Abstract
Considering the growth and promising outlook of STEM occupations and the significant need to diversify STEM, the present study explored Black and Latinx youths’ situated experiences with and perspectives on STEM education. Informed by the major tenets of a grounded theory qualitative method, we interviewed 24 middle and high school students about their perceptions of their math and science preparation, their pursuit of STEM pathways, and their persistence in these fields. Results suggested a major theme related to participants’ experiences navigating uneven pathways towards academic and STEM success. In relation to this major theme, five open themes emerged which included: (1) characteristics, behaviors, and beliefs related to success in math and science; (2) familial role in achievement and success; (3) the lived experience of school and STEM classes; (4) external barriers and supports related to academic success; and (5) STEM careers and world of work. Identifying the challenges and opportunities that Black and Latinx youth face in their math and science education may inform the development of STEM education programs that meet the needs of this population.
Similar content being viewed by others
References
Adams, J. H., Bright, D., Jackson, J., & Simmons, O. S. (2021). A holistic model for Black student success in STEM: The case for a comprehensive and holistic approach in building the pipeline. In W. Pearson Jr. & V. Reddy (Eds.), Social justice and education in the 21st century: From South Africa and the United States (pp. 195–219). Springer Nature. https://doi.org/10.1007/978-3-030-65417-7_11
Baird, M. D., Bozick, R., & Harris, M. (2017). Postsecondary education and STEM employment in the United States: An analysis of national trends with a focus on the natural gas and oil industry. Rand Corporation. https://www.api.org/~/media/Files/Policy/Jobs/STEM-Employment/RAND-Education-Report.pdf
Ball, C., Huang, K., Cotten, S. R., & Rikard, R. V. (2017). Pressurizing the STEM pipeline: An expectancy-value theory analysis of youths’ STEM attitudes. Journal of Science Education and Technology, 26, 372–382. https://doi.org/10.1007/s10956-017-9685-1
Barr, D. A., Gonzalez, M. E., & Wanat, S. F. (2008). The leaky pipeline: Factors associated with early decline in interest in premedical studies among underrepresented minority undergraduate students. Academic Medicine, 83(5), 503–511. https://doi.org/10.1097/ACM.0b013e31816bda16
Beckett, G. H., Hemmings, A., Maltbie, C., Wright, K., Sherman, M., & Sersion, B. (2016). Urban high school student engagement through cincy/STEM iTEST projects. Journal of Science Education and Technology, 25(6), 995–1008. https://doi.org/10.1007/s10956-016-9640-6
Beymer, P. N., Rosenberg, J. M., Schmidt, J. A., & Naftzger, N. J. (2018). Examining relationships among choice, affect, and engagement in summer STEM programs. Journal of Youth and Adolescence, 47, 1178–1191. https://doi.org/10.1007/s10964-018-0814-9
Blickenstaff, J. C. (2005). Women and science careers: Leaky pipeline or gender filter? Gender and Education, 17(4), 369–386. https://doi.org/10.1080/09540250500145072
Bottia, M. C., Stearns, E., Mickelson, R. A., & Moller, S. (2018). Boosting the numbers of STEM majors? The role of high schools with a STEM program. Science Education Policy, 102(1), 85–107. https://doi.org/10.1002/sce.21318
Burack, J. A., D’Arrisso, A., Ponizovsky, V., Troop-Gordon, W., Mandour, T., Tootoosis, C., & Fryberg, S. (2013). ‘Friends and grades’: Peer preference and attachment predict academic success among Naskapi youth. School Psychology International, 34(4), 371–386. https://doi.org/10.1177/0143034312446888
Carnegie Corporation of New York, & Institute for Advanced Study. (2009). The opportunity equation. Transforming mathematics and science education for citizenship and the global economy. https://media.carnegie.org/filer_public/80/c8/80c8a7bc-c7ab-4f49-847d-1e2966f4dd97/ccny_report_2009_opportunityequation.pdf
Carnevalle, A. P., Smith, N., & Melton, M. (2011). STEM: State-level analysis (Report ED525297). Georgetown University Center on Education and the Workforce. https://files.eric.ed.gov/fulltext/ED525307.pdf
Causadias, J. M., & Cicchetti, D. (2018). Cultural development and psychopathology. Development and Psychopathology, 30(5), 1549–1555. https://doi.org/10.1017/S0954579418001220
Chapman, A., Rodriguez, F. D., Pena, C., Hinojosa, E., Morales, L., Del Bosque, V., Tijerina, Y., & Tarawneh, C. (2019). “Nothing is impossible”: Characteristics of Hispanic females participating in an informal STEM setting. Cultural Studies of Science Education, 15, 723–737. https://doi.org/10.1007/s11422-019-09947-6
Charleston, L. J. (2012). A qualitative investigation of African Americans’ decision to pursue computing science degrees: Implications for cultivating career choice and aspiration. Journal of Diversity in Higher Education, 5(4), 222–243. https://doi.org/10.1037/a0028918
Chen, X., & Soldner, M. (2013). STEM attrition: College students’ paths into and out of STEM fields. National Center for Education Statistics. https://nces.ed.gov/pubs2014/2014001rev.pdf
Christensen, R., & Knezek, G. (2017). Relationship of middle school student STEM interest to career intent. Journal of Education in Science Environment and Health, 3(1), 1–13. https://doi.org/10.21891/jeseh.275649
Corbin, J., & Strauss, A. (2008). Basics of qualitative research: Techniques and procedures for developing grounded theory (3rd ed.). Sage.
Cotabish, A., Dailey, D., Robinson, A., & Hughes, G. (2013). The effects of a STEM intervention on elementary students’ science knowledge and skills. School Science and Mathematics, 113(5), 215–226. https://doi.org/10.1111/ssm.12023
Creswell, J. W. (2007). Qualitative inquiry and research design: Choosing among five approaches (2nd ed.). Sage.
Dooley, M., Payne, A., Steffler, M., & Wagner, J. (2017). Understanding the STEM path through high school and into university programs. Canadian Public Policy, 43(1), 1–16. https://doi.org/10.3138/cpp.2016-007
Dweck, C. S. (2006). Mindset: The new psychology of success. Random House.
Eccles, J. S. (1983). Female achievement patterns: Attributions, expectancies, values, and choice. Journal of Social Issues, 1, 1–26.
Eccles, J. S. (2009). Who am I and what am I going to do with my life? Personal and collective identities as motivators of action. Educational Psychologist, 44(2), 78–89. https://doi.org/10.1080/00461520902832368
Eccles, J. S., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., & Meece, J. L. (1983). Expectancies, values, and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motivation (pp. 75–146). W. H. Freeman.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(1), 109–132. https://doi.org/10.1146/annurev.psych.53.100901.135153
Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory: A developmental, social cognitive, and sociocultural perspective on motivation. Contemporary Educational Psychology, 61(4), 101857. https://doi.org/10.1016/j.cedpsych.2020.101859
Eccles, J., Wigfield, A., Harold, R., & Blumenfeld, P. (1993). Age and gender differences in children’s self- and task perceptions during elementary school. Child Development, 64(3), 830–847. https://doi.org/10.2307/1131221
Elias, M. J., & Haynes, N. M. (2008). Social competence, social support, and academic achievement in minority, low-income, urban elementary school children. School Psychology Quarterly, 23(4), 474–495. https://doi.org/10.1037/1045-3830.23.4.47
Farinde, A. A., Tempest, B., & Merriweather, L. (2014). Service learning: A bridge to engineering for underrepresented minorities [Special edition]. International Journal for Service Learning, 2014, 475–491. https://doi.org/10.24908/ijsle.v0i0.5579
Fassinger, R. E. (2005). Paradigms, praxis, problems, and promise: Grounded theory in counseling psychology research. Journal of Counseling Psychology, 52(2), 156–166. https://doi.org/10.1037/0022-0167.52.2.156
Fayer, S., Lacey, A., & Watson, A. (2017). BLS spotlight on statistics: STEM occupations-past, present, and future. United States Department of Labor. https://www.bls.gov/spotlight/2017/science-technology-engineering-and-mathematics-stem-occupations-past-present-and-future/pdf/science-technology-engineering-and-mathematics-stem-occupations-past-present-and-future.pdf
Fouad, N. A., & Santana, M. C. (2017). SCCT and underrepresented populations in STEM fields: Moving the needle. Journal of Career Assessment, 25(1), 24–39. https://doi.org/10.1177/1069072716658324
Funk, C., & Parker, K. (2018, January 9). Diversity in the STEM workforce varies widely across jobs. Pew Research Center. http://www.pewsocialtrends.org/2018/01/09/diversity-in-the-stem-workforce-varies-widely-across-jobs/
Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine.
Glesne, C. (2011). Becoming qualitative researchers: An introduction (4th ed.). Pearson.
Gottfried, M., Owens, A., Williams, D., Kim, H. Y., & Musto, M. (2017). Friends and family: A literature review on how high school social groups influence advanced math and science coursetaking. Education Policy Analysis Archives, 25, 1–26. https://doi.org/10.14507/epaa.25.2857
Grogan, K. (2019). How the entire scientific community can confront gender bias in the workplace. Nature Ecology & Evolution, 3, 3–6. https://doi.org/10.1038/s41559-018-0747-4
Grossman, J. M., & Porche, M. V. (2014). Perceived gender and racial/ethnic barriers to STEM success. Urban Education, 49(6), 698–727. https://doi.org/10.1177/0042085913481364
Haberman, M. (1991). The pedagogy of poverty versus good teaching. Phi Delta Kappan, 73(4), 290–294. https://doi.org/10.1177/003172171009200223
Hajovsky, D. B., Oyen, K. A., Chesnut, S. R., & Curtin, S. J. (2020). Teacher-student relationship quality and math achievement: The mediating role of teacher self-efficacy. Psychology in the Schools, 57(1), 111–134. https://doi.org/10.1002/pits.22322
Herman, J., Schmidt, I., Kessels, U., & Preckel, F. (2016). Big fish in big ponds: Contrast and assimilation effects on math and verbal self-concepts of students in within-school gifted tracks. British Journal of Educational Psychology, 86(2), 222–240. https://doi.org/10.1111/bjep.12100
Hernandez, J. C., & Lopez, M. A. (2007). Leaking pipeline: Issues impacting Latino/a college student retention. In A. Seidman (Ed.), Minority student retention: The best of Journal of College Student Retention: Research, Theory & Practice (pp. 99–122). Baywood Publishing.
Hill, C. J., Bloom, H. S., Black, A. R., & Lipsey, M. W. (2008). Empirical benchmarks for interpreting effect sizes in research. Child Development Perspectives, 2(3), 172–177. https://doi.org/10.1111/j.1750-8606.2008.00061.x
Jiang, S., Simpkins, S. D., & Eccles, J. S. (2020). Individuals’ math and science motivation and their subsequent STEM choices and achievement in high school and college: A longitudinal study of gender and college generation status differences. Developmental Psychology, 56(11), 2137–2151. https://doi.org/10.1037/dev0001110
Landivar, L. C. (2013). Disparities in STEM employment by sex, race, and Hispanic origin: American Community Survey Reports. U.S. Census Bureau. https://www2.census.gov/library/publications/2013/acs/acs-24.pdf
Liu, S.-N.C., Brown, S. E. V., & Sabat, I. E. (2019). Patching the “leaky pipeline”: Interventions for women of color faculty in STEM academia. Archives of Scientific Psychology, 7(1), 32–39. https://doi.org/10.1037/arc0000062
Long, L. L., & Mejia, J. A. (2016). Conversations about diversity: Institutional barriers for underrepresented engineering students. Journal of Engineering Education, 105(2), 211–218. https://doi.org/10.1002/jee.20114
Marsh, H. W., Van Zanden, B., Parker, P. D., Guo, J., Conigrave, J., & Seaton, M. (2019). Young women face disadvantage to enrollment in university STEM coursework regardless of prior achievement and attitudes. American Educational Research Journal, 56(5), 1629–1680. https://doi.org/10.3102/0002831218824111
Metcalf, H. (2010). Stuck in the pipeline: A critical review of STEM workforce literature. InterActions: UCLA Journal of Education and Information Studies, 6(2), 1–21. https://escholarship.org/uc/item/6zf09176
Morganson, V. J., Major, D. A., Streets, V. N., Litano, M. L., & Myers, D. P. (2015). Using embeddedness theory to understand and promote persistence in STEM majors. Career Development Quarterly, 63(4), 348–362. https://doi.org/10.1002/cdq.12033
Muscara, M., Pace, U., Passanisi, A., D’Urso, G., & Zappulla, C. (2018). The transition from middle school to high school: The mediating role of perceived peer support in the relationship between family functioning and school satisfaction. Journal of Child and Family Studies, 27, 2690–2698. https://doi.org/10.1007/s10826-018-1098-0
Nasir, N. S., & Vakil, S. (2017). STEM-focused academies in urban schools: Tensions and possibilities. Journal of the Learning Sciences, 26(3), 376–406. https://doi.org/10.1080/10508406.2017.1314215
National Assessment of Education Progress. (2015). Student experiences. The Nation’s Report Card. https://www.nationsreportcard.gov/science_2015/#context?grade=4https://www.nationsreportcard.gov/science/studentexperiences/?grade=4
National Center for Education Statistics. (2017). Number and percentage distribution of STEM degrees. https://nces.ed.gov/programs/digest/d17/tables/dt17_318.45.asp
National Science Board. (2014). Science and engineering indicators 2014. National Science Foundation. https://www.nsf.gov/statistics/seind14/
National Science Foundation. (2014). STEM education data and trends 2014: Has employment of women and minorities in S&E jobs increased? https://nsf.gov/nsb/sei/edTool/data/workforce-07.html
National Science Foundation. (2015). Women, minorities, and persons with disabilities in science and engineering: 2015 (Special Report NSF 15-311). National Center for Science and Engineering Statistics. http://www.nsf.gov/statistics/wmpd/
Nikischer, A. B., Weis, L., & Dominguez, R. (2016). Differential access to high school counseling, postsecondary destinations, and STEM careers. Teachers College Record, 118(11), 1–36. https://eric.ed.gov/?id=EJ1114920
Olszewski-Kubilius, P., Worrell, F. C., & Subotnik, R. F. (2018). The role of the family in talent development. In S. I. Pfeiffer, E. Shaunessy-Dedrick, & M. Foler-Nicpon (Eds.), APA handbooks in psychology: Handbook of giftedness and talent (pp. 465–477). American Psychological Association. https://doi.org/10.1037/0000038-030
Perera, H. N., & John, J. E. (2020). Teachers’ self-efficacy beliefs for teaching math: Relations with teacher and student outcomes. Contemporary Educational Psychology, 61, 1–13. https://doi.org/10.1016/j.cedpsych.2020.101842
Pitzer, J., & Skinner, E. (2017). Predictors of changes in students’ motivational resilience over the school year: The roles of teacher support, self-appraisals, and emotional reactivity. International Journal of Behavioral Development, 41(1), 15–29. https://doi.org/10.1177/0165025416642051
Ponterotto, J. G. (2005). Qualitative research in counseling psychology: A primer on research paradigms and philosophy of science. Journal of Counseling Psychology, 52(2), 126–136. https://doi.org/10.1037/0022-0167.52.2.126
President’s Council of Advisors on Science and Technology. (2012). Engage to excel: Producing one million additional college graduates with degrees in science, technology, engineering, and mathematics. Executive Office of the President of the United States. https://files.eric.ed.gov/fulltext/ED541511.pdf
Robinson, K. A., Lee, Y., Bovee, E. A., Perez, T., Walton, S. P., Briedis, D., & Linnenbrink-Garcia, L. (2019). Motivation in transition: Development and roles of expectancy, task values, and costs in early college engineering. Journal of Educational Psychology, 111(6), 1081–1102. https://doi.org/10.1037/edu0000331
Robnett, R. D., & Leaper, C. (2013). Friendship groups, personal motivation, and gender in relation to high school students’ STEM career interest. Journal of Research on Adolescence, 23(4), 652–664. https://doi.org/10.1111/jora.12013
Roksa, J., & Kinsley, P. (2019). The role of family support in facilitating academic success of low-income students. Research in Higher Education, 60, 415–436. https://doi.org/10.1007/s11162-018-9517-z
Rubel, L. H., & Chu, H. (2012). Reinscribing urban: Teaching high school mathematics in low income, urban communities of color. Journal of Mathematics Teacher Education, 15(1), 39–52. https://doi.org/10.1007/s10857-011-9200-1
Sakamoto, A., Takei, I., & Woo, H. (2012). The myth of the model minority myth. Sociological Spectrum, 32(4), 309–321. https://doi.org/10.1080/02732173.2012.664042
Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., Burroughs, H., & Jinks, C. (2018). Saturation in qualitative research: Exploring its conceptualization and operationalization. Quality and Quantity, 52(4), 1893–1907. https://doi.org/10.1007/s11135-017-0574-8
Saw, G., & Chang, C.-N. (2018). Cross-lagged models of mathematics achievement and motivational factors among Hispanic and non-Hispanic high school students. Hispanic Journal of Behavioral Sciences, 40(2), 240–256. https://doi.org/10.1177/0739986318766511
Smit, R., Robin, N., De Toffol, C., & Atanasova, S. (2021). Industry-school projects as an aim to foster secondary school students’ interest in technology and engineering careers. International Journal of Technology & Design Education, 31(1), 61–79. https://doi.org/10.1007/s10798-019-09538-0
Stipanovic, N., & Woo, H. (2016). Understanding African American students’ experiences in STEM education: An ecological systems approach. Career Development Quarterly, 65(3), 192–206. https://doi.org/10.1002/cdq.12092
Strayhorn, T. L., Long, L. L., III, Kitchen, J. A., Williams, M. S., & Stentz, M. (2013). Academic and social barriers to Black and Latino male collegians’ success in engineering and related STEM fields [Conference session]. American Society for Engineering Education Annual Conference and Exposition, Atlanta, GA, USA https://commons.erau.edu/publication/295
Sue, D. W., Capodilupo, C. M., Torino, G. C., Bucceri, J. M., Holder, A. M. B., Nadal, K. L., & Esquilin, M. (2007). Racial microaggressions in everyday life. Implications for clinical practice. American Psychologist, 62(4), 271–286. https://doi.org/10.1037/0003-066X.62.4.271
Tyson, W., Lee, R., Borman, K. M., & Hanson, M. A. (2007). Science, technology, engineering, and mathematics (STEM) pathways: High school science and math coursework and postsecondary degree attainment. Journal of Education for Students Placed at Risk, 12(3), 243–270. https://doi.org/10.1080/10824660601601266
Wang, X. (2013). Modeling entrance into STEM fields of study among students beginning at community college and four year institutions. Research in Higher Education, 54, 664–692. https://doi.org/10.1007/s11162-013-9291-x
Weiner, L. (2000). Research in the 90’s: Implications for urban teacher preparation. Review of Educational Research, 70(3), 369–406. https://doi.org/10.3102/00346543070003369
Wills, B., & Morse, J. M. (2001). Cross-cultural grounded theory studies and the concept of culture (abstract). In Second International Advances in Qualitative Methods Conference (p. 88). International Institute for Qualitative Methodology.
Witteveen, D., & Attewell, P. (2020). The STEM grading penalty: An alternative to the “leaky pipeline” hypothesis. Science Education, 104(4), 714–735. https://doi.org/10.1002/sce.21580
Young, J., & Young, J. (2018). The structural relationship between out-of-school time enrichment and Black student participation in advanced science. Journal for the Education of the Gifted, 41(1), 43–59. https://doi.org/10.11770/0162353217745381
Zilberman, A., & Ice, L. (2021). Why computer occupations are behind strong STEM employment growth in the 2019-29 decade. U.S. Bureau of Labor Statistics. https://www.bls.gov/opub/btn/volume-10/why-computer-occupations-are-behind-strong-stem-employment-growth.htm
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
There is no conflict of interest associated with this manuscript.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix 1
See Table 1.
Appendix 2
Semi-Structured Interview Questionnaire
General Questions
-
1.
What do you think about school?
-
a.
Examples
-
b.
Positives/negatives
-
a.
-
2.
What kinds of things do you like to do outside of school? (structured/unstructured)
-
a.
What do you like about [activity name]?
-
b.
Who do you do those activities with?
-
a.
-
3.
How well do you sleep at night?
-
a.
If not well: What makes it hard to sleep at night?
-
b.
Do you ever have your phone or computer with you?
-
a.
-
4.
What helps you succeed or do well in academics?
-
a.
What makes you do well compared to others? (internal/external supports)
-
b.
Probe influences
-
a.
-
5.
Types of relationships
-
a.
Peers
-
b.
Adults
-
a.
-
6.
Types of actions
-
7.
What are some ways you manage stress?
-
a.
Activities?
-
b.
Internal strategies?
-
c.
Interpersonal connections?
-
a.
-
8.
What jobs/careers do you hope to have when you get older?
-
a.
What jobs/careers do you expect to have when you get older?
-
b.
If there is a difference: What might the reason for you to have the job you expect versus the job you hope?
-
a.
-
9.
Could you describe the process you would go through to become a ________?
-
a.
What are the steps you would need to take to become a ____________?
-
a.
-
10.
What do your parents/family members think are good jobs/careers for you?
-
a.
Are there any specific jobs your parents/family members would definitely not want you to have and why not?
-
b.
What would your family/parents say if you decided to get a job in science, technology, engineering, or math?
-
a.
STEM Pathways (opportunities, mentors, career knowledge, do you know what you need to get to your end goal?)
-
1.
What comes to mind when you think about jobs in science, technology, engineering and math?
-
a.
What do you know about jobs in these areas?
-
b.
How did you learn about them?
-
c.
If non-responsive: Prompt with examples (friends, family, role models, teachers, etc.)
-
d.
What would you like to know about these kinds of jobs that you don’t know right now?
-
a.
-
2.
Tell me about any previous experiences you had where you were interested in STEM.
-
a.
Field trips? School events? Witnessing parents or loved ones/inspirational people do well?
-
a.
STEM Preparation/Self-Efficacy in Math and Science
-
1.
From when you were younger to now, how have you felt about math?
-
a.
Based on that, do you think your ability to do well and general preparedness to do well in math changed over time? Tell me more.
-
a.
-
2.
From when you were younger to now, how have you felt about science?
-
3.
How prepared do you feel in your math and science classes? (Or what does being prepared for math and science classes mean to you?)
-
a.
What do you do to prepare for math and science?
-
b.
What do others do to help you prepare for math and science?
-
c.
How comfortable do you feel about taking more advanced math and science classes?
-
a.
STEM Persistence (Psychological, Behavioral, Cognitive)
-
1.
When math and sciences classes get hard, what do you do?
-
a.
Help-seeking behavior
-
b.
Strategies
-
c.
Self-efficacy
-
d.
Different relationships (peers, teachers, parents, others)
-
a.
-
2.
In school and outside of school
-
a.
Environmental contexts—competition? Pressure to do well?
-
b.
How do you motivate yourself when you feel that you are stuck in a challenge or obstacle related to school?
-
a.
-
3.
What do you do when your math and science classes go well?
-
a.
How they feel
-
b.
Sense of self/confidence
-
c.
What were some of the things you did that helped you do well?
-
d.
How’d you keep going at it?
-
a.
-
4.
As you get older, what are some challenges you think you will face related to STEM?
-
a.
Probe: high school, college, careers
So now we are going to switch topics and talk a little bit about your identity. There are no right or wrong answers to these questions.
-
a.
-
5.
What ethnicity and gender do you identify with?
-
6.
How do you think your identity influences, if at all, your success in going into a STEM career?
Now, I’m wondering if we could talk a little bit about some barriers and challenges you might face that have to do with your identity.
-
7.
Sometimes individuals from underrepresented groups in STEM, like women or people of color, experience challenges related to their identity. Have you ever experienced a time when other individuals judged you based on your race or a gender stereotype?
-
a.
Stereotype threat? (think, experience, cope)
-
a.
-
8.
Has this ever happened to you in an academic setting or in STEM classes?
-
9.
Has this ever happened to you outside of class or school?
-
a.
What was that experience like for you?
-
b.
How do you cope with experiences like this?
-
a.
-
10.
Need to perform better than others?
-
11.
Do you feel like you need to prove yourself?
-
12.
Is there anything that we have not asked you that you think we should know about?
Appendix 3
Demographic Questionnaire
Demographic Questions
-
1.
How old are you?
-
2.
What is the name of your school?
-
3.
What grade are you currently in?
-
4.
What is your gender identity?
-
5.
What is your racial identity?
-
6.
What is your ethnic identity?
-
7.
Do you have any siblings?
-
a.
If yes: How many siblings do you have, and what are their ages and gender?
-
a.
-
8.
Who are your primary caretakers (the adults at home who take care of you)?
-
9.
If any, what jobs do your primary caretakers or parents hold?
-
10.
Who lives at home with you?
-
11.
Who helps you at home with your homework?
-
12.
What language(s) do you speak at home?
-
13.
What are some of the jobs and careers you’ve learned about at home?
-
14.
What is your favorite class in school?
-
15.
How long does it take you to get to school?
-
16.
What clubs/activities do you do in school?
-
17.
What activities/clubs do you do outside of school?
Rights and permissions
About this article
Cite this article
Park-Taylor, J., Wing, H.M., Aladin, M. et al. STEM Pathways for Black and Latinx Middle and High School Students. Urban Rev 54, 595–623 (2022). https://doi.org/10.1007/s11256-021-00631-0
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11256-021-00631-0