Abstract
Research suggests poor outcomes among children raised in disadvantaged contexts are a consequence of cultural mismatch, that is, competing practices that create conditions too weak to support positive outcomes. While useful, research is limited in its primary focus on individual social spheres and, as a result, does not yet fully account for dynamics across spheres. It also fails to explain the puzzling case of why some children from disadvantaged contexts succeed. To address this, we propose a cultural alignment framework that considers the interaction between organizational routines, cultural practices, and the habits children carry across spheres. Using the case of technological competence, we find that children’s habits can exert force and shift cultural practice to produce alignment in unexpected ways, such as opening additional learning experiences at school—but only if children fit within organizational routines, making the organization more flexible to their individual action. More broadly, the cultural alignment framework can be used to understand dynamics across social spheres, the conditions under which alignment can occur, and how these dynamics shape learning in such settings as higher education and employment.
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Notes
In part of the quantitative portion of the study, the first author surveyed a stratified random sample of 897 students from Title I and non-Title I schools and scale ratings were normally distributed. This suggests the students selected for this ethnographic study from that survey who are higher and lower on the scale are not outliers and can offer an informative contrast.
The data were collected by the first author, but for consistency we use the term “we” hereafter.
All names are pseudonyms
Family structure did not appear to make a difference in whether or how children learned technology at home. For instance, Sumalee was in a large household with many adults around. But Anandi had a similar family structure and that did not increase attention or interactions about technology between family members.
After an hour of watching Anandi struggle, the first author helped her with these activities.
“xD” is a symbol for sideways squinting eyes and a large grin and “o.o” is a symbol for big eyes and a small nose.
Although the month we were present was a busy testing period, the computer teacher reported even outside of this month his instructional time was greatly reduced by testing throughout the year.
The first author observed similar differences within classrooms while implementing the broader survey. At first we thought this was measurement error, but we realized students were simply reporting their experience: Some receive more learning experiences than others in the same classes. This finding across data types suggests teachers can be essentially different teachers for different students, even in socio-economically homogeneous, low-income classrooms.
A related finding was seen in another low-SES school the first author visited when administering surveys. In one classroom, the teacher only allowed students who promptly completed their survey to use classroom computers. In this practice, tech use is called a “treat,” and thus tech-learning opportunities are an “earned” additional resource or add-on to academics.
Gender plays a role in the cultural alignment process, but not a definitive one, as it may skew teachers’ perceptions of who is a “good student” regardless of the tech habits children have. On the one hand, teachers viewed Marcus as well behaved and there were girls observed in class who disrupted the teacher the way Rafael sometimes did. On the other hand, based on observations, gender seemed to play a role given that boys were more typically seen as disruptive, so were more likely to be seen by teachers as “bad students” and be allowed to slip away and not develop their technological competence at school. Moreover, an interesting gender difference was noted among boys and girls in the surveys, whereby the boys had a higher and narrower range in terms of rating their technology learning habits, that is, it was more unusual for them to develop very few technology learning habits. Exploring reasons for gender differences in tech habits is beyond the scope of this study, but it strengthens our claim about the critical role of teachers’ perceptions of students as the key that unlocks technology opportunities in school.
References
Alexander, Karl L., Doris Entwisle, and Linda Olson. 2014. The long shadow: Family background, disadvantaged urban youth, and the transition to adulthood. New York: Russell Sage Foundation.
Attewell, Paul. 2001. Comment: The first and second digital divides. Sociology of Education 74 (3): 252–259.
Attewell, Paul, and Juan Battle. 1999. Home computers and school performance. The Information Society 15 (1): 1–10.
Barron, Brigid. 2006. Interest and self-sustained learning as catalysts of development: A learning ecology perspective. Human Development 49: 193–224.
Bennett, Susan, Karl Maton, and Lisa Kervin. 2009. The 'digital natives' debate: A critical review of the evidence. British Journal of Educational Technology 39 (5): 775–786.
Bourdieu, Pierre, and Jean-Claude Passeron. 1990/1977. Reproduction in education, society, and culture. London: Sage Publications. Original edition, 1977.
Brice Heath, Shirley. 1982. What no bedtime story means: Narrative skills at home and school. Language in Society 11 (1): 49–76.
Bronfenbrenner, Urie. 1979. The ecology of human development: Experiments by nature and design. Cambridge: Harvard University Press.
Calarco, Jessica McCrory. 2011. I need help!' Social class and children's help-seeking in elementary school. American Sociological Review 76 (6): 862–882.
Chicago Public Schools. 2016. New CPS computer science graduation requirement to prepare students for jobs of the future. Chicago: CPS Office of Communications.
Coca, Vanessa, and Elaine M. Allensworth. 2007. Trends in access to computing technology and its use in Chicago Public Schools 2001–2005. Chicago: Consortium on Chicago School Research.
Coleman, James S. 1961. The adolescent society: The social life of the teenager and its impact on education. Oxford: Free Press of Glencoe.
Cuban, Larry. 2003. Oversold and underused: Computers in the classroom. Cambridge: Harvard University Press.
Dewey, John. 1922. Human nature and conduct: An introduction to social psychology. New York: Henry Holt and Company.
Emirbayer, Mustafa. 1997. Manifesto for a relational sociology. American Journal of Sociology 103 (2): 281–317.
Epstein, Joyce L. 1987. Toward a theory of family-school connections: Teacher practices and parent involvement. In Social intervention: Potential and constraints, ed. K. Hurrelman, F. Kaufmann, and F. Losel, 121–136. New York: DeGruyter.
Erlich, Stacy B., Sue E. Sporte, and Penny Bender Sebring. 2013. The use of technology in Chicago Public Schools. Chicago: Consortium on Chicago School Research.
Fairlie, Robert W., and Peter Riley Bahr. 2018. The effects of computers and acquired skills on earnings, employment and college enrollment: Evidence from a field experiment and California UI earnings records. Economics of Education Review 63: 51–63.
Feldman, Martha S., and Brian T. Pentland. 2003. Reconceptualizing organizational routines as a source of flexibility and change. Administrative Science Quarterly 48 (1): 94–118.
Fine, Gary Alan. 2004. Adolescence as cultural toolkit: High school debate and the repertoires of childhood and adulthood. The Sociological Quarterly 45 (1): 1–20.
Friedland, Roger, and Robert R. Alford. 1991. Bringing society back in: Symbols, practices, and institutional contradictions. In The new institutionalism in organizational analysis, ed. Walter Powell and Paul J. DiMaggio. Chicago: University of Chicago Press.
Giacquinta, Joseph B., Jo Anne Bauer, and Jane E. Levin. 1993. Beyond technology's promise: An examination of children's educational computing at home. Cambridge: Cambridge University Press.
Giddens, Anthony. 1993. New rules of sociological method: A positive critique of interpretative sociologies. Stanford: Stanford University Press.
Goldin, Claudia, and Lawrence F. Katz. 2008. The race between technology and education. Cambridge: Harvard University Press.
Gorman-Smith, Deborah, David B. Henry, and Patrick H. Tolan. 2004. Exposure to community violence and violence perpetration: The protective effects of family functioning. Journal of Clinical Child and Adolescent Psychology 33 (3): 439–449.
Gray, Lucinda, Nina Thomas, Laurie Lewis, and Peter Tice. 2010. Teachers’ use of educational technology in U.S. public schools: 2009. Washington, D.C.: National Center for Educational Statistics, Institute for Educational Sciences, U.S. Department of Education.
Greeno, James. 2007. Toward the development of intellective character. In Affirmative development: Cultivating academic ability, ed. Edmund W. Gordon and Beatrice L. Bridglall, 17–48. Lanham: Rowman & Littlefield.
Hanushek, Eric A., John F. Kain, Jacob M. Markman, and Steven G. Rivkin. 2001. Does peer ability affect student achievement? Journal of Applied Econometrics 18: 527–544.
Harding, David J. 2007. Cultural context, sexual behavior, and romantic relationships in disadvantaged neighborhoods. American Sociological Review 72: 341–364.
Harding, David J. 2011. Rethinking the cultural context of schooling decisions in disadvantaged neighborhoods: From deviant subculture to cultural heterogeneity. Sociology of Education 84 (4): 322–339.
Harding, David J., Michele Lamont, and Mario L. Small. 2010. Reconsidering culture and poverty. The Annals of the American Academy of Political and Social Science 629: 6–27.
Hodgson, Geoffrey M. 2009. The nature and replication of routines. In Organizational routines: Advancing empirical research, ed. Markus C. Becker and Nathalie Lazaric, 26–44. Cheltenham, UK: Edward Elgar Publishing.
Horvat, Erin McNamara, and James Earl Davis. 2011. Schools as sites for transformation: Exploring the contribution of habitus. Youth and Society 43(1):142–70.
Hoxby, Caroline. 2000. Peer effects in the classroom: Learning from gender and race variation, NBER working paper no. 7867. Cambridge: National Bureau of Economic Research.
James, William. 1890. Habit. New York: Henry Holt and Company.
Judge, Sharon, Kathleen Puckett, and Sherry Mee Bell. 2006. Closing the digital divide: Update from the Early Childhood Longitudinal Study. The Journal of Educational Research: 52–60.
Konstantopoulos, Spyros, and Geoffrey D. Borman. 2011. Family background and school effects on student achievement: A multilevel re-analysis of the Coleman data. Teachers College Record 113: 97–132.
Lareau, Annette. 2011. Unequal childhoods: Class, race, and family life. second ed. Los Angeles: University of California Press.
Maltese, Adam V., and Tai, Robert H. 2010. Eyeballs in the fridge: Sources of early interest in science. International Journal of Science Education, 32(5), 669–685.
Maltese, Adam V., and Tai, Robert H. 2011. Pipeline persistence: examining the association of educational experiences with earned degrees in STEM among U.S. students. Science Education, 95(5), 877–907.
Massey, Douglas S. 1990. American apartheid: Segregation and the making of the underclass. American Journal of Sociology 98 (2): 329–357.
Massey, Douglas S., and Stefanie Brodmann. 2014. Spheres of influence: The social ecology of racial and class inequality. New York: Russell Sage Foundation.
Mead, George Herbert. 1910. What social objects must psychology presuppose? Journal of Psychology 7: 174–180.
Mollborn, Stefanie, Benjamin W. Domingue, and Jason D. Boardman. 2014. Norms as group-level constructs: Investigating school-level teen pregnancy norms and behaviors. Social Forces 93 (1): 241–267.
Oakes, Jeannie. 1990. Opportunities, achievement, and choice: Women and minority students in science and mathematics. Review of Research in Education 16: 153–222.
Paino, Maria, and Linda A. Renzulli. 2013. Digital dimension of cultural capital: The (in)visible advantages for students who exhibit computer skills. Sociology of Education 86(2):124–38.
Puckett, Cassidy. 2013. Technology education. In Sociology of education: An a-to-z guide, ed. James Ainsworth. Thousand Oaks: Sage Publications.
Puckett, Cassidy. 2015. Technological change, digital adaptability, and social inequality. In Doctor of Philosophy Doctoral Dissertation, Northwestern University.
Quillian, Lincoln. 2012. Segregation and poverty concentration: The role of three segregations. American Sociological Review 77: 354–379.
Reay, Diane, Miriam David, and Stephen Ball. 2001. Making a difference?: Institutional habituses and higher education choice. Sociological Research Online 5 (4): 126–142.
Resnick, Mitchel. 2007. Sowing the seeds for a more creative society. Learning & Leading with Technology 35 (4): 18–22.
Rosenbaum, James. 2001. Beyond college for all. New York: Russell Sage Foundation.
Small, Mario L., and Jessica Feldman. 2012. Ethnographic evidence, heterogeneity, and neighbourhood effects after moving to opportunity. In Neighbourhood effects research: New perspectives, ed. Maarten van Ham, David Manley, Nick Bailey, Ludi Simpson, and Duncan Maclennan, 57–77. Dordrecht, Heidelberg, London, and New York: Springer.
Smith, Dorothy E. 2005. Institutional ethnography: A sociology for people. Lanham: Altamira Press.
Streib, Jessi. 2011. Class reproduction by four year olds. Qualitative Sociology 34 (2): 337–352.
Sweet, Stephen, and Phyllis Moen. 2012. Dual earners preparing for job loss: Agency, linked lives, and resilience. Work and Occupations 39(1):35–70.
Swidler, Ann. 1986. Culture in action: Symbols and strategies. American Sociological Review 51 (2): 273–286.
Thomas, Liz. 2002. Student retention in higher education: The role of institutional habitus. Journal of Education Policy 17 (4): 423–442.
Timmermans, Stefan, and Iddo Tavory. 2012. Theory construction in qualitative research: From grounded theory to abductive analysis. Sociological Theory 30: 167–186.
Turner, Scott F., and Eugenia Cacciatori. 2016. Mutiplicity of habit: Implications for routines research. In Organizational routines: How they are created, maintained, and changed, ed. Jennifer Howard-Grenville, Claus Rerup, Ann Langly, and Haridimos Tsoukas, 71–95. Oxford: Oxford University Press.
U.S Department of Education. 2017. Reimagining the role of technology in education: National education technology plan update. Washington, DC: Office of Educational Technology.
Vygotsky, Lev. 1978. Mind in society: The development of higher psychological processes. Cambridge: Harvard University Press.
Wacquant, Loic. 2002. Scrutinizing the street: Poverty, morality, and the pitfalls of urban ethnography. American Journal of Sociology 107 (1468-1532).
Warschauer, Mark. 2012. The digital divide and social inclusion. Americas Quarterly 6 (2): 131–135.
Watkins, S. Craig, Andres Lombana-Bermudez, Alexander Cho, Vivian Shaw, Jacqueline Ryan Vickery, and Lauren Weinzimmer. 2018. The digital edge: How black and Latino youth navigate digital inequality. New York: New York University Press.
Acknowledgements
The authors wish to thank Timothy Dowd, Jeremy Freese, Charles Camic, David Harding, James Paul Gee, Brigid Barron, Leslie McCall, Jeannette Colyvas, Brian Powell, Wendy Espeland, Wendy Griswold, and the Culture Workshop at Northwestern for invaluable support and feedback.
Funding
The research reported here was supported by the Institute of Education Sciences; U.S. Department of Education, through Grant R305B080027 to Northwestern University; as well as a National Science Foundation Dissertation Improvement Grant #1303682; a Northwestern University Sociology Department MacArthur Research Grant; a Graduate Research Grant from Northwestern University; a Technology Grant from the Information Technology Group at Northwestern University; an American Council of Learned Societies/Andrew W. Mellon Dissertation Completion Fellowship; and support from the John D. and Catherine T. MacArthur Foundation through the Emerging Scholars’ Group at Arizona State University. The opinions expressed are those of the authors and do not represent views of the Institute of Education Sciences, the U.S. Department of Education, or other supporting parties.
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Puckett, C., Nelson, J.L. The Geek Instinct: Theorizing Cultural Alignment in Disadvantaged Contexts. Qual Sociol 42, 25–48 (2019). https://doi.org/10.1007/s11133-019-9408-4
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DOI: https://doi.org/10.1007/s11133-019-9408-4