ENDNOTES

1 All students’ names have been changed throughout.

2 McFarland, J., Hussar, B., Wang, X., Zhang, J., Wang, K., Rathbun, A., Barmer, A., Forrest Cataldi, E., & Bullock Mann, F. (2018). The condition of education 2018 (NCES 2018-144). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https:// nces.ed.gov/pubsearch/pubsinfo. asp?pubid=2018144

3 Latinx is a gender-neutral term that refers to individuals of Latin American origin or descent.

4 College remediation rates based on students starting at a four-year college. These rates are 60% among all students, 78% among Black students and 75% among Latinx students beginning at a two-year college. See Table 2 in Chen, X. (2016). Remedial coursetaking at US public 2-and 4-year institutions: Scope, experiences, and outcomes. Statistical Analysis Report (NCES 2016-405). Washington, DC: National Center for Education Statistics. Retrieved from https:// nces.ed.gov/pubs2016/2016405.pdf

5 Barry, M.N. & Dannenberg, M. (2016). Out of pocket: The high cost of inadequate high schools and high school student achievement on college affordability. Washington, DC: Education Reform Now and Education Post. Retrieved from https:// edreformnow.org/policy-briefs/ out-of-pocket-the-high-cost-of- inadequate-high-schools-and-high- school-student-achievement-on- college-affordability/

6 Achieve. (2015). Rising to the challenge: Are high school graduates prepared for college and work? Washington, DC: Achieve. Retrieved from https://www. achieve.org/rising-challenge

7 Drake, G., Pomerance, L., Rickenbrode, R., & Walsh, K. (2018). Teacher prep review. Washington, DC: National Council on Teacher Quality. Retrieved from https:// www.nctq.org/publications/2018- Teacher-Prep-Review

8 TNTP. (2015). The Mirage: Confronting the hard truth about our quest for teacher development. Brooklyn, NY: TNTP. Retrieved from https://tntp.org/publications/... the-mirage-confronting-the-truth- about-our-quest-for-teacher- development

9 Herold, B. & Molnar, M. (2014). Research Questions Common-Core Claims by Publishers. Education Week (March 3, 2014).

10 1,200 hours every year is based on a typical school year of 180 days, with 6.64 hours per school day. See National Center for Education Statistics. (2008). Number of hours in the school day and average number of days in the school year for public schools, by state: 2007–08. Schools and Staffing Survey (SASS). U.S. Department of Education Washington, DC: National Center for Education Statistics. Retrieved from https://nces.ed.gov/surveys/sass/tables_list.asp. See also McFarland, J., Hussar, B., Wang, X., Zhang, J., Wang, K., Rathbun, A., Barmer, A., Forrest Cataldi, E., & Bullock Mann, F. (2018). The condition of education 2018 (NCES 2018-144). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https:// nces.ed.gov/pubsearch/pubsinfo. asp?pubid=2018144

11 The adjusted cohort graduation rate in 2015-2016 was 84%, the highest it’s ever been. McFarland, J., Hussar, B., Wang, X., Zhang, J., Wang, K., Rathbun, A., Barmer, A., Forrest Cataldi, E., & Bullock Mann, F. (2018). The condition of education 2018 (NCES 2018-144). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https:// nces.ed.gov/pubsearch/pubsinfo. asp?pubid=2018144

12 National Center for Education Statistics. (2018). Digest of education statistics, 2016 (NCES 2017-094), Chapter 3. U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https://nces. ed.gov/pubsearch/pubsinfo. asp?pubid=2017094

13 NAEP defines four categories of trajectories based on the type and amount of credits earned in each core subject: rigorous, mid-level, standard, and below-standard. Across all our partner systems, 17% of students were in a rigorous trajectory, 45% were in a mid-level trajectory, 20% were in a standard trajectory and 17% were in a below-standard trajectory. See the Technical Appendix for more details about how we applied these definitions to our participating districts’ data. For the NAEP study, see: 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 (NCES 2011-462). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https://nces. ed.gov/nationsreportcard/pdf/ studies/2011462.pdf

14 We estimated the amount of learning in a classroom by comparing its students’ actual state standardized test scores to the state standardized test scores that were expected of them given how they had scored historically, as well as other characteristics like their race/ethnicity and family income. See the Technical Appendix for more details about this approach and additional analysis results. Throughout the report, we make the commonly used assumption that a difference of 0.25 standard deviations represents 9 months of learning. See Kane, T. J., & Staiger, D. O. (2012). Gathering feedback for teaching: Combining high-quality observations with student surveys and achievement gains. Research Paper. MET Project. Seattle, WA: Bill & Melinda Gates Foundation. Retrieved from https://eric.ed.gov/?id=ED5409...

15 We defined classrooms where students started the year behind as those classrooms where students’ average state standardized test score in the previous school year was at least 0.5 standard deviations (or 18 months) below the average score among all students in the state. For each key resource, we split this subset of classrooms in half so that one group represented the 50% of these classrooms with the highest-rated assignments, lessons, engagement, or expectations, and the other represented the 50% of classes with the lowest scores on these resources. See the Technical Appendix for more details about this approach.

16 Because only grade 3-12 students completed student surveys, these percentages exclude K-2 students.

17 Only classrooms that had a minimum number of submitted assignments, observed lessons, or student surveys were included. See the Technical Appendix for how we set these minima.

18 Assuming a single class contains 180 instructional hours in a school year, the average ELA, math, science, and social studies classroom in our study spent, respectively, 122, 127, 164, and 166 hours on assignments that were not appropriate for the grade. See the Technical Appendix for details on how we estimated the amount of class time spent with grade- appropriate assignments, with strong instruction, or engaged.

19 Though the amount of time in school varies state to state, in all analyses, we assume a single class requires 180 hours in a school year, or 9 months. See National Center for Education Statistics. (2008). Number of hours in the school day and average number of days in the school year for public schools, by state: 2007–08. Schools and Staffing Survey (SASS). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https://nces.ed.gov/surveys/ sass/tables_list.asp

20 See the Technical Appendix for more details on how we reviewed and analyzed districts’ curricular and assessment policies, as well as how we rated materials and assessments themselves.

21 Our definition of strong instruction did not require teachers to earn perfect scores on the four domains we observed—classroom culture, content, instructional practices, and student ownership— so it was possible for a lesson to be classified as “strong” but not have high ratings on every domain. In this example, many lessons (295) had the highest possible ratings on content, but lower ratings on instructional practices and student ownership. See the Technical Appendix for how we defined “strong instruction.”

22 Scherer, M. (2008). Learning: Who’s job is it? Educational Leadership, 66(3), p.7. Retrieved from http://www.ascd.org/ publications/educational- leadership/nov08/vol66/num03/ Learning@-Whose-Job-Is- It%C2%A2.aspx.

23 The interest, enjoyment, and concentration approach to measuring engagement is based on Shernoff, D., Csikszentmihalyi, M., Schneider, B., & Shernoff. E. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychological Quarterly, 18(2), pp. 158–176. https://doi.org/10.1521/scpq.1...

24 The survey questions we used to represent worth were partly adapted from Uekawa, K., Borman, K. & Lee, R. (2007). Student engagement in U.S. urban high school mathematics and science classrooms: Findings on social organization, race, and ethnicity. The Urban Review, 39(1), pp. 1–43. https://doi.org/10.1007/s11256- 006-0039-1. See the Technical Appendix for more details on how we used survey questions to categorize students’ perceptions of engagement and worth.

25 Romero, C. (2015). What we know about belonging from scientific research. Palo Alto, CA: Mindset Scholars Network. Retrieved from http://mindsetscholarsnetwork. org/wp-content/uploads/2015/09/ What-We-Know-About-Belonging.pdf

26 “Rarely” defined as having no more than one experience perceived as engaging and worthwhile. 28% never had an engaging and worthwhile experience and 13% rarely did (N = 2,427 students).

27 Rate based on 2012 “event dropouts,” which represent the “percentage of high school students who left high school between the beginning of one school year and the beginning of the next without earning a high school diploma or an alternative credential (e.g., a GED).” See Table 1 in Stark, P., & Noel, A.M. (2015). Trends in high school dropout and completion rates in the United States: 1972–2012 (NCES 2015-015). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https://nces.ed.gov/pubs2015/2...

28 On the other hand, the same student tended to be less engaged on days when they received higher-quality assignments. See the Technical Appendix for results on how engagement varied on different days based on the quality of assignments and lessons.

29 Teachers’ perceptions of the extent to which they talked to students about their interests and goals based on four survey items: To what extent do you engage in the following practices: (1) meet with students to discuss their learning progress; (2) meet with students to discuss their strengths and interests; (3) set learning goals with students; (4) communicate with individual students and their families about the aspirations they have for a student’s future. Teachers had four choices for each item: Never, Sometimes, Often, Daily or Almost Daily. We integer-coded teachers’ responses so that Never was a 1 and Daily or Almost Daily was a 4, took the average across all four items, and then classified this composite value into quartiles. Classrooms in the top quartile had an average engagement rate of 62% while classrooms in the bottom quartile had an average engagement rate of 46%.

30 All analyses using students’ letter grades were based on all grade 3-12 students in the participating district or participating CMO school, not just the subset of classrooms we visited. See the Technical Appendix for more details on how we used data on course grades for all students in the participating districts.

31 We ran a series of linear regression models predicting the typical quality of assignments and lessons provided to classrooms based on their demographic characteristics as well as a host of other controls, including prior achievement. Notably, there was still a statistically significant negative relationship between the percent of students from low- income families in a class and the average quality of assignments, even after controlling for prior achievement (p<0.01). See the Technical Appendix for our model specifications and Table A.13 in the Appendix for full model results.

32 For classes where at least 50% of the students were students of color, the typical percent of time spent with grade-appropriate assignments, with strong lessons, and engaged were respectively 23%, 9%, and 50%, while for classes with mostly white students, these values were 34%, 33%, and 62%. For classes where at least 75% of students were from low- income families, these values were respectively 20%, 8%, and 52%, compared to 44%, 41%, and 63% for classes where at least 75% of students were not from low-income families. Only classrooms that contained enough data to meet our inclusion rules were included; see the Technical Appendix for more details on these rules and further analysis comparing access to these key resources by student characteristics.

33 Some of the racial/ethnic disparities in test outcomes between students is likely due to “stereotype threat.” Stereotype threat is an experimentally established phenomenon that represents the negative effect on performance when students feel like they must perform well or risk confirming negative intellectual stereotypes. For example, female students have been stereotyped to be less intellectually strong in math, and thus female students’ math test performance likely underestimates their true abilities because the anxiety of having to disprove this negative stereotype lowers their performance on tests. This is particularly true when the student knows the test will be used for comparative purposes, as is the case in state standardized tests, ACT and SAT tests, and AP tests. Research has shown that stereotype threat can underestimate Black and Latinx students’ total SAT math and reading scores by about 40 points. Though this is a large effect, across our participating districts the difference between students of color and white students with the same course grade was about 100 points on both the SAT math and reading components. Thus, while stereotype threat plays a role in our findings, it likely does not explain them entirely. For a thorough understanding of stereotype threat, see Steele, C. (2010). Whistling Vivaldi: And other clues to how stereotypes affect us. New York, NY: W.W. Norton & Company. See also Logel, C. R., Walton, G. M., Spencer, S. J., Peach, J., & Mark, Z. P. (2012). Unleashing latent ability: Implications of stereotype threat for college admissions. Educational Psychologist, 47(1), 42-50. https:// doi.org/10.1080/00461520.2011 .611368

34 Classrooms with the most grade- appropriate assignments were defined as those classrooms whose average assignment score ranked in the top quartile; classrooms with the least grade-appropriate assignments were those who ranked in the bottom quartile.

35 Wilson, T. (2011). Redirect: The surprising new science of psychological change. New York, NY: Little Brown.

36 Wenzlaff, R. & Wagner, D. (2000). Thought suppression. Annual Review of Psychology, 51(1), pp. 59-91. https://doi.org/10.1146/annure...

37 Murphy, M.C., Kroeper, K., & Ozier, E. (2018). Prejudiced places: How contexts shape equality and how policy change them. Policy Insights from the Behavioral and Brain Sciences, 5(1), pp. 66-74. https://doi. org/10.1177/2372732217748671

38 Cherng, H. & Halpin, P. (2016). The importance of minority teachers: Student perceptions of minority versus white teachers. Educational Researcher, 45(7), pp. 407–420. https://doi. org/10.3102/0013189X16671718

 

 

For our complete methodology, including further explanation of our analytical approaches and full analysis results, see the Technical Appendix at tntp.org/opportunitymyth