among Students and across Grades

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Title: Does It Matter How the Rigor of High School Coursework Is Measured? Gaps in Coursework among Students and across Grades
Language: English
Authors: Burhan Ogut (ORCID 0000-0003-1729-1396), Darrick Yee, Ruhan Circi, Nevin Dizdari
Source: Grantee Submission. 2023.
Peer Reviewed: Y
Page Count: 31
Publication Date: 2023
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R305A190073
Document Type: Reports - Research
Education Level: High Schools
Secondary Education
Descriptors: Course Selection (Students), High School Students, Difficulty Level, Age Differences, Student Characteristics, Disadvantaged, Longitudinal Studies, Achievement Gap
Assessment and Survey Identifiers: High School Longitudinal Study of 2009 (NCES)
DOI: 10.1111/emip.12577
Abstract: Research shows that the intensity of high school course-taking is related to postsecondary outcomes. However, there are various approaches to measuring the intensity of students' course-taking. This study presents new measures of coursework intensity that rely on differing levels of quantity and quality of coursework. We used these new indices to provide a current description of variations in high school course-taking across grades and student subgroups using a nationally representative dataset, the High School Longitudinal Study of 2009. Results showed that for measures emphasizing the quality of coursework the gaps in coursework among underserved students were larger and there was less upward movement in rigor across grades. [This paper was published in "Educational Measurement: Issues and Practice" v42 n4 p42-52 2023.]
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2024
Accession Number: ED653803
Database: ERIC
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  Value: <anid>AN0174011104;ems01dec.23;2023Dec07.04:00;v2.2.500</anid> <title id="AN0174011104-1">Does It Matter How the Rigor of High School Coursework Is Measured? Gaps in Coursework Among Students and Across Grades </title> <p>Research shows that the intensity of high school course‐taking is related to postsecondary outcomes. However, there are various approaches to measuring the intensity of students' course‐taking. This study presents new measures of coursework intensity that rely on differing levels of quantity and quality of coursework. We used these new indices to provide a current description of variations in high school course‐taking across grades and student subgroups using a nationally representative dataset, the High School Longitudinal Study of 2009. Results showed that for measures emphasizing the quality of coursework the gaps in coursework among underserved students were larger and there was less upward movement in rigor across grades.</p> <p>Keywords: coursework gaps; coursework intensity; high school coursework; postsecondary enrollment</p> <p>Increasing the rigor of courses taken in high school is a crucial part of education policy. The No Child Left Behind Act of 2001 aimed to increase coursework rigor by expanding students' access to Advanced Placement (AP) courses and AP exams through AP Incentive and AP Test Fee programs. Recent initiatives such as the 2009 Race to the Top and Common Core State Standards pushed for more advanced course‐taking in mathematics, English language arts, literacy in history and social studies, science, and technical subjects. Course‐taking can be described using the quantity (i.e., the number of credits received) and the quality (how advanced the course is) of the courses taken (Adelman, [<reflink idref="bib1" id="ref1">1</reflink>]). Studies show that both the quantity and quality of academic courses completed in high school are strong predictors of secondary and postsecondary attainment and success (Adelman, [<reflink idref="bib1" id="ref2">1</reflink>]; Leow et al., [<reflink idref="bib9" id="ref3">9</reflink>]; Long et al., [<reflink idref="bib10" id="ref4">10</reflink>]; Morgan et al., [<reflink idref="bib11" id="ref5">11</reflink>]).</p> <p>There is little agreement on how to measure the intensity of high school coursework. Approaches to measuring the intensity of students' coursework range from using a single course (generally the highest math course taken) to indices using all the core academic courses the student has taken (e.g., Adelman, [<reflink idref="bib1" id="ref6">1</reflink>]). This study offers new measures of coursework intensity that rely to different degrees on the levels of quantity and quality of students' coursework. Using recent data from a nationally representative study, we provide a current and comprehensive description of the gaps in high school coursework across student groups and the relationship between high school coursework and secondary and postsecondary outcomes. We see three strengths in the proposed measures. First, the measures are easily replicable and can be applied to any dataset that includes student transcripts. Second, they provide a complete picture of students' course‐taking across major subjects. Finally, instead of a single measure of intensity at the end of high school, new measures can be created at each grade level and can easily track students' course‐taking progression in high school. These measures can also pinpoint where (i.e., quantity vs. quality by grade level) gaps in coursework exist for underserved students.</p> <hd id="AN0174011104-2">Relevant Literature</hd> <p></p> <hd id="AN0174011104-3">Measuring Coursework</hd> <p>One of the used approaches to coursework intensity focuses only on math course‐taking and treats it as a sequence without considering other subjects and the course rigor involved in capturing overall course‐taking (e.g., Bozick & Ingels, [<reflink idref="bib3" id="ref7">3</reflink>]; Horn & Nuñez, [<reflink idref="bib7" id="ref8">7</reflink>]). Using data from the Educational Longitudinal Study of 2002 (ELS: 2002), Byun et al. ([<reflink idref="bib4" id="ref9">4</reflink>]) utilized a mathematics pipeline measure that operationalized advanced course‐taking as having completed at least one course beyond algebra, including trigonometry, precalculus, and Calculus. The results showed that after using propensity score matching to match students on prior achievement as well as student, parent, and school characteristics, advanced coursework significantly increased the probability of college enrollment.</p> <p>Some studies examined all the courses that a student had taken when measuring coursework rigor. For instance, Nord et al. ([<reflink idref="bib13" id="ref10">13</reflink>]), using data from the National Assessment of Educational Progress (NAEP) High School Transcript Study, classified a high school graduate's coursework into three levels: standard, midlevel, and rigorous. Standard coursework indicated that a student earned four credits in English and three credits each in social studies, mathematics, and science. For midlevel coursework, a high school graduate had to meet three additional requirements: mathematics credits earned must include algebra and geometry; science courses completed must cover two subjects among biology, chemistry, and physics; and one credit must be earned in a foreign language course. For rigorous coursework, a high school graduate had to earn four credits in mathematics, of which one course must be precalculus or a higher level; science courses completed must cover all three subjects of biology, chemistry, and physics; and three credits must be earned in foreign language courses. Nord et al. ([<reflink idref="bib13" id="ref11">13</reflink>]) found that graduates who completed rigorous coursework had higher NAEP scores.</p> <p>Using data from a cohort of students who graduated from high schools in Florida in the 2002–2003 school year, Long et al. ([<reflink idref="bib10" id="ref12">10</reflink>]) showed that rigorous course‐taking—coursework that included honors, Advanced Placement, and other upper‐level courses—had a positive impact on college enrollment. Taking a rigorous math course by the fall of tenth grade increased math scores on the tenth‐grade Florida Comprehensive Assessment Test, graduation rates, and enrollment into 4‐year colleges. Rigorous math courses had the largest impact on 4‐year college enrollment. Advanced coursework in other subjects also had a substantial effect. Similarly, an association between high school course‐taking and college enrollment, persistence, and attainment has been reported by several researchers (Morgan et al., [<reflink idref="bib11" id="ref13">11</reflink>]; Woods et al., [<reflink idref="bib14" id="ref14">14</reflink>]).</p> <p>Indices that aim to account for all course‐taking have also been used for measuring coursework. The curriculum intensity index developed by Adelman ([<reflink idref="bib1" id="ref15">1</reflink>]) aimed to capture the quantity and quality of students' coursework in core subjects (English, mathematics, science, history, social studies, and foreign languages). To take the quality of coursework into account, the index included the highest math course completed, the number of credits completed in core science courses (biology, physics, and chemistry), whether the student took at least one AP course, and whether the student ever took remedial math or English. Ultimately, the curriculum intensity measure had 31 gradations, meaning levels of academic intensity, which were then aggregated into five quintiles for simplified categorization. Adelman showed that curriculum intensity was significantly related to college outcomes. Attewell and Domina ([<reflink idref="bib2" id="ref16">2</reflink>]) used Adelman's intensity measure with data from the 1988 National Educational Longitudinal Survey (NELS:88) to estimate the impact of high academic intensity on students' secondary and postsecondary outcomes. They employed a propensity score method in which students in adjacent coursework levels were compared (i.e., highest academic intensity quintile versus the second‐highest quintile) and found that students who had more intense academic intensity had higher twelfth‐grade test scores (math, reading, and SAT/ACT) and probabilities of college entry and completion.</p> <p>The consequences of choosing one measure of coursework intensity over the others are unclear. Using the highest course taken in mathematics as a proxy for coursework intensity (e.g., Byun et al., [<reflink idref="bib4" id="ref17">4</reflink>]) is a simple and easily understandable proxy for coursework intensity, but it does not directly measure coursework in other subjects. Indices like Adelman's can be difficult to create and are not easy to apply outside the two NCES (National Center for Education Statistics) datasets (i.e., the High School and Beyond survey and NELS:88) because of the many subjective decisions involved in creating the index. Moreover, measures may place different degrees of emphasis on the quality (rigor) or quantity (number of credits earned) of courses taken. Adelman ([<reflink idref="bib1" id="ref18">1</reflink>]) weighed the quantity of course‐taking more heavily than the quality, whereas Long et al. ([<reflink idref="bib10" id="ref19">10</reflink>]) focused primarily on the quality of the courses taken. Predicted outcomes may vary, depending on the coursework intensity measure used. Models that employ mathematics‐only measures, for example, cannot distinguish between students who take the same mathematics courses but different non‐mathematics courses (all else equal) and will therefore predict the same college enrollment probabilities for all such students. At the same time, mathematics courses may be so strongly correlated with overall coursework that additional course information will add little predictive power; similarly, course quantity may be so closely related to quality that the predictive ability of quantity‐ and quality‐based measures are not substantially different. To evaluate this empirically, we compared different measures of academic intensity by examining gaps in intensity across diverse groups of students, as well as their strength and validity in predicting secondary and postsecondary outcomes.</p> <hd id="AN0174011104-4">Gaps in Coursework Across Student Subgroups</hd> <p></p> <hd id="AN0174011104-5">Race/ethnicity</hd> <p>Studies have shown that there are differences in coursework intensity and the relationship between intensity and postsecondary outcomes across racial and ethnic groups. Adelman ([<reflink idref="bib1" id="ref20">1</reflink>]) showed that the relationship between high school academic intensity and degree completion was more pronounced for Black and Latino students than for White students. Moreover, Long et al. ([<reflink idref="bib10" id="ref21">10</reflink>]) showed that Black and Hispanic students had lower rates of rigorous course‐taking among a cohort of students who graduated from high schools in Florida in the 2002–2003 school year. They also found that the impact of taking at least one rigorous course by the fall of tenth grade was higher for Black and Hispanic students on high school graduation than for White students. In contrast, using the highest math course taken to measure academic intensity, Byun et al. ([<reflink idref="bib4" id="ref22">4</reflink>]) found that the impact of taking an advanced math course during any time in high school on math achievement was lower for Black students than for White students.</p> <p>Using a modified version of the Adelman index (terciles instead of quintiles), along with a propensity score method, Jha and Stearns ([<reflink idref="bib8" id="ref23">8</reflink>]) found that the impact of course intensity on attaining a 4‐year college degree differed among racial groups. For example, Asian American and American Indian/Alaskan Native students in the middle course intensity tercile and Asian American students in the high course intensity tercile were more likely to earn at least a 4‐year college degree than same‐race students in the low course intensity tercile. They also found that Black students following the lowest course intensity level were more likely than White students at the same course level to obtain 4‐year college degrees. In contrast, at the higher course intensity levels, White students were more likely to obtain 4‐year degrees than Black students.</p> <hd id="AN0174011104-6">Socioeconomic status (SES)</hd> <p>Studies have shown differences in coursework rigor by socioeconomic status. Long et al. ([<reflink idref="bib10" id="ref24">10</reflink>]) showed that students receiving free‐ or reduced‐price lunch and students from high‐poverty schools had lower rates of rigorous course‐taking. They found that taking a rigorous math course before the fall of tenth grade had a higher impact on the probability of receiving a high school diploma for lower SES students than for students of higher SES. Taking at least one rigorous course in any of math, English, science, or social science had larger effects on the probability of receiving a high school diploma and going to a 2‐year college for lower SES students than for higher SES students. Similarly, Byun et al. ([<reflink idref="bib4" id="ref25">4</reflink>]) found that for students of low SES, advanced math course‐taking had a greater effect than for students with a higher SES. While math course‐taking plays a significant role in college enrollment, the findings did not suggest any variation across students of different SES and racial/ethnic backgrounds. Attewell and Domina ([<reflink idref="bib2" id="ref26">2</reflink>]) reported that students from lower SES backgrounds had less rigorous coursework than students from higher SES backgrounds. They also showed that there was an interaction between race and SES: controlling for SES, Black students had higher probabilities of taking more rigorous coursework than White students. However, because most of the Black and Hispanic students were from lower SES, on average, they took less intensive courses than White students.</p> <hd id="AN0174011104-7">Coursework Intensity Across Grades</hd> <p>There is considerable evidence for the relationship between the intensity of the complete set of courses taken in high school and postsecondary outcomes, but less is known about grade‐level coursework intensity and how they relate to student outcomes. There is some literature on the timing of coursework. For example, Gottfried and Plasman ([<reflink idref="bib6" id="ref27">6</reflink>]) investigated the impact of the timing of career technical education (CTE) courses on postsecondary outcomes. Their results showed that regardless of the timing, taking CTE course was associated with higher postsecondary enrollment, but the effect was larger for taking the CTE courses toward the end of high school. Although Long et al. ([<reflink idref="bib10" id="ref28">10</reflink>]), as discussed earlier, also examined the effect of advanced course‐taking by the fall of Grade 10 and found positive impacts on student outcomes, there was no systematic examination of how the intensity of students' coursework changes across grades and how grade‐level indices related to postsecondary outcomes. By creating and examining grade‐level coursework intensities, this study aimed to fill this void.</p> <hd id="AN0174011104-8">Current Study</hd> <p>Much of the existing knowledge about high school coursework in the nation's schools originates from relatively outdated data. The most recent data was from the ELS:2002 for students who were tenth graders in 2002. This study builds on current research using data from the HSLS:09, the most recent nationally representative dataset. HSLS:09 standardized the course information in the transcripts of the students across the nation using the NCES School Courses for the Exchange of Data (SCED) system to allow the analysis of coursework data at the national level.</p> <p>We used transcript data to construct comprehensive and multisubject measures of coursework intensity. We created three measures, which differ in the emphasis placed on the quantity and quality of the coursework students completed. The first measure depends mostly on the quantity of coursework (i.e., the number of credits received) in core academic subjects but uses quality as a tiebreaker. The second measure uses both the quality and quantity of coursework. The third measure depends mostly on the quality of coursework, namely the highest math, science, and English courses completed. To provide a contrast, we examined two coursework intensity measures employed in literature: Adelman ([<reflink idref="bib1" id="ref29">1</reflink>]), which is based on the number of credits received in core academic subjects and the highest math course completed. Note that we use the term "quality" to describe the level of advancement of courses taken, not the quality of instruction or implementation.</p> <p>Ensuring students finish high school with rigorous coursework is important. But measuring students' coursework intensity at the end of high school for the complete set of courses taken is not extremely helpful if the purpose is to keep the student on track to having high‐intensity coursework. Without a grade‐level measure of intensity, we cannot track students' progress across levels of intensity while the students are still in high school and have the chance to change their trajectory. Unfortunately, no grade‐level coursework intensity measures exist in the literature. This study aims to fill that void by creating grade‐level coursework intensities and exploring the relationship among grade‐level intensities and how students advance in coursework intensity across grades.</p> <p>The goals of this study were threefold. First, we examined overall and grade‐level coursework intensity among all students as well as underserved students, such as Black and Hispanic students, students with disabilities, low socioeconomic status students, and students whose parents did not attend college. Second, we studied grade‐level progression in students' coursework intensity. Finally, we investigated how coursework intensity is related to student outcomes, including high school graduation, college enrollment, selectivity of the colleges in which students enroll, whether students choose a STEM (Science, Technology, Engineering, or Mathematics) major, and persistence in postsecondary education.</p> <hd id="AN0174011104-9">Method</hd> <p></p> <hd id="AN0174011104-10">Data</hd> <p>The data came from the HSLS:09, a nationally representative, longitudinal study of students who were in the ninth grade in 2009. Students, their parents, mathematics and science teachers, school administrators, and school counselors were surveyed. The first data collection occurred in the fall of 2009 when students were starting ninth grade. The second data collection occurred in the spring of 2012 when most students were completing the eleventh grade. Transcript data were collected from the schools in 2013 after most students had completed high school. The students were contacted in 2016, 2 years after their expected high school graduation, to gather information about their educational and occupational experiences (National Center for Education Statistics, [<reflink idref="bib12" id="ref30">12</reflink>]).</p> <hd id="AN0174011104-11">Student data</hd> <p>Student characteristics, parent]al education, and earnings as reported by parents, and the outcome variables were drawn from HSLS:09 student and parent data collected in the base year and 2016 follow‐up. The background variables included gender, race/ethnicity, disability status, English language learner status, SES, and parental education.</p> <hd id="AN0174011104-12">Transcript data</hd> <p>Our coursework intensity measures were constructed using information from the transcript data. The transcript data file contains information from students' transcripts on each student's course enrollment and completion status, with courses coded using the NCES School Courses for the Exchange of Data (SCED) system, which provides a uniform classification of courses across schools. Each record provided the data for one course taken by a student in a particular grade or year. The data included grade level, semester, credit received, SCED codes, course name, and grade received.</p> <p>After processing the transcript data (details can be found in the supplemental file), we merged it with student demographic and outcome data to create the analytical sample. Since the Adelman index uses all academic courses taken in high school, for comparability purposes across different measures of coursework intensity, the analytical sample was limited to students who had 4 years of transcript data (<emph>N</emph> ≈ 11,340). In addition, we used two composite variables HSLS:09 provided: highest math course taken and within‐subject course levels (General, Specialty, Advanced, and AP/International Baccalaureate [IB]) for biology, chemistry, and physics.</p> <hd id="AN0174011104-13">Measures of Coursework Intensity</hd> <p>We created three new data‐driven measures of coursework intensity and two measures of intensity used in the literature (the highest mathematics course taken), and the Adelman ([<reflink idref="bib1" id="ref31">1</reflink>]) measure. All these measures can be conceptualized based on two characteristics of course‐taking: quantity (i.e., the number of credits received) and quality (how advanced the courses taken are). Indices were created for all courses taken at the end of high school and for courses taken by each grade. The ninth‐grade measure was based on courses in ninth grade only. The tenth‐grade measure included courses taken in ninth or tenth grade. The eleventh‐grade measure used courses taken in ninth, tenth, or eleventh grades. Following Adelman ([<reflink idref="bib1" id="ref32">1</reflink>]), we created quintiles for the end‐of‐high school intensity measures to ensure roughly equal percentages of students within each level of the coursework intensity measure. Each quintile measure is an ordinal variable taking integer values from 1 (lowest) to 5 (highest). The grade‐level measures, due to a lack of sufficient variation in quantity and/or quality of coursework, were based on terciles (low, medium, and high).</p> <p>Adelman index. The intensity measure developed by Adelman ([<reflink idref="bib1" id="ref33">1</reflink>]) was based primarily on the number of credits earned in six subject areas: English language arts (ELA), mathematics, science, history, social studies, and foreign languages. Additional criteria, such as the presence of remedial courses on students' transcripts, the number of AP credits earned, the highest math course, and the presence of computer science credits, were used by Adelman to distinguish some, but not all, levels. We used the cutoffs and other criteria that Adelman ([<reflink idref="bib1" id="ref34">1</reflink>]) employed to create the gradations and HSLS:09 survey weights to create the quintiles. (Additional information can be found in the supplemental file.)</p> <p>Coursework credit index. This index, like Adelman's, was designed to measure coursework intensity, accounting for all academic subjects, by using a scale based upon student rankings in multiple course‐taking variables. In brief, students were ranked across the nation according to their values in each of multiple course‐taking variables, such as credits earned in ELA and highest mathematics course, then assigned an overall rank using their lowest (worst) rank across the variables. Students were then partitioned into quintiles according to their overall rank, and the quintile rank was used as their intensity level. The lowest rank was used to ensure that all students at a given level met certain minimum requirements, as with the Adelman index.</p> <p>There are two potential advantages of this approach. First, it is a relative measure of intensity that relies solely on order rather than on an absolute measure with cutoffs that may not be useful across different populations and periods. Second, quality and quantity may be captured to varying degrees, via the selection of input variables.</p> <p>The coursework credit index implemented for this study was designed primarily to capture quantity and used six variables: the highest math course taken; credits earned in mathematics, ELA, social sciences, and natural sciences (biology, chemistry, and physics); and "elective" credits, defined as the sum of credits earned in foreign languages, computer science, and engineering.</p> <p>Coursework rigor index. This measure was created using the procedure developed for the coursework credit index but placed greater emphasis on course "quality." Its input variables comprised honors, AP, and IB course credits, rather than total course credits, in each of the subject areas above—mathematics, English, social sciences, natural sciences, and combined foreign language, computer science, and engineering courses.</p> <p>Highest mathematics course. This ordinal variable was developed by HSLS:09. It consists of a 13‐level "highest mathematics course" variable derived from student transcript data. The values range from "Below Algebra I" through "AP/IB Calculus." We collapsed this variable into quintiles to make the metric comparable with the other measures.</p> <p>Highest courses in mathematics, science, and English (highest MSE). This measure augments the highest mathematics course measure with information from science and English courses to break ties among students. Students are first sorted by highest mathematics course level, then sorted within highest mathematics levels by highest science, then within mathematics and science levels by English. For comparability purposes across different measures, we again partitioned students into quintiles using this ordering and used the resulting quintiles as intensity levels in our analyses. (More information can be found in the supplemental file.)</p> <hd id="AN0174011104-14">Outcome Measures</hd> <p>The outcome variables were constructed from data collected in the second follow‐up and include an HSLS:09 Algebra assessment at Grade 11, college enrollment status for the first postsecondary institution (no college, less than 2 years, 2 years, and 4 years), Integrated Postsecondary Education Data System (IPEDS) selectivity of first postsecondary institution enrolled (no college; selectivity not classified, less than 2 years; selectivity not classified, 2 years; selectivity not classified, 4 years; inclusive, 4 years; moderately selective, 4 years; and highly, selective, 4 years), remedial course‐taking after high school (as reported by the student), selecting a STEM major (STEM vs. not as defined by HSLS:09), and persistence (measured as whether students were still registered at any postsecondary education or received any degree by the fall of 2016 when the data collection occurred).</p> <hd id="AN0174011104-15">Analysis</hd> <p>To examine the characteristics of different measures and their relationship, we used the distributions of credits taken for each subject across the levels of the coursework intensity measures and pairwise correlations. To examine gaps in coursework intensity, we computed the proportion of students at each coursework intensity level, both overall and disaggregated by the following characteristics: gender, race/ethnicity, disability status, English language learner status, SES, and parental education, and computed the differences in average coursework intensity for these characteristics. The disparities in coursework across groups were tested using simple regression models with intensity as the dependent variable and levels of the students' characteristics (e.g., race with five dummy variables, Black, Hispanic, Asian, American Indian/Alaska Native, and more than one race) as the independent variables. Pairwise correlations were used to examine the relationship between different measures of coursework intensity and student outcomes.</p> <hd id="AN0174011104-16">Results</hd> <p></p> <hd id="AN0174011104-17">Characteristics of the Sample</hd> <p>The full sample of HSLS:09 included (<emph>N</emph> ≈ 12,960) students who participated in the base year and second follow‐up and had transcript data. The analytic sample (<emph>N</emph> ≈ 11,340) consisted of students in the full sample who had complete transcript information for all grades in high school. Summary statistics for key variables for both samples are presented in Table 1. The two samples were similar in that there were no statistically significant differences between them on any of the variables presented (α = 0.05). The weighted analytical sample was 50% female, 2% English language learner students, and 32% students with a disability. The proportion of students identified as having a disability was unusually high, because we used student‐reported disabilities and created a binary indicator corresponding to whether a student has any disability. About 53% of the sample was White, 13% was Black, 22% was Hispanic, and 4% was Asian. Eight percent of students had parents with less than a high school education, 39% with high school diplomas, 17% with associate degrees, 22% with bachelor's degrees, and 10% with advanced degrees (master's or PhD).</p> <p>1 Table Summary Statistics for Full HSLS:09 Sample and Analytical Sample</p> <p> <ephtml> <table><thead><tr><th /><th align="center">Full Sample</th><th align="center">Analytic Sample</th></tr><tr><th>Variable</th><th align="center"><italic>N</italic></th><th align="center">Mean</th><th align="center">SE</th><th align="center"><italic>N</italic></th><th align="center">Mean</th><th align="center">SE</th></tr></thead><tbody><tr><td>Male</td><td>6,290</td><td>0.504</td><td>0.008</td><td>5,490</td><td>0.502</td><td>0.008</td></tr><tr><td>Female</td><td>6,670</td><td>0.496</td><td>0.008</td><td>5,850</td><td>0.498</td><td>0.008</td></tr><tr><td>ELL</td><td>210</td><td>0.027</td><td>0.004</td><td>180</td><td>0.024</td><td>0.003</td></tr><tr><td>Disability</td><td>3,670</td><td>0.324</td><td>0.008</td><td>3,160</td><td>0.316</td><td>0.008</td></tr><tr><td>White</td><td>7,500</td><td>0.517</td><td>0.011</td><td>6,700</td><td>0.531</td><td>0.012</td></tr><tr><td>Black</td><td>1,240</td><td>0.136</td><td>0.009</td><td>1,020</td><td>0.126</td><td>0.009</td></tr><tr><td>Hispanic</td><td>1,940</td><td>0.221</td><td>0.009</td><td>1,630</td><td>0.218</td><td>0.009</td></tr><tr><td>Asian</td><td>1,080</td><td>0.041</td><td>0.004</td><td>980</td><td>0.044</td><td>0.005</td></tr><tr><td>SES Quintile 1—lowest</td><td>1,660</td><td>0.192</td><td>0.008</td><td>1,390</td><td>0.181</td><td>0.009</td></tr><tr><td>SES Quintile 2</td><td>1,990</td><td>0.195</td><td>0.007</td><td>1,740</td><td>0.193</td><td>0.007</td></tr><tr><td>SES Quintile 3</td><td>2,170</td><td>0.206</td><td>0.006</td><td>1,910</td><td>0.203</td><td>0.007</td></tr><tr><td>SES Quintile 4</td><td>2,730</td><td>0.205</td><td>0.006</td><td>2,450</td><td>0.210</td><td>0.007</td></tr><tr><td>SES Quintile 5—highest</td><td>3,810</td><td>0.202</td><td>0.008</td><td>3,500</td><td>0.211</td><td>0.008</td></tr><tr><td>PE high school</td><td>4,300</td><td>0.403</td><td>0.009</td><td>3,630</td><td>0.391</td><td>0.010</td></tr><tr><td>PE associate's</td><td>1,970</td><td>0.166</td><td>0.005</td><td>1,720</td><td>0.167</td><td>0.006</td></tr><tr><td>PE bachelor's</td><td>3,310</td><td>0.211</td><td>0.006</td><td>2,970</td><td>0.219</td><td>0.007</td></tr><tr><td>PE advanced</td><td>1,780</td><td>0.099</td><td>0.004</td><td>1,630</td><td>0.105</td><td>0.004</td></tr></tbody></table> </ephtml> </p> <p>1 SES = HSLS:09 socioeconomic status index; PE = parental education.</p> <p>2 <emph>Data source</emph>: U.S. Department of Education, National Center for Education Statistics, HSLS:09.</p> <hd id="AN0174011104-18">Characteristics of the Coursework Intensity Measures</hd> <p>Table 2 displays the average credits for each subject among students at each level in each of the five coursework intensity measures (Table A1 in the supplemental file shows the average and minimum credits). It is worth noting that the mean number of credits is significantly higher than Adelman ([<reflink idref="bib1" id="ref35">1</reflink>]) observed among students who were in Grade 12 in 1992, reflecting the trend toward taking more academic courses over time. The minimum thresholds (see Table A1) have also increased across the years. In the highest quintile, the minimum credits for English and math increased from 3.67 in the Adelman index to 4 in the coursework credit index. In fact, math, English, and social sciences all have minimum thresholds of 4 credits.</p> <p>2 Table Mean Course Credits by Coursework Intensity Measure Quintile and Course Subject</p> <p> <ephtml> <table><thead><tr><th>Measure</th><th align="center">Quintile</th><th align="center">English</th><th align="center">Math</th><th align="center">Science</th><th align="center">Soc. Sci.</th><th align="center">Electives</th></tr></thead><tbody><tr><td>Adelman</td><td>5</td><td>4.80</td><td>4.65</td><td>4.46</td><td>4.74</td><td>4.46</td></tr><tr><td /><td>4</td><td>4.44</td><td>4.18</td><td>3.95</td><td>4.30</td><td>3.18</td></tr><tr><td /><td>3</td><td>4.61</td><td>4.11</td><td>3.70</td><td>4.18</td><td>2.88</td></tr><tr><td /><td>2</td><td>4.57</td><td>3.67</td><td>3.17</td><td>3.90</td><td>1.91</td></tr><tr><td /><td>1</td><td>3.36</td><td>2.91</td><td>2.60</td><td>3.10</td><td>1.49</td></tr><tr><td>Credit index</td><td>5</td><td>4.88</td><td>4.78</td><td>4.79</td><td>5.09</td><td>4.22</td></tr><tr><td /><td>4</td><td>4.75</td><td>4.44</td><td>3.76</td><td>4.54</td><td>3.17</td></tr><tr><td /><td>3</td><td>4.46</td><td>3.70</td><td>3.75</td><td>3.68</td><td>3.32</td></tr><tr><td /><td>2</td><td>4.35</td><td>3.99</td><td>3.34</td><td>4.01</td><td>2.16</td></tr><tr><td /><td>1</td><td>3.41</td><td>2.61</td><td>2.32</td><td>2.88</td><td>1.25</td></tr><tr><td>Rigor index</td><td>5</td><td>4.43</td><td>4.32</td><td>4.29</td><td>4.63</td><td>3.62</td></tr><tr><td /><td>4</td><td>4.45</td><td>4.32</td><td>3.98</td><td>4.18</td><td>3.29</td></tr><tr><td /><td>3</td><td>4.54</td><td>4.03</td><td>3.61</td><td>4.24</td><td>2.98</td></tr><tr><td /><td>2</td><td>4.56</td><td>3.86</td><td>3.40</td><td>3.91</td><td>2.50</td></tr><tr><td /><td>1</td><td>3.79</td><td>2.78</td><td>2.40</td><td>3.21</td><td>1.37</td></tr></tbody></table> </ephtml> </p> <ulist> <item>3 Soc. Sci. = social sciences; Electives = foreign languages, computer science, and engineering.</item> <item>4 <emph>Data source</emph>: U.S. Department of Education, National Center for Education Statistics, HSLS:09.</item> </ulist> <p>The indices created from the highest math and highest MSE did not have the monotonic relationships in the minimum number of credits required to achieve distinct levels of the indices (Table A2). However, they were driven mostly by the highest math course taken (Table 3).</p> <p>3 Table Percentage of Students Taking Selected Courses as Their Highest Course, by Coursework Intensity Measure Quintile and Course Subject</p> <p> <ephtml> <table><thead><tr><th /><th align="center">Highest Math Quintile</th><th align="center">Highest MSE Quintile</th></tr><tr><th>Coursework</th><th align="center">5</th><th align="center">4</th><th align="center">3</th><th align="center">2</th><th align="center">1</th><th align="center">5</th><th align="center">4</th><th align="center">3</th><th align="center">2</th><th align="center">1</th></tr></thead><tbody><tr><td align="center">Mathematics</td></tr><tr><td>Algebra I or lower</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>15.1</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>19.3</td></tr><tr><td>Geometry</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>24.4</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>31.2</td></tr><tr><td>Algebra II</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>60.5</td><td>0.0</td><td>0.0</td><td>0.0</td><td>68.3</td><td>49.6</td></tr><tr><td>Trigonometry</td><td>0.0</td><td>0.0</td><td>0.0</td><td>100.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>17.1</td><td>31.7</td><td>0.0</td></tr><tr><td>Other advanced</td><td>0.0</td><td>0.0</td><td>69.9</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>59.0</td><td>0.0</td><td>0.0</td></tr><tr><td>Prob. and statistics</td><td>0.0</td><td>0.0</td><td>30.1</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.4</td><td>23.9</td><td>0.0</td><td>0.0</td></tr><tr><td>Other AP/IB math</td><td>0.0</td><td>7.9</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>8.5</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>Precalculus</td><td>0.0</td><td>92.1</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10.0</td><td>90.1</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>Calculus</td><td>29.7</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>26.8</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>AP/IB Calculus</td><td>70.3</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>63.3</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td align="center">Science</td></tr><tr><td>No science</td><td>0.0</td><td>0.1</td><td>1.6</td><td>1.1</td><td>7.7</td><td>0.0</td><td>0.1</td><td>1.3</td><td>0.7</td><td>9.8</td></tr><tr><td>General science</td><td>26.5</td><td>47.7</td><td>61.1</td><td>58.6</td><td>68.5</td><td>23.9</td><td>51.3</td><td>53.8</td><td>41.0</td><td>83.3</td></tr><tr><td>Specialty science</td><td>20.2</td><td>27.7</td><td>28.6</td><td>32.2</td><td>20.0</td><td>18.2</td><td>29.8</td><td>36.0</td><td>49.3</td><td>5.7</td></tr><tr><td>Advanced science</td><td>7.0</td><td>8.8</td><td>4.4</td><td>2.8</td><td>3.0</td><td>6.3</td><td>10.0</td><td>4.2</td><td>6.6</td><td>1.2</td></tr><tr><td>AP/IB science</td><td>46.3</td><td>15.8</td><td>4.4</td><td>5.3</td><td>0.8</td><td>51.6</td><td>8.9</td><td>4.7</td><td>2.4</td><td>0.0</td></tr><tr><td>English</td></tr><tr><td>AP/IB English</td><td>52.4</td><td>31.9</td><td>11.0</td><td>13.5</td><td>5.3</td><td>57.1</td><td>26.3</td><td>13.2</td><td>15.9</td><td>0.4</td></tr></tbody></table> </ephtml> </p> <ulist> <item>5 <emph>Note</emph>. Column values within mathematics and science may not sum to 100 due to rounding.</item> <item>6 <emph>Data source</emph>: U.S. Department of Education, National Center for Education Statistics, HSLS:09.</item> </ulist> <p>The highest level of the highest math measure included students who have taken AP/IB Calculus (70%) and Calculus (30%). Precalculus was a course taken by 92% of the students who were at the second‐highest level. In the highest MSE measure, the highest level consisted of students who have taken AP/IB Calculus (63%), Calculus (27%), Precalculus (10%), AP/IB science (52%), and AP/IB English (57%). At the lowest level, about half of students took Algebra II as their highest mathematics course, while the remaining students did not progress beyond geometry, Algebra I, or other lower‐level math courses. They mostly took general science courses (83%), and fewer than 1% took AP/IB English.</p> <p>The percentages of students taking courses as their highest course for coursework rigor index showed similar patterns (Table 4). The majority of the students at the highest level of coursework rigor index took Calculus (55%), 63% took AP/IB English (%63), and 43% of them also took advanced science. However, most of the students at the highest level of coursework credit index took precalculus (42%), general science (41%), and no AP/IB English (61%).</p> <p>4 Table Percentage of Students Taking Selected Courses as Their Highest Course, by Coursework Intensity Measure Quintile and Course Subject</p> <p> <ephtml> <table><thead><tr><th /><th align="center">Coursework Credits</th><th align="center">Coursework Rigor</th></tr><tr><th /><th align="center">5</th><th align="center">4</th><th align="center">3</th><th align="center">2</th><th align="center">1</th><th align="center">5</th><th align="center">4</th><th align="center">3</th><th align="center">2</th><th align="center">1</th></tr></thead><tbody><tr><td align="center">Mathematics</td></tr><tr><td>Below Algebra II</td><td>53.6</td><td>22.1</td><td>0</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Algebra II</td><td>19.6</td><td>29.5</td><td>31.9</td><td>36.8</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Trigonometry, probability, other advanced</td><td>14.4</td><td>22.3</td><td>26.9</td><td>29.7</td><td>22.1</td><td>0</td><td>0</td><td>100</td><td>19.9</td><td>0</td></tr><tr><td>Precalculus/other AP</td><td>7.3</td><td>15.1</td><td>26.4</td><td>19.5</td><td>41.5</td><td>0</td><td>0</td><td>0</td><td>55.4</td><td>45.3</td></tr><tr><td>Calculus</td><td>5.1</td><td>11</td><td>14.8</td><td>14</td><td>36.4</td><td>0</td><td>0</td><td>0</td><td>24.7</td><td>54.7</td></tr><tr><td align="center">Science</td></tr><tr><td>No science</td><td>15.4</td><td>1.1</td><td>0.4</td><td>0.2</td><td>0</td><td>17.5</td><td>1.3</td><td>1.8</td><td>0.1</td><td>0</td></tr><tr><td>General science</td><td>63.1</td><td>62.7</td><td>54.8</td><td>54.8</td><td>40.7</td><td>68.8</td><td>68.3</td><td>60.4</td><td>50.7</td><td>29.3</td></tr><tr><td>Specialty science</td><td>14.7</td><td>23.4</td><td>25.8</td><td>30.5</td><td>25.3</td><td>11.3</td><td>25.8</td><td>29.3</td><td>28.8</td><td>20.8</td></tr><tr><td>Advanced science</td><td>3.2</td><td>4.1</td><td>5.2</td><td>5.3</td><td>7.7</td><td>2.4</td><td>3.4</td><td>3.7</td><td>8.4</td><td>6.8</td></tr><tr><td>AP/IB science</td><td>3.6</td><td>8.7</td><td>13.8</td><td>9.2</td><td>26.3</td><td>0.1</td><td>1.3</td><td>4.9</td><td>12</td><td>43</td></tr><tr><td align="center">English</td></tr><tr><td>No AP/IB English</td><td>92.8</td><td>88.2</td><td>78.6</td><td>78</td><td>61.4</td><td>99.2</td><td>91.7</td><td>89.4</td><td>82.6</td><td>37.4</td></tr><tr><td>AP/IB English</td><td>7.2</td><td>11.8</td><td>21.4</td><td>22</td><td>38.6</td><td>0.8</td><td>8.3</td><td>10.6</td><td>17.4</td><td>62.6</td></tr></tbody></table> </ephtml> </p> <p>7 <emph>Note</emph>. Percentages add up to 100 within each subject area. <emph>Data source</emph>: U.S. Department of Education, National Center for Education Statistics, HSLS:09.</p> <p>The correlations between the indices were moderate to high, ranging from 0.46 to 0.93 for the indices using all courses in high school (Table 5). Adelman's measure had the highest correlation with the coursework credit index. The highest correlations overall, however, were between the coursework rigor index, highest MSE, and highest math measures, where correlations ranged from 0.84 to 0.93. Correlations among indices across grades (Table 6) show that the intensity measures in Grade 9 had the lowest correlations with their corresponding all‐grades measures. The correlations increased from grades 9 to 11, reaching 0.7 and higher at Grade 11, depending on the measure.</p> <p>5 Table Correlations among Measures of Coursework Intensity</p> <p> <ephtml> <table><thead><tr><th /><th align="center">Adelman</th><th align="center">Credit Index</th><th align="center">Rigor Index</th><th align="center">Highest MSE</th><th align="center">Highest Math</th></tr></thead><tbody><tr><td>Adelman</td><td>1.00</td><td /><td /><td /><td /></tr><tr><td>Credit index</td><td>0.76</td><td>1.00</td><td /><td /><td /></tr><tr><td>Rigor index</td><td>0.60</td><td>0.54</td><td>1.00</td><td /><td /></tr><tr><td>Highest MSE</td><td>0.59</td><td>0.50</td><td>0.92</td><td>1.00</td><td /></tr><tr><td>Highest Math</td><td>0.57</td><td>0.46</td><td>0.84</td><td>0.93</td><td>1.00</td></tr></tbody></table> </ephtml> </p> <p>6 Table Correlations between Measures of Coursework Intensity in Grades 9, 10, and 11 and Coursework Intensity Measured at Grade 12</p> <p> <ephtml> <table><thead><tr><th /><th align="center">Grade</th><th align="center">Credit Index</th><th align="center">Rigor Index</th><th align="center">Highest MSE</th><th align="center">Highest Math</th></tr></thead><tbody><tr><td>Credit index</td><td>9</td><td>0.50</td><td>0.38</td><td>0.36</td><td>0.34</td></tr><tr><td /><td>10</td><td>0.59</td><td>0.42</td><td>0.40</td><td>0.36</td></tr><tr><td /><td>11</td><td>0.72</td><td>0.43</td><td>0.41</td><td>0.38</td></tr><tr><td>Rigor index</td><td>9</td><td>0.28</td><td>0.53</td><td>0.54</td><td>0.53</td></tr><tr><td /><td>10</td><td>0.32</td><td>0.59</td><td>0.60</td><td>0.59</td></tr><tr><td /><td>11</td><td>0.40</td><td>0.71</td><td>0.71</td><td>0.70</td></tr><tr><td>Highest MSE</td><td>9</td><td>0.24</td><td>0.50</td><td>0.53</td><td>0.52</td></tr><tr><td /><td>10</td><td>0.23</td><td>0.49</td><td>0.54</td><td>0.55</td></tr><tr><td /><td>11</td><td>0.32</td><td>0.65</td><td>0.71</td><td>0.69</td></tr><tr><td>Highest math</td><td>9</td><td>0.19</td><td>0.43</td><td>0.48</td><td>0.49</td></tr><tr><td /><td>10</td><td>0.22</td><td>0.49</td><td>0.54</td><td>0.56</td></tr><tr><td /><td>11</td><td>0.30</td><td>0.63</td><td>0.69</td><td>0.70</td></tr></tbody></table> </ephtml> </p> <p>8 <emph>Data source</emph>: U.S. Department of Education, National Center for Education Statistics, HSLS:09.</p> <hd id="AN0174011104-19">Gaps in Coursework Intensity</hd> <p>For the overall high school coursework intensity measures, there were significant differences between male and female students on all five measures (Figure 1). Female students, on average, had higher coursework intensities, indicating that female students earned more credits or took more rigorous courses, on average. Across racial/ethnic groups, Asian students had on average the highest coursework intensity levels. White students had higher intensities than both Black and Hispanic students in three of the five measures, while the White‐Black difference was not statistically significantly different from zero for either the Adelman ([<reflink idref="bib1" id="ref36">1</reflink>]) index or the coursework credit index.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/EMS/01dec23/emip12577-fig-0001.jpg?ephost1=dGJyMNHX8kSepq84v%2bvlOLCmsE6epq5Srqa4SK6WxWXS" alt="emip12577-fig-0001.jpg" title="1 Gaps in Coursework Intensity for Five Coursework Intensity Measures, by Student Characteristics and Parental Education LevelNotes. Positive values indicate higher levels for the first group shown (e.g., Female in "Female‐Male"). *Value is statistically significantly different from zero (p < 0.05). ELL = English language learners; SWOD = students without disabilities; SWD = students with disabilities; Advanced = master's/professional degree or higher.Data source: U.S. Department of Education, National Center for Education Statistics, HSLS:09." /> </p> <p></p> <p>The results also showed that non‐ELL students, on average, took more rigorous courses than ELL students, which was reflected in all five coursework intensity measures (Figure 2). Similarly, students with disabilities (SWD) took less rigorous courses than students without disabilities (SWOD). Gaps in coursework intensity for ELL and non‐ELL students were larger than the gaps in the SWD and SWOD groups.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/EMS/01dec23/emip12577-fig-0002.jpg?ephost1=dGJyMNHX8kSepq84v%2bvlOLCmsE6epq5Srqa4SK6WxWXS" alt="emip12577-fig-0002.jpg" title="2 Gaps in Coursework Intensity for Five Coursework Intensity Measures, by ELL Status, Disability Status, and Parental Education LevelNotes. Positive values indicate higher levels for the first group shown (e.g., Female in "Female‐Male"). *Value is statistically significantly different from zero (p < 0.05). ELL = English language learners; SWOD = students without disabilities; SWD = students with disabilities; Advanced = master's/professional degree or higher.Data source: U.S. Department of Education, National Center for Education Statistics, HSLS:09." /> </p> <p></p> <p>Gaps in coursework intensity existed by parental education level, as well, with students of parents with higher education levels generally having higher coursework intensity levels. Gaps in coursework intensity appeared larger for parental education subgroups than gaps in racial/ethnic groups, gender, disability status, and ELL status.</p> <p>Comparing different measures of intensity, the results showed that the gaps in coursework intensity levels were generally smaller under the Adelman index and coursework credit index than the other indices. The intensity measures computed using the highest MSE led to slightly higher gaps than intensity using the highest math. The gaps in intensity using the coursework rigor index were lower than those of both the highest MSE and highest math.</p> <p>We also examined the gaps in coursework intensity across grades. We reported results from one measure, the coursework rigor index, because it incorporated quality and quantity, to a lesser degree, of course‐taking (Figure 2; the figure corresponding to the coursework credit index can be found in Figure A1 in the supplemental file). The results for the change in the gap across grades showed that when the measure mostly depends on the quantity of the courses taken, like the coursework credit index, the gaps in coursework intensity that existed in Grade 9 remained, on average, unchanged. However, when the intensity measures started giving more weight to the quality of the courses such as the coursework rigor index, the highest MSE, and the highest math, the gaps in coursework intensity increased by grade. Students who had higher‐intensity coursework in Grade 9 started reaching even higher‐intensity levels when they reached Grade 12. The subgroup differences observed for the coursework intensities for the complete high school courses also existed in grade‐level intensity measures (Figure 3).</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/EMS/01dec23/emip12577-fig-0003.jpg?ephost1=dGJyMNHX8kSepq84v%2bvlOLCmsE6epq5Srqa4SK6WxWXS" alt="emip12577-fig-0003.jpg" title="3 Gaps in Rigor Index for Grades 9–12, by Student Characteristics and Parental Education LevelNotes. Positive values indicate higher levels for the first group shown (e.g., Female in "Female‐Male"). *Value is statistically significantly different from zero (p < 0.05). ELL = English language learners; SWOD = students without disabilities; SWD = students with disabilities; Advanced = master's/professional degree or higher.Data source: U.S. Department of Education, National Center for Education Statistics, HSLS:09." /> </p> <p></p> <hd id="AN0174011104-23">Coursework Intensity and Student Outcomes</hd> <p>To examine unconditional relationships between student outcomes and coursework indices, we conducted pairwise correlations between student index values and a selection of postsecondary outcomes (Table 7). These findings are descriptive and are not meant to be interpreted as causal. Of the five measures, the highest MSE had the strongest correlation with enrollment in 4‐year college (0.53). The highest math and coursework rigor index had similarly high correlation coefficients. The coursework credit index had the weakest correlation with 4‐year college enrollment (0.37). The patterns of correlations were similar for selectivity of enrolled colleges, choosing a STEM major, taking remedial courses, and persistence in postsecondary education.</p> <p>7 Table Correlations between Coursework Intensity Measures and Postsecondary Outcomes</p> <p> <ephtml> <table><thead><tr><th>Measure</th><th align="center">Grade</th><th align="center">Four‐Year</th><th align="center">Two‐Year</th><th align="center">STEM</th><th align="center">Remedial</th><th align="center">Persistence</th><th align="center">Selectivity</th></tr></thead><tbody><tr><td>Adelman</td><td>12</td><td>0.43</td><td>−0.13</td><td>0.10</td><td>−0.10</td><td>0.18</td><td>0.49</td></tr><tr><td>Coursework credit index</td><td>9</td><td>0.29</td><td>−0.08</td><td>0.09</td><td>−0.14</td><td>0.09</td><td>0.33</td></tr><tr><td /><td>10</td><td>0.32</td><td>−0.09</td><td>0.09</td><td>−0.16</td><td>0.12</td><td>0.35</td></tr><tr><td /><td>11</td><td>0.33</td><td>−0.07</td><td>0.08</td><td>−0.14</td><td>0.14</td><td>0.37</td></tr><tr><td /><td>12</td><td>0.37</td><td>−0.07</td><td>0.08</td><td>−0.08</td><td>0.16</td><td>0.43</td></tr><tr><td>Coursework rigor index</td><td>9</td><td>0.33</td><td>−0.12</td><td>0.13</td><td>−0.20</td><td>0.13</td><td>0.36</td></tr><tr><td /><td>10</td><td>0.38</td><td>−0.13</td><td>0.15</td><td>−0.20</td><td>0.16</td><td>0.41</td></tr><tr><td /><td>11</td><td>0.42</td><td>−0.14</td><td>0.17</td><td>−0.21</td><td>0.20</td><td>0.46</td></tr><tr><td /><td>12</td><td>0.52</td><td>−0.18</td><td>0.21</td><td>−0.21</td><td>0.26</td><td>0.59</td></tr><tr><td>Highest MSE</td><td>9</td><td>0.30</td><td>−0.11</td><td>0.15</td><td>−0.17</td><td>0.12</td><td>0.33</td></tr><tr><td /><td>10</td><td>0.31</td><td>−0.15</td><td>0.18</td><td>−0.19</td><td>0.12</td><td>0.33</td></tr><tr><td /><td>11</td><td>0.39</td><td>−0.17</td><td>0.19</td><td>−0.21</td><td>0.18</td><td>0.42</td></tr><tr><td /><td>12</td><td>0.53</td><td>−0.21</td><td>0.24</td><td>−0.24</td><td>0.26</td><td>0.59</td></tr><tr><td>Highest math</td><td>9</td><td>0.29</td><td>−0.15</td><td>0.15</td><td>−0.17</td><td>0.11</td><td>0.30</td></tr><tr><td /><td>10</td><td>0.31</td><td>−0.16</td><td>0.18</td><td>−0.18</td><td>0.12</td><td>0.33</td></tr><tr><td /><td>11</td><td>0.36</td><td>−0.18</td><td>0.19</td><td>−0.21</td><td>0.17</td><td>0.39</td></tr><tr><td /><td>12</td><td>0.51</td><td>−0.21</td><td>0.24</td><td>−0.24</td><td>0.25</td><td>0.58</td></tr></tbody></table> </ephtml> </p> <p>9 <emph>Note</emph>. Four‐year and Two‐year = indicators for enrollment in four‐ and two‐year colleges, respectively; STEM = indicator for declaring a major in a STEM field; Remedial = indicator for student taking at least one remedial course after high school; Persistence = indicator for having earned a postsecondary degree or still being enrolled in a degree program as of fall 2016; Selectivity = indicator for student's first postsecondary institution classified as moderately or highly selective. <emph>Data source</emph>: U.S. Department of Education, National Center for Education Statistics, HSLS:09</p> <p>The results showed that the measures that incorporate the quality of the courses taken (i.e., coursework rigor index, and highest MSE) had higher correlations with the postsecondary outcomes than the measure that mostly uses the quantity of the courses taken (coursework credit index). The magnitude of correlations between the coursework intensity measures and student outcomes increased across grades, but the increases were higher for indices that focus on the quality of the coursework. Among the outcomes, the intensity measures generally were most strongly correlated with enrollment in a 4‐year college and the selectivity of enrolled institutions. Taken together, the results highlight the importance of coursework intensity in early grades.</p> <hd id="AN0174011104-24">Discussion</hd> <p>It is important to accurately measure coursework intensity to effectively examine the relationship between course‐taking and student postsecondary outcomes. Using transcript data from a recent cohort of students who started high school in 2009 (HSLS:09), we proposed several measures that vary with respect to the relative importance assigned to the quantity and quality of students' course‐taking. The correlations between the different indices we created were between moderate to high, ranging from 0.46 to 0.93 for the indices that used end‐of‐high school transcripts. Adelman's measure had the highest correlation with the coursework credit index. While it is well known, Adelman's ([<reflink idref="bib1" id="ref37">1</reflink>]) index is difficult to create in other datasets. Our results showed that we could create an index that mimics Adelman's ([<reflink idref="bib1" id="ref38">1</reflink>]) index but, we believe, is easier to describe, construct, and replicate in other settings or datasets. The highest correlations among all the measures created as part of this study were observed between the coursework rigor index, highest MSE, and highest math measures. This finding is not surprising because all these measures depended primarily on the quality of the courses students took.</p> <p>The way coursework indices are defined and created has implications for the results obtained, in some instances. In terms of gaps in coursework intensity among different student groups, all measures showed comparable results. Female students took more intense courses than male students, which was in line with prior studies (Long et al., [<reflink idref="bib10" id="ref39">10</reflink>]). Similarly, there were gaps in coursework intensity for English language learners; students with disabilities; lower SES students; and Black and Hispanic students relative to their counterparts. These results replicate some of the earlier findings in the literature (Adelman, 1999, [<reflink idref="bib1" id="ref40">1</reflink>]; Attewell & Domina, [<reflink idref="bib2" id="ref41">2</reflink>]; Byun et al., [<reflink idref="bib4" id="ref42">4</reflink>]; Jha & Stearns, [<reflink idref="bib8" id="ref43">8</reflink>]; Long et al., [<reflink idref="bib10" id="ref44">10</reflink>]). However, we found that the gaps in coursework intensity were larger when using measures of coursework intensity that focus more on the quality of the courses taken than the quantity of the credits earned, highlighting the importance of the quality of the courses.</p> <p>Unlike Adelman's ([<reflink idref="bib1" id="ref45">1</reflink>]) index, the measures we developed can be created at different grades. Grade‐level analyses also revealed that the differences in coursework intensity for student subgroups increased from Grade 9 to Grade 12 for indices that give more weight to the quality of the courses. The coursework intensity gaps under these measures increased for all pairs of subgroups we examined except for the White and Asian students.</p> <p>In terms of the relationship between postsecondary outcomes and coursework intensity, our results, although not causal, support prior findings that high school coursework predicts postsecondary success (Adelman, [<reflink idref="bib1" id="ref46">1</reflink>]; Byun et al., [<reflink idref="bib4" id="ref47">4</reflink>]; Long et al., [<reflink idref="bib10" id="ref48">10</reflink>]; Morgan et al., [<reflink idref="bib11" id="ref49">11</reflink>]; Woods et al., [<reflink idref="bib14" id="ref50">14</reflink>]). Although the quantity of the credits received mattered in explaining variation in postsecondary outcomes, the results pointed to the importance of the quality of the courses taken. The measures that incorporate the quality of the courses taken (the coursework rigor index and highest MSE) had stronger associations with postsecondary outcomes than Adelman's measure and the coursework credit index, both of which depend primarily on the number of course credits earned. We expanded the evidence base for the correlations between high school coursework and postsecondary outcomes beyond enrollment to include the selectivity of enrolled colleges, choosing a STEM major, remedial course‐taking, and persistence in postsecondary education. High school coursework had a higher correlation with college enrollment and selectivity of the colleges enrolled than with choosing a STEM major, remedial course‐taking, and persistence. These results may point to the importance of other factors such as science or math identity, interest, motivation, or family finances for these outcomes.</p> <p>We also found a meaningful relationship between coursework intensity at earlier grades and postsecondary outcomes. However, the magnitude of the correlations became higher, as can be expected, for later grades that included courses taken in earlier grades and reached their peak at Grade 12. As with the end‐of‐high school measures, the grade‐specific measures that gave more weight to the quality of courses were more predictive of postsecondary outcomes than those that did not.</p> <p>Regardless of the measures used, we found coursework intensity to be associated with postsecondary outcomes. This is critical because coursework intensity could be increased by several different stakeholders. Students can change their course‐taking behavior, as corroborated by the increase in the number of students enrolling in advanced courses (e.g., Calculus). Policy changes that aim to increase coursework standards could increase the number of advanced courses available to the students or the students could be incentivized to take more challenging courses. For example, with the Algebra for All movement, many states required students to take Algebra I before ninth grade, with the idea that Algebra I acts as a gateway to more advanced course‐taking and success in high school. Similarly, states can adopt requirements for students to go through specific coursework, such as college and career‐ready coursework, and change graduation requirements like increasing the minimum number of mathematics credits required to graduate from high school (Federman, [<reflink idref="bib5" id="ref51">5</reflink>]). School‐level policies can encourage students generally, and specifically underserved students, to take more challenging courses. Schools can help students with navigating the coursework, provide mentoring, or offer encouragement about the importance of high school course‐taking for students who do not have parental involvement or knowledge of college admissions requirements and course prerequisites.</p> <p>We emphasize that, in the context of this study, the term "quality" refers strictly to the level of advancement of the course type, not to the quality of instruction or implementation. The intensity measures we created assume that students receive passing grades from the courses they enrolled in. This means that students have the prerequisite knowledge to be successful in the class, and merely enrolling all students into advanced courses will not necessarily lead to higher high school coursework intensities.</p> <hd id="AN0174011104-25">Acknowledgments</hd> <p>The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R305A190073 to the American Institutes for Research (AIR). The opinions expressed are those of the authors and do not represent the views of the Institute or the U.S. Department of Education.</p> <p>The authors have no relevant financial or nonfinancial interests to disclose.</p> <p>GRAPH: Does it Matter How the Rigor of High School Coursework is Measured? Gaps in Coursework Among Students and Across Grades</p> <ref id="AN0174011104-26"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> https://www2.ed.gov/about/offices/list/ovae/pi/hsinit/papers/nclb.pdf.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref16" type="bt">2</bibl> <bibtext> <ulink href="http://www.corestandards.org/wp-content/uploads/Math%5fStandards1.pdf;">http://www.corestandards.org/wp-content/uploads/Math%5fStandards1.pdf;</ulink> <ulink href="http://www.corestandards.org/wp-content/uploads/ELA%5fStandards1.pdf">http://www.corestandards.org/wp-content/uploads/ELA%5fStandards1.pdf</ulink>.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref7" type="bt">3</bibl> <bibtext> We also report results examining how students advance in coursework intensity across grades using Sankey diagrams in the Supplemental materials.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref9" type="bt">4</bibl> <bibtext> SCED codes are a common classification system for prior‐to‐secondary and secondary school courses. The first two digits indicate the subject area and are used to aggregate credits received within core academic courses.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref51" type="bt">5</bibl> <bibtext> In this study, we adopt the definition of STEM majors by the U.S. Department of Education (ED). Unlike the National Science Foundation's definition, the ED's SMART grant definition does not include psychology or the social and behavioral sciences, such as political science and economics, among the STEM fields.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref27" type="bt">6</bibl> <bibtext> Parental education is a composite variable created by HSLS:09 and measures the highest education level of either parent.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref8" type="bt">7</bibl> <bibtext> Bolding is added to highlight the correlations for the same measure across grades.</bibtext> </blist> </ref> <ref id="AN0174011104-27"> <title> References </title> <blist> <bibtext> Adelman, C. (2006). The Toolbox revisited: Paths to degree completion from high school to college. Washington, DC: U.S. Department of Education.</bibtext> </blist> <blist> <bibtext> Attewell, P., & Domina, T. (2008). Raising the bar: Curricular intensity and academic performance. Educational Evaluation and Policy Analysis, 30 (1), 51 – 71.</bibtext> </blist> <blist> <bibtext> Bozick, R., & Ingels, S. J. (2007). Mathematics coursetaking and achievement at the end of high school: Evidence from the Education Longitudinal Study of 2002 (ELS:2002) (NCES 2008–319). Washington, DC : U.S. Department of Education.</bibtext> </blist> <blist> <bibtext> Byun, S., Irvin, J., & Bell, A. (2015). Advanced math course taking: Effects on math achievement and college enrollment. Journal of Experimental Education, 83, 439 – 468.</bibtext> </blist> <blist> <bibtext> Federman, M. (2007). State graduation requirements, high school course taking, and choosing a technical college major. B.E. Journal of Economic Analysis & Policy, 7 (1), 1 – 32.</bibtext> </blist> <blist> <bibtext> Gottfried, M. A., & Plasman, J. S. (2018). Linking the timing of career and technical education coursetaking with high school dropout and college‐going behavior. American Educational Research Journal, 55 (2), 325 – 361.</bibtext> </blist> <blist> <bibtext> Horn, L., & Nuñez, A. M. (2000). Mapping the road to college: First‐generation students' math track, planning strategies, and context of support (NCES 2000–153). Washington, DC.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref23" type="bt">8</bibl> <bibtext> Jha, N. K., & Stearns, E. M. (2018). Race‐specific high school course intensity and student's post‐secondary education attainment. Research in Higher Education, 59, 765 – 791. https://doi.org/10.1007/s11162‐017‐9484‐9</bibtext> </blist> <blist> <bibl id="bib9" idref="ref3" type="bt">9</bibl> <bibtext> Leow, C., Marcus, S., Zanutto, E., & Boruch, R. (2004). Effects of advanced course‐taking on math and science achievement: Addressing selection bias using propensity scores. American Journal of Evaluation, 25, 461 – 478.</bibtext> </blist> <blist> <bibtext> Long, M. C., Conger, D., & Iatarola, P. (2012). Effects of high school course‐taking on secondary and postsecondary success. American Educational Research Journal, 49 (2), 285 – 322.</bibtext> </blist> <blist> <bibtext> Morgan, T. L., Zakhem, D., & Cooper, W. L. (2018). From high school access to postsecondary success: An exploratory study of the impact of high‐rigor coursework. Education Sciences, 8, 191.</bibtext> </blist> <blist> <bibtext> National Center for Education Statistics. (2018). High School Longitudinal Study of 2009. Retrieved, July 1, 2018 from https://nces.ed.gov/surveys/hsls09/</bibtext> </blist> <blist> <bibtext> Nord, C., Roey, S., Perkins, R., Lyons, M., Lemanski, N., Brown, J., & Schuknecht, J. (2011). The nation's report card: America's high school graduates: Results of the 2009 NAEP High School Transcript Study (NCES 2011–462). Washington, DC : U.S. Department of Education, National Center for Education Statistics.</bibtext> </blist> <blist> <bibtext> Woods, C., Park, T., Hu, S., & Betrand Jones, T. (2018). How high school coursework predicts introductory college‐level course success. Community College Review, 46 (2), 176 – 196.</bibtext> </blist> </ref> <aug> <p>By Burhan Ogut; Darrick Yee; Ruhan Circi and Nevin Dizdari</p> <p>Reported by Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib10" firstref="ref4"></nolink> <nolink nlid="nl2" bibid="bib11" firstref="ref5"></nolink> <nolink nlid="nl3" bibid="bib13" firstref="ref10"></nolink> <nolink nlid="nl4" bibid="bib14" firstref="ref14"></nolink> <nolink nlid="nl5" bibid="bib12" firstref="ref30"></nolink>
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  Data: Research shows that the intensity of high school course-taking is related to postsecondary outcomes. However, there are various approaches to measuring the intensity of students' course-taking. This study presents new measures of coursework intensity that rely on differing levels of quantity and quality of coursework. We used these new indices to provide a current description of variations in high school course-taking across grades and student subgroups using a nationally representative dataset, the High School Longitudinal Study of 2009. Results showed that for measures emphasizing the quality of coursework the gaps in coursework among underserved students were larger and there was less upward movement in rigor across grades. [This paper was published in "Educational Measurement: Issues and Practice" v42 n4 p42-52 2023.]
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      – PersonEntity:
          Name:
            NameFull: Ruhan Circi
      – PersonEntity:
          Name:
            NameFull: Nevin Dizdari
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
          Titles:
            – TitleFull: Grantee Submission
              Type: main
ResultId 1