Abstract
African Americans, especially African American women, remain one of the most underrepresented groups in technology-based degrees and careers. However, little is known about whether gender differences permeate African American adolescents’ engagement in technology in earlier development, such as in middle and high school (ages 12–18). Drawing on an ecological and intersectional framework, we examined if African American male and female adolescents differed in technological engagement and what contextual factors affected their engagement. We hypothesized that parental encouragement would be associated with greater technological confidence in adolescents, which would be linked to more experiences with and interests in technology. Further, we investigated if these associations would vary by adolescents’ and parents’ gender. Survey data from 1041 African American parent-adolescent dyads highlighted that adolescents had less experience and interest with technical activities than with creative activities, especially among female adolescents. More parents encouraged adolescent sons but limited daughters to use technology, yet female adolescents reported greater technological confidence. Moderated mediation analyses revealed that adolescents’ technological confidence mediated the positive association between parental encouragement and adolescents’ technological engagement across all parent-adolescent dyads, but with some nuances. Our findings suggest that prospective gender studies and educational programs should consider the influences of parenting and gender on promoting African American adolescents’ technological involvement and confidence.
Similar content being viewed by others
References
Akkuş Çakır, N., Gass, A., Foster, A., & Lee, F. J. (2017). Development of a game-design workshop to promote young girls' interest towards computing through identity exploration. Computers & Education, 108, 115–130. https://doi.org/10.1016/j.compedu.2017.02.002.
Alliman-Brissett, A., & Turner, S. L. (2010). Racism, parent support, and math-based career interests, efficacy, and outcome expectations among African American adolescents. Journal of Black Psychology, 36(2), 197–225. https://doi.org/10.1177/0095798409351830.
Benyo, J., & White, J. (2009). New image for computing: Report on market research. Boston, MA: WGBH Educational Foundation and the Association for Computing Machinery.
Bronfenbrenner, U., & Morris, P. A. (1998). The ecology of developmental processes. In W. Damon & R. M. Lerner (Eds.), Handbook of child psychology: Theoretical models of human development (Vol. 1, 5th ed., pp. 993–1028). Hoboken, NJ: John Wiley & Sons Inc.
Buck, G., Cook, K., Quigley, C., Eastwood, J., & Lucas, Y. (2009). Profiles of urban, low SES, African American girls’ attitudes toward science: A sequential explanatory mixed methods study. Journal of Mixed Methods Research, 3(4), 386–410. https://doi.org/10.1177/1558689809341797.
Buckley, T. R., & Carter, R. T. (2005). Black adolescent girls: Do gender role and racial identity: Impact their self-esteem? Sex Roles: A Journal of Research, 53(9–10), 647–661. https://doi.org/10.1007/s11199-005-7731-6.
Buschor, C. B., Berweger, S., Frei, A. K., & Kappler, C. (2014). Majoring in STEM—What accounts for women's career decision making? A mixed methods study. The Journal of Educational Research, 107(3), 167–176. https://doi.org/10.1080/00220671.2013.788989.
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.
College Board. (2017). AP program participation and performance data (National summary 2017). Retrieved from https://research.collegeboard.org/programs/ap/data/archived/ap-2017
Collins, P. H., & Bilge, S. (2016). Intersectionality. Malden, MA: Polity Press.
Crenshaw, K. W. (1991). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford Law Review, 46, 1241–1299. https://doi.org/10.2307/1229039.
Diekman, A. B., Brown, E. R., Johnston, A. M., & Clark, E. K. (2010). Seeking congruity between goals and roles: A new look at why women opt out of science, technology, engineering, and mathematics careers. Psychological Science, 21(8), 1051–1057. https://doi.org/10.1177/0956797610377342.
Eagly, A. H., & Wood, W. (1999). The origins of sex differences in human behavior: Evolved dispositions versus social roles. American Psychologist, 54, 408–423. https://doi.org/10.1037/0003-066X.54.6.408.
Eagly, A. H., & Wood, W. (2013). The nature-nurture debates: 25 years of challenges in understanding the psychology of gender. Perspectives on Psychological Science, 8, 340–357. https://doi.org/10.1177/1745691613484767.
Eagly, A. H., Wood, W., & Diekman, A. B. (2000). Social role theory of sex differences and similarities: A current appraisal. In T. Eckes & H. M. Trautner (Eds.), The developmental social psychology of gender (pp. 123–174). Mahwah, NJ: Erlbaum.
English-Clarke, T. (2012). Things my family told me about math: African American youths' perception and use of racial and mathematical socialization messages (Order No. AAI3462195). Available from PsycINFO. (1011880073; 2012–99051-285).
Ferry, T. R., Fouad, N. A., & Smith, P. L. (2000). The role of family context in a social cognitive model for career-related choice behavior: A math and science perspective. Journal of Vocational Behavior, 57(3), 348–364. https://doi.org/10.1006/jvbe.1999.1743.
Fletcher, A. C., & Blair, B. L. (2014). Maternal authority regarding early adolescents' social technology use. Journal of Family Issues, 35(1), 54–74. https://doi.org/10.1177/0192513X12467753.
Gallup. (2015). Images of computer science: Perceptions among students, parents and educators in the U.S. Retrieved from https://services.google.com/fh/files/misc/images-of-computer-science-report.pdf.
Garriott, P. O., Flores, L. Y., Prabhakar, B., Mazzotta, E. C., Liskov, A. C., & Shapiro, J. E. (2014). Parental support and underrepresented students’ math/science interests: The mediating role of learning experiences. Journal of Career Assessment, 22(4), 627–641. https://doi.org/10.1177/1069072713514933.
Girl Scout Research Institute. (2012). Generation STEM: What girls say about science, technology, engineering, and math. Girl Scouts of USA. Retrieved from https://www.girlscouts.org/join/educators/generation_stem_full_report.pdf.
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). New York City, NY: The Guilford Press.
Huang, K., Cotten, S. R., & Rikard, R. V. (2017). Access is not enough: The impact of emotional costs and self-efficacy on the changes in African-American students’ ICT use patterns. Information, Communication & Society, 20(4), 637–650. https://doi.org/10.1080/1369118X.2016.1203456.
Ireland, D. T., Freeman, K. E., Winston-Proctor, C. E., DeLaine, K. D., McDonald Lowe, S., & Woodson, K. M. (2018). (Un) hidden figures: A synthesis of research examining the intersectional experiences of Black women and girls in STEM education. Review of Research in Education, 42(1), 226–254. https://doi.org/10.3102/0091732X18759072.
Kim, A. S., & Davis, K. (2017). Tweens’ perspectives on their parents’ media-related attitudes and rules: An exploratory study in the US. Journal of Children and Media, 11(3), 358–366. https://doi.org/10.1080/17482798.2017.1308399.
Lindley, L. D. (2005). Perceived barriers to career development in the context of social cognitive career theory. Journal of Career Assessment, 13(3), 271–287. https://doi.org/10.1177/1069072705274953.
MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence of the mediation, confounding and suppression effect. Prevention Science: The official journal of the Society for Prevention Research, 1(4), 173–181. https://doi.org/10.1023/a:1026595011371.
Madden, M., Lenhart, A., Duggan, M., Cortesi, S., & Gasser, U. (2013). Adolescents and technology 2013 (pp. 1–19). Washington, DC: Pew Internet & American Life Project.
Mandara, J., Murray, C. B., & Joyner, T. N. (2005). The impact of fathers' absence on African American adolescents' gender role development. Sex Roles: A Journal of Research, 53(3–4), 207–220. https://doi.org/10.1007/s11199-005-5679-1.
McAlear, F., Scott, A., Scott, K. & Weiss, S. (2018). Data brief: Women of color in computing. Retrieved from https://www.wocincomputing.org/wp-content/uploads/2018/08/WOCinComputingDataBrief.pdf.
McHale, S. M., Crouter, A. C., Kim, J., Burton, L. M., Davis, K. D., Dotterer, A. M., & Swanson, D. P. (2006). Mothers' and fathers' racial socialization in African American families: Implications for youth. Child Development, 77(5), 1387–1402. https://doi.org/10.1111/j.1467-8624.2006.00942.x.
National Science Foundation. (2017). Women, minorities, and persons with disabilities in science and engineering: 2017. Special Report NSF 17–310. Retrieved from https://www.nsf.gov/statistics/wmpd/.
Nielson. (2016). Young, connected, and Black: African-American millennials are driving social change and learning digital advancement. Retrieved from http://www.ethnifacts.com/Nielsen-African-American-Consumer-Report-Oct-2016.pdf.
O'Brien, L. T., Blodorn, A., Adams, G., Garcia, D. M., & Hammer, E. (2015). Ethnic variation in gender-STEM stereotypes and STEM participation: An intersectional approach. Cultural Diversity and Ethnic Minority Psychology, 21(2), 169–180. https://doi.org/10.1037/a0037944.
Ong, M., Wright, C., Espinosa, L. L., & Orfield, G. (2011). Inside the double bind: A synthesis of empirical research on undergraduate and graduate women of color in science, technology, engineering, and mathematics. Harvard Educational Review, 81(2), 172–208. https://doi.org/10.17763/haer.81.2.t022245n7x4752v2.
Paul, D. G. (2016). The millennial morphing of the digital divide and its implications for African American youngsters in a new literacies era. Journal of Negro Education, 85(4), 407–415. https://doi.org/10.7709/jnegroeducation.85.4.0407.
Pew Research Center. (2018). Women and men in STEM often at odds over workplace equity. Retrieved from http://www.pewsocialtrends.org/2018/01/09/women-and-men-in-stem-often-at-odds-over-workplace-equity/.
Quimby, J. L., Wolfson, J. L., & Seyala, N. D. (2007). Social cognitive predictors of African American adolescents' career interests. Journal of Career Development, 33(4), 376–394. https://doi.org/10.1177/0894845307300414.
Rice, L., Barth, J. M., Guadagno, R. E., Smith, G. P. A., & McCallum, D. M. (2013). The role of social support in students’ perceived abilities and attitudes toward math and science. Journal of Youth and Adolescence, 42(7), 1028–1040. https://doi.org/10.1007/s10964-012-9801-8.
Rideout, V., Lauricella, A., & Wartella, E. (2011). Children, media and race: Media use among White, Black, Hispanic, and Asian American children. Retrieved from http://web5.soc.northwestern.edu/cmhd/wp-content/uploads/2011/06/SOCconfReportSingleFinal-1.pdf
Rideout, V. J., Scott, K. A., & Clark, K. A. (2016). The digital lives of African American tweens, teens, and parents: Innovating and learning with technology. Retrieved from https://cgest.asu.edu/sites/default/files/digital_lives_report_0.pdf
Robinson, A., Pérez-Quiñones, M. A., & Scales, G. (2016). African-American middle school girls: Influences on attitudes toward computer science. Computing in Science & Engineering, 18(3), 14–23. https://doi.org/10.1109/MCSE.2016.43.
Rottinghaus, P. J., Larson, L. M., & Borgen, F. H. (2003). The relation of self-efficacy and interests: A meta-analysis of 60 samples. Journal of Vocational Behavior, 62(2), 221–236. https://doi.org/10.1016/S0001-8791(02)00039-8.
Schmidt, F. L. (2014). A general theoretical integrative model of individual differences in interests, abilities, personality traits, and academic and occupational achievement: A commentary on four recent articles. Perspectives on Psychological Science, 9, 211–224. https://doi.org/10.1177/1745691613518074.
Scott, K. A., & Garcia, P. (2016). Techno-social change agents: Fostering activist dispositions among girls of color. Meridians, 15(1), 65–85.
Scott, K. A., & White, M. A. (2013). COMPUGIRLS’ standpoint: Culturally responsive computing and its effect on girls of color. Urban Education, 48(5), 657–681.
Shank, D. B., & Cotten, S. R. (2014). Does technology empower urban youth? The relationship of technology use to self-efficacy. Computers & Education, 70, 184–193. https://doi.org/10.1016/j.compedu.2013.08.018.
Skinner, O. D., Perkins, K., Wood, D., & Kurtz-Costes, B. (2016). Gender development in African American youth. Journal of Black Psychology, 42(5), 394–423. https://doi.org/10.1177/0095798415585217.
Smetana, J., & Chuang, S. (2001). Middle-class African American parents' conceptions of parenting in early adolescence. Journal of Research on Adolescence, 11(2), 177–198. https://doi.org/10.1111/1532-7795.00009.
Smetana, J. G., Abernethy, A., & Harris, A. (2000). Adolescent–parent interactions in middle-class African American families: Longitudinal change and contextual variations. Journal of Family Psychology, 14(3), 458–474. https://doi.org/10.1037/0893-3200.14.3.458.
Stipanovic, N., & Woo, H. (2017). Understanding African American students' experiences in STEM education: An ecological systems approach. The Career Development Quarterly, 65(3), 192–206. https://doi.org/10.1002/cdq.12092.
Stoet, G., & Geary, D. (2018). The gender-equality paradox in science, technology, engineering, and mathematics education. Psychological Science, 29(4), 581–593. https://doi.org/10.1177/0956797617741719.
Su, R., & Rounds, J. (2015). All STEM fields are not created equal: People and things interests explain gender disparities across STEM fields. Frontiers in Psychology, 6(189), 1–20. https://doi.org/10.3389/fpsyg.2015.00189.
Suizzo, M., Rackley, K. R., Robbins, P. A., Jackson, K. M., Rarick, J. R. D., & McClain, S. (2017). The unique effects of fathers’ warmth on adolescents’ positive beliefs and behaviors: Pathways to resilience in low-income families. Sex Roles, 77(1–2), 46–58. https://doi.org/10.1007/s11199-016-0696-9.
Tenenbaum, H. R., & Leaper, C. (2003). Parent-child conversations about science: The socialization of gender inequities? Developmental Psychology, 39(1), 34–47. https://doi.org/10.1037/0012-1649.39.1.34.
The White House on Women and Girls. (2016, December 16). Advancing equity for women and girls of color: 2016 updated report. Retrieved from https://www.whitehouse.gov/sites/whitehouse.gov/files/images/2016%20CWG%20WGOC%20REPORT%20.pdf
Townsend, T. G. (2008). Protecting our daughters: Intersection of race, class and gender in African american mothers' socialization of their daughters' heterosexuality. Sex Roles: A Journal of Research, 59(5–6), 429–442. https://doi.org/10.1007/s11199-008-9409-3.
Turner, S. L., Steward, J. C., & Lapan, R. T. (2004). Family factors associated with sixth-grade adolescents' math and science career interests. Career Development Quarterly, 53(1), 41–52. https://doi.org/10.1002/j.2161-0045.2004.tb00654.x.
Tynes, B. M., & Mitchell, K. J. (2014). Black youth beyond the digital divide: Age and gender differences in internet use, communication patterns, and victimization experiences. Journal of Black Psychology, 40(3), 291–307. https://doi.org/10.1177/0095798413487555.
Varner, F., & Mandara, J. (2013). Discrimination concerns and expectations as explanations for gendered socialization in African American families. Child Development, 84, 875–890. https://doi.org/10.1111/cdev.12021.
Yardi, S., & Bruckman, A. (2012, May). Income, race, and class: exploring socioeconomic differences in family technology use. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3041–3050). New York, NY: ACM. https://doi.org/10.1145/2207676.2208716.
Acknowledgements
This research was funded by the Bill & Melinda Gates Foundation (OPP1113020). We thank Victoria Rideout of VJR Consulting and Dr. Kevin Clark of George Mason University for their collaboration on the development, data collection, and initial analyses of this project. We are grateful for the expert advisory group: Dr. Jerlando F. L. Jackson at the University of Wisconsin-Madison; David J. Johns, executive director of the White House Initiative on Educational Excellence for African Americans; Dr. Vikki Katz of Rutgers University; Dr. Allison Scott, who was at that time at the National Institutes of Health and is currently with the Kapor Center for Social Impact; Aaron Smith of the Pew Research Center; and Dr. S. Craig Watkins of the University of Texas at Austin. We appreciate all the African American families that participated in this project and contributed to our knowledge of how they use and learn technology in informal learning environments.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 26 kb)
Rights and permissions
About this article
Cite this article
Tao, C., Scott, K.A. & McCarthy, K.S. Do African American Male and Female Adolescents Differ in Technological Engagement?: The Effects of Parental Encouragement and Adolescent Technological Confidence. Sex Roles 83, 536–551 (2020). https://doi.org/10.1007/s11199-020-01134-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11199-020-01134-0