Abstract
Adolescents are surrounded by people who have expectations about their college-going potential. Yet, few studies have examined the link between these multiple sources of college-going expectations and the actual status of students in postsecondary education years later. The study draws on data collected in the 2002–2006 Educational Longitudinal Study and employs an underutilized statistical technique (cross-classified multilevel modeling) to account for teacher reports on overlapping groups of students (typical of high school research). Results showed that positive expectations of students, parents, English, and mathematics teachers in the 10th grade each uniquely predicted postsecondary status 4 years later. As a group, the four sources of expectations explained greater variance in postsecondary education than student characteristics such as socioeconomic status and academic performance. This suggests positive expectations are additive and promotive for students regardless of their risk status. Teacher expectations were also found to be protective for low income students. Implications for future expectancy research and equity-focused interventions are discussed.
Similar content being viewed by others
Notes
In order to investigate if using a two-level CCREM was appropriate in modeling our data, we compared other similar, competing models taking into account possible school-level variability in our outcome measure. We ran unconditional models of A) students nested within two teachers nested within schools (using CCREM) and B) students nested within a single teacher nested within schools (not using CCREM but a standard three-level multilevel model). To guide model selection, we considered the variability at the school-level (using the school-level intraclass correlation or ICC), the model Akaike information criterion (AIC), and the Schwarz Bayesian information criterion (SBC; also known as BIC) as done by Meyers and Beretvas (2006). Smaller values of the AIC and SBC indicate better model fit.
Our unconditional, baseline CCREM model had an AIC of 10,782. Competing model A had a very similar AIC of 10,781 and model B had a much higher AIC of 10,892. Using SBC, the two-level CCREM (SBC = 10,774) fit better than the competing models (SBCA = 10,802; SBCB = 10,909). Meyers and Beretvas (2006) indicated that SBC may be more accurate in determining model fit for cross classified models compared to AIC.
The variability at the school level was statistically significant in model A (p = .04) and model B (p < .001) but the proportion of variance accounted for at the school-level was relatively small (ICCA = 0.03 and ICCB = 0.06). In addition, we conducted further analyses using the competing models but included student-level covariates. With the inclusion of student-level controls, school-level variance for both competing models became nonsignificant (both ps > 0.05). Based on the AIC, SBC, and as a result of school-level variability being relatively small (and later nonsignificant), we opted to present the results of the two-level CCREM.
References
Aud, S., Fox, M., & KewalRamani, A. (2010). Status and trends in the education of racial and ethnic groups (NCES 2010–015). Washington, DC: U.S. Government Printing Office.
Benner, A. D., & Mistry, R. S. (2007). Congruence of mother and teacher educational expectations and low-income youth’s academic competence. Journal of Educational Psychology, 99, 140–153.
Bozick, R., Alexander, K., Entwisle, D., Dauber, S., & Kerr, K. (2010). Framing the future: Revisiting the place of educational expectations in status attainment. Social Forces, 88, 2027–2052.
Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press.
Brophy, J., & Good, T. (1974). Teacher-student relationships: Causes and consequences. New York: Holt, Rineholt, & Winston.
Chen, W., & Gregory, A. (2009). Parental involvement as a protective factor during the transition to high school. Journal of Educational Research, 103, 53–62.
Datnow, A., Solorzano, D. G., Watford, T., & Park, V. (2010). Mapping the terrain: The state of knowledge regarding low-income youth access to postsecondary education. Journal of Education for Students Placed at Risk, 14, 1–8.
de Boer, H., Bosker, R. J., & van der Werf, M. P. C. (2010). Sustainability of teacher expectation bias effects on long-term student performance. Journal of Educational Psychology, 102, 168–179.
Dishion, T. J., Piehler, T. F., & Myers, M. W. (2008). Dynamics and ecology of adolescent peer influence. In M. J. Prinstein & K. A. Dodge (Eds.), Understanding peer influence in children and adolescents (pp. 45–71). New York: Guilford Press.
Dweck, C. S. (2000). Self-theories: Their role in motivation, personality, and development. Philadelphia: Psychology Press.
Elliott, W. (2008). Children’s college aspirations and expectations: The potential role of college development accounts (CDAs). Children and Youth Services Review, 31, 274–283.
Fan, X., & Chen, M. (2001). Parental involvement and students’ academic achievement: A meta-analysis. Educational Psychology Review, 13, 1–22.
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74, 59–109.
Glick, J. E., & White, M. J. (2004). Post-secondary school participation of immigrant and native youth: The role of familial resources and educational expectations. Social Science Research, 33, 272–299.
Greenwald, A. G., Poehlman, T. A., Uhlmann, E. L., & Banaji, M. R. (2009). Understanding and using the Implicit Association test: III. Meta-analysis of predictive validity. Journal of Personality and Social Psychology, 97, 17–41.
Hahs-Vaughn, D. (2005). A primer on using and understanding weights with national datasets. Journal of Experimental Education, 73, 221–248.
Hamrick, F. A., & Stage, F. K. (2004). College predisposition at high-minority enrollment, low income schools. The Review of Higher Education, 27, 151–168.
Hox, J. J. (2010). Multilevel analysis. Techniques and applications. 2nd edn. New York: Routledge.
Julian, T., & Kominiski, R. (2011). Education and synthetic work-life earnings estimates: American community survey reports. (ACS-14). Washington DC: U.S. Census Bureau Retrieved from http://www.census.gov/prod/2011pubs/acs-14.pdf.
Jussim, L., Eccles, J. S., & Madon, S. (1996). Social perception, social stereotypes, and teacher expectations: Accuracy and the quest for the powerful self-fulfilling prophecy. Advances in Experimental Social Psychology, 28, 281–388.
Jussim, L., Robustelli, S., & Cain, T. (2009). Teacher expectations and self-fulfilling prophecies. In A. Wigfield & K. Wentzel (Eds.), Handbook of motivation at school (pp. 349–380). Mahwah, NJ: Erlbaum.
Kim, Y., & Sherraden, M. (2011). Do parental assets matter for children’s educational attainment? Evidence from mediation tests. Children & Youth Services Review, 6, 969–980.
King, J. (1996). The Decision to go to college: Attitudes and experiences associated with college attendance among low-income students. Washington, DC: College Board.
Kuklinski, M., & Weinstein, R. S. (2001). Classroom and developmental differences in a path model of teacher expectancy effects. Child Development, 72, 1554–1578.
LaRusso, M. D., Jones, S. M., Brown, J. L., & Aber, J. L. (2010). School context and microcontexts: The complexities of studying school settings. In L. M. Dinella (Ed.), Conducting psychology research in school-based settings. Washington, DC: American Psychological Association.
Lomax, R. G., & Hahs-Vaughn, D. L. (2012). An introduction to statistical concepts (3rd ed.). New York, NY: Routledge.
Losel, F., & Farrington, D. P. (2012). Direct protective and buffering protective factors in the development of youth violence. American Journal of Preventive Medicine, 43, S8–S23.
McGowan, M. O., & Lindgren, J. (2006). Testing the model minority myth. Northwestern University Law Review, 100, 331–378.
McKown, C., & Weinstein, R. S. (2002). Modeling the role of child ethnicity and gender in children’s differential response to teacher expectations. Journal of Applied Social Psychology, 32, 159–184.
McKown, C., & Weinstein, R. S. (2008). Teacher expectations, classroom context, and the achievement gap. Journal of School Psychology, 46, 235–261.
Mello, Z. R. (2008). Gender variation in developmental trajectories of educational and occupational expectations and attainment from adolescence to adulthood. Developmental Psychology, 44, 1069–1080.
Meyers, J. L., & Beretvas, S. N. (2006). The impact of inappropriate modeling of cross-classified data structures. Multivariate Behavioral Research, 41, 473–497.
Neuenschwander, M. P., Vida, M., Garrett, J. L., & Eccles, J. S. (2007). Parents’ expectations and students’ achievement in two western nations. International Journal of Behavioral Development, 31, 594–602.
Paternoster, R., Brame, R., Mazerolle, P., & Piquero, A. (1998). Using the correct statistical test for the equality of regression coefficients. Criminology, 36, 859–866.
Persell, C. H., Catsambis, S., & Cookson, P. W. (1992). Family background, school type, and college attendance. A conjoint system of cultural capital transmission. Journal of Research on Adolescence, 2, 1–23.
Pollard, K. (2011). Gender gap in college enrollment and graduation. Population Reference Bureau. Retrieved from http://www.prb.org/Articles/2011/gender-gap-in-education.aspx.
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. Newbury Park: Sage.
Rosenthal, R., & Jacobson, L. (1968). Pygmalion in the classroom. New York: Holt, Rinehart & Winston.
Rutter, M. (1995). Psychosocial adversity: Risk, resilience, and recovery. Southern African Journal of Child and Adolescent Psychiatry., 7, 75–88.
Sandefur, G. D., Meier, A. M., & Campbell, M. E. (2006). Family resources, social capital, and college attendance. Social Science Research, 35, 525–553.
Sciarra, D. T., & Ambrosino, K. E. (2011). Post-secondary expectations and educational attainment. Professional School Counseling, 14, 231–241.
Stoll, M. A. (2010). Labor market advancement for young men: How it differs by educational attainment and race/ethnicity during the initial transition to work. Journal of Education for Students Placed at Risk, 15, 66–92.
Tavani, C., & Losh, S. (2003). Motivation, self-confidence, and expectations as predictors of the academic performances among our high school students. Child Study Journal, 33, 141–151.
Thomas, S. L., & Heck, R. H. (2001). Analysis of large-scale secondary data in higher education research: Potential perils associated with complex sampling designs. Research in Higher Education, 42, 517–540.
United States Census. (2010). College Enrollment of Recent High School Completers. Retrieved from http://www.census.gov/compendia/statab/2012/tables/12s0276.pdf.
United States Department of Education, National Center for Education Statistics. (2012). Digest of education statistics, 2011 (NCES 2012-001),Chapter 3. Retrieved from http://nces.ed.gov/fastfacts/display.asp?id=98.
Weinstein, R. S. (2002). Reaching Higher: The power of expectations in schooling. Cambridge: Harvard University Press.
Weinstein, R. S., Soulé, C. R., Collins, F., Cone, J., Mehlhorn, M., & Simontacchi, K. (1991). Expectations and high school change: Teacher-researcher collaboration to prevent school failure. American Journal of Community Psychology, 19, 333–364.
Weinstein, R. S., Gregory, A., & Strambler, M. (2004). Intractable self-fulfilling prophecies: Fifty years after Brown v Board of Education. American Psychologist, 59, 511–520.
Wood, D., Kurtz-Costes, B., & Copping, K. E. (2011). Gender differences in motivational pathways to college for middle class African American youths. Developmental Psychology, 47, 961–968.
Zhan, M. (2006). Assets, parental expectations and involvement, and children’s educational performance. Children and Youth Services Review, 28, 961–975.
Acknowledgments
This research was supported by a grant from the American Education Research Association which receives funds from its “AERA grants program” from the National Science Foundation under its NSF Grant #DRL-0941014. Opinions reflect those of the authors and do not necessarily reflect those of the granting agencies. The authors would also like to thank Rhona S. Weinstein for her contribution to the study.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gregory, A., Huang, F. It Takes a Village: The Effects of 10th Grade College-Going Expectations of Students, Parents, and Teachers Four Years Later. Am J Community Psychol 52, 41–55 (2013). https://doi.org/10.1007/s10464-013-9575-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10464-013-9575-5