When Do Honors Programs Make the Grade? Conditional Effects on College Satisfaction, Achievement, Retention, and Graduation


Many people within and outside of higher education view honors programs as providing meaningful academic experiences that promote learning and growth for high-achieving students. To date, the research exploring the link between honors participation and college grades and retention has obtained mixed results; some of the seemingly conflicting findings may stem from the presence of methodological limitations, including the difficulty with adequately accounting for selection into honors programs. In addition, virtually no research has explored the conditions under which honors programs are most strongly related to desired outcomes. To provide a rigorous examination of the potential impact of this experience, this study conducted propensity score analyses with a large, multi-institutional, longitudinal sample of undergraduates at 4-year institutions. In the full sample, honors participation predicts greater college GPA and 4-year graduation, while it is unrelated to college satisfaction and retention. However, these results differ notably by institutional selectivity: Honors participation is associated with greater college GPA, retention to the third and fourth years of college, and 4-year graduation at less selective institutions, but it is significantly related only to GPA at more selective institutions. These relationships are also sometimes larger among students from historically underrepresented groups.

This is a preview of subscription content, log in to check access.

Access options

Buy single article

Instant unlimited access to the full article PDF.

US$ 39.95

Price includes VAT for USA

Subscribe to journal

Immediate online access to all issues from 2019. Subscription will auto renew annually.

US$ 99

This is the net price. Taxes to be calculated in checkout.

Fig. 1


  1. 1.

    In this paper, the term “honors programs” will be used to describe academic initiatives that include department-based programs (e.g., “departmental honors”), institution-wide programs (e.g., “college honors”), and entire colleges within a university (which represents a broader organizational structure). The National Collegiate Honors Council (2017) describes “honors education” as being “characterized by in-class and extracurricular activities that are broader, deeper, or more complex than comparable learning experiences typically found at institutions of higher education” (para. 1).


  1. Achterberg, C. (2005). What is an honors student? Journal of the National Collegiate Honors Council, 6(1), 75–83.

  2. Akers, A. (2010). Determination of the optimal number of strata for bias reduction in propensity score matching. Dissertation Abstracts International, 71(08), 58A. (UMI No. 3417726)

  3. An, B. P., Loes, C. N., & Trolian, T. L. (in press). Binge drinking on academic performance: Considering mediating effects of academic involvement. Journal of College Student Development.

  4. Astin, A. W. (1970). The methodology of research on college impact, part one. Sociology of Education, 43(3), 223–254.

  5. Astin, A. W. (1984). Student involvement: A developmental theory for higher education. Journal of College Student Personnel, 25(4), 297–308.

  6. Astin, A. W. (1993). What matters in college? Four critical years revisited. San Francisco: Jossey-Bass.

  7. Austin, C. G. (1991). Honors programs: Development, review, and revitalization. Charleston: National Collegiate Honors Council.

  8. Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioral Research, 46, 399–424.

  9. Bailey, T., Jaggars, S. S., & Jenkins, D. (2015). Redesigning America’s community colleges: A clearer path to student success. Cambridge: Harvard University Press.

  10. Bean, J., & Eaton, S. (2000). A psychological model of college student retention. In J. M. Braxton (Ed.), Reworking the student departure puzzle (pp. 48–61). Nashville: Vanderbilt University Press.

  11. Berger, J. B., & Milem, J. F. (2000). Organizational behavior in higher education and student outcomes. In J. Smart (Ed.), Higher education: Handbook of theory and research (pp. 268–338). New York: Agathon Press.

  12. Biemer, P. P., & Christ, S. L. (2008). Weighting survey data. In E. D. de Leeuw, J. J. Hox, & D. A. Dillman (Eds.), International handbook of survey methodology (pp. 317–341). New York: Psychology Press.

  13. Bowman, N. A., & Culver, K. (in press). Promoting equity and student learning: Rigor in undergraduate academic experiences. In C. M. Campbell (Ed.), Reframing notions of rigor: Building scaffolding for equity and student success (New Directions for Higher Education). San Francisco, CA: Jossey-Bass.

  14. Bowman, N. A., Denson, N., & Park, J. J. (2016). Racial/cultural awareness workshops and post-college civic engagement: A propensity score matching approach. American Educational Research Journal, 53(6), 1556–1587.

  15. Bowman, N. A., Park, J. J., & Denson, N. (2015). Student involvement in ethnic student organizations: Examining civic outcomes six years after graduation. Research in Higher Education, 56(2), 127–145.

  16. Braxton, J. M., Hirschy, A. S., & McClendon, S. A. (2004). Understanding and reducing college student departure (ASHE-ERIC Higher Education Report 30-3). San Francisco: Jossey-Bass.

  17. Brookhart, M. A., Schneeweiss, S., Rothman, K. J., Glynn, R. J., Avorn, J., & Stürmer, T. (2006). Variable selection for propensity score models. American Journal of Epidemiology, 163(12), 1149–1156.

  18. Cabin, R. J., & Mitchell, R. J. (2000). To Bonferroni or not to Bonferroni: When and how are the questions. Bulletin of the Ecological Society of America, 81(3), 246–248.

  19. Cabrera, A. F., Nora, A., & Castañeda, M. B. (1992). The role of finances in the persistence process: A structural model. Research in Higher Education, 33, 571–593.

  20. Cacioppo, J., Petty, R., Feinstein, J., & Jarvis, W. (1996). Dispositional differences in cognitive motivation: The life and times of individuals varying in need for cognition. Psychological Bulletin, 119, 197–253.

  21. Chen, R., & DesJardins, S. L. (2010). Investigating the impact of financial aid on student dropout risks: Racial and ethnic differences. Journal of Higher Education, 81(2), 179–208.

  22. Cochran, W. G. (1968). The effectiveness of adjustment by subclassification in removing bias in observational studies. Biometrics, 24, 295–313.

  23. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah: Lawrence Erlbaum.

  24. Cosgrove, J. R. (2004). The impact of honors programs on undergraduate academic performance, retention, and graduation. Journal of the National Collegiate Honors Council, 5(2), 45–53.

  25. Cruce, T. M. (2009). A note on the calculation and interpretation of the delta-p statistic for categorical independent variables. Research in Higher Education, 50(6), 608–622.

  26. Cruce, T. M., Wolniak, G. C., Seifert, T. A., & Pascarella, E. T. (2006). Impacts of good practices on cognitive development, learning orientations, and graduate degree plans during the first year of college. Journal of College Student Development, 47(4), 365–383.

  27. Digby, J. (2005). Peterson’s smart choices: Honors programs and colleges (4th ed.). Lawrenceville: Thomson Peterson’s.

  28. Eckles, J. E., & Stradley, E. G. (2012). A social network analysis of student retention using archival data. Social Psychology of Education, 15, 165–180.

  29. Farrington, C. A., Roderick, M., Allensworth, E., Nagaoka, J., Keyes, T. S., Johnson, D. W., et al. (2012). Teaching adolescents to become learners. The role of noncognitive factors in shaping school performance: A critical literature review. Chicago: University of Chicago Consortium on Chicago School Research.

  30. Graunke, S. S., & Woosley, S. A. (2005). An exploration of the factors that affect the academic success of college sophomores. College Student Journal, 39(2), 367–376.

  31. Griswald, M. E., Localio, A. R., & Mulrow, C. (2010). Propensity score adjustment with multilevel data: Setting your sites on decreasing selection bias. Annals of Internal Medicine, 152(6), 393–395.

  32. Groves, R. M., Fowler, F. J., Jr., Couper, M. P., Lepkowski, J. M., Singer, E., & Tourangeau, R. (2009). Survey methodology (2nd ed.). Hoboken: Wiley.

  33. Guo, S., & Fraser, M. W. (2015). Propensity score analysis: Statistical methods and applications (2nd ed.). Los Angeles: Sage.

  34. Haak, D. C., Hille Ris Lambers, J., Pitre, E., & Freeman, S. (2011). Increased structure and active learning reduce the achievement gap in introductory biology. Science, 332(6034), 1213–1216.

  35. Hartleroad, G. E. (2005). Comparison of the academic achievement of first year female honors program and non-honors program engineering students. Journal of the National Collegiate Honors Council, 6(2), 109–120.

  36. Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. New York: Routledge.

  37. Heck, R. H., & Thomas, S. L. (2009). An introduction to multilevel modeling techniques (2nd ed.). New York: Routledge.

  38. Herzog, S. (2011). Gauging academic growth of bachelor degree recipients: Longitudinal vs. self-reported gains in general education. In S. Herzog & N. A. Bowman (Eds.), Validity and limitations of college student self-report data (New Directions for Institutional Research, No. 150, pp. 113–120). San Francisco: Jossey-Bass.

  39. Holmes, W. M. (2013). Using propensity scores in quasi-experimental designs. Los Angeles: Sage.

  40. Hong, G., & Raudenbush, S. W. (2005). Effects of kindergarten retention policy on children’s cognitive growth in reading and mathematics. Educational Evaluation and Policy Analysis, 27, 205–224.

  41. Hong, G., & Raudenbush, S. W. (2006). Evaluating kindergarten retention policy: A case study of causal inference for multilevel observational data. Journal of the American Statistical Association, 101, 901–910.

  42. Ishitani, T. T. (2008). How do transfers survive after “transfer shock”? A longitudinal study of transfer student departure. Research in Higher Education, 49(5), 403–419.

  43. Jaccard, J., & Turrisi, R. (2003). Interaction effects in multiple regression (2nd ed.). Newbury Park: Sage.

  44. Jaeger, A. J., & Eagan, M. K., Jr. (2011). Examining retention and contingent faculty use in a state system of public higher education. Educational Policy, 25(3), 507–537.

  45. Johnson, V. E. (2003). Grade inflation: A crisis in higher education. New York: Springer.

  46. Keller, R. R., & Lacy, M. G. (2013). Propensity score analysis of an honors program’s contribution to students’ retention and graduation outcomes. Journal of the National Collegiate Honors Council, 2, 73–84.

  47. Kim, M. M. (2002). Cultivating intellectual development: Comparing women-only colleges and coeducational colleges for educational effectiveness. Research in Higher Education, 43(4), 447–481.

  48. Kinzie, J., Gonyea, R., Kuh, G. D., Umbach, P. D., Blaich, C., & Korkmaz, A. (2007, November). The relationship between gender and student engagement in college. Paper presented at the annual meeting of the Association for the Study of Higher Education, Louisville, KY.

  49. Kuh, G. D., Cruce, T. M., Shoup, R., & Kinzie, J. (2008). Unmasking the effects of student engagement on first-year college grades and persistence. Journal of Higher Education, 79(5), 540–563.

  50. Li, D. (2010). They need help: Transfer students from four-year to four-year institutions. Review of Higher Education, 33(2), 207–238.

  51. Mayhew, M. J., Rockenbach, A. N., Bowman, N. A., Seifert, T. A., Wolniak, G. C., Pascarella, E. T., et al. (2016). How college affects students (Vol. 3): 21st century evidence that higher education works. San Francisco: Jossey-Bass.

  52. Melguizo, T. (2011). A review of the theories developed to describe the process of college persistence and attainment. In J. C. Smart & M. B. Paulsen (Eds.), Higher education: Handbook of theory and research (Vol. 26, pp. 395–424). New York: Springer.

  53. Moon, J. L. (2012). Honors and high-ability students: Factors that predict academic efficacy, critical thinking skills, and academic goals. Doctoral dissertation, Available from Proquest Dissertations and Theses database (UMI No. 3511628)

  54. Museus, S. D. (2014). The culturally engaging campus environments (CECE) model: A new theory of college success among racially diverse student populations. In M. B. Paulsen (Ed.), Higher education: Handbook of theory and research (pp. 189–227). New York: Springer.

  55. National Collegiate Honors Council. (2017). About NCHC. Retrieved from

  56. Ogilvie, K., & Reza, E. M. (2009). Business student performance in traditional vs. honors course settings. Business Education Innovation Journal, 1(2), 31–37.

  57. Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124(1), 54–74.

  58. Pace, C. R. (1982). Achievement and the quality of student effort. Washington, DC: U.S. Department of Education.

  59. Pan, W., & Bai, H. (Eds.). (2015). Propensity score analysis: Fundamentals and developments. New York: Guilford Press.

  60. Park, D. C. & Maisto, A. A. (1984). Assessment of the impact of an introductory honors psychology course on students: Initial and delayed effects. Annual Meeting of the Southeastern Psychological Association (p. 14).

  61. Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students (Vol. 2): A third decade of research. San Francisco, CA: Jossey-Bass.

  62. Patrick, A. R., Schneeweiss, S., Brookhart, M. A., Glynn, R. J., Rothman, K. J., Avorn, J., et al. (2011). The implications of propensity score variable selection strategies in pharmacoepidemiology: An empirical illustration. Pharmacoepidemiology and Drug Safety, 20(6), 551–559.

  63. Pflaum, S. W., Pascarella, E. T., & Duby, P. (1985). The effects of honors college participation on academic performance during the freshman year. Journal of College Student Personnel, 26(5), 414–419.

  64. Preszler, R. W. (2009). Replacing lecture with peer-led workshops improves student learning. CBE—Life Sciences Education, 8(3), 182–192.

  65. Radford, A. W., Berkner, L., Wheeless, S. C., & Shepherd, B. (2010). Persistence and attainment of 2003–04 beginning postsecondary students: After 6 years (NCES 2011-151). Washington, DC: U.S. Department of Education.

  66. Raley, R. K., Kim, Y., & Daniels, K. (2012). Young adults’ fertility expectations and events: Associations with college enrollment and persistence. Journal of Marriage & Family, 74(4), 866–879.

  67. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Newbury Park: Sage.

  68. Rice, W. R. (1989). Analyzing tables of statistical tests. Evolution, 43(1), 223–225.

  69. Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138, 353–387.

  70. Rinn, A. N. (2007). Effects of programmatic selectivity on the academic achievement, academic self-concepts, and aspirations of gifted college students. Gifted Child Quarterly, 51(3), 232–245.

  71. Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130, 261–288.

  72. Roksa, J. (2011). Differentiation and work: Inequality in degree attainment in U.S. higher education. Higher Education, 61(3), 293–308.

  73. Roksa, J., & Keith, B. (2008). Credits, time, and attainment: Articulation policies and success after transfer. Educational Evaluation and Policy Analysis, 30(3), 236–254.

  74. Roszkowski, M. J., & Nigro, R. A. (2015). The value of SAT scores and high school grades in the selection of honors program candidates from the perspective of honors students and graduates. Strategic Enrollment Management Quarterly, 2(4), 259–293.

  75. Ryff, C. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology, 57, 1069–1081.

  76. Seifert, T. A., Pascarella, E. T., Colangelo, N., & Assouline, S. (2007). The effects of honors program participation on experiences of good practices and learning outcomes. Journal of College Student Development, 48(1), 57–74.

  77. Shushok, F. (2002). Educating the best and the brightest: Collegiate honors programs and the intellectual, social and psychological development of students. Doctoral dissertation. Available from Proquest Dissertations and Theses database (UMI No. 3070562).

  78. Shushok, F. J. (2006). Student outcomes and honors programs: A longitudinal study of 172 honors students 2000–2004. Journal of the National Collegiate Honors Council, 7(2), 85–96.

  79. Slavin, C., Coladarci, T., & Pratt, P. A. (2008). Is student participation in a honors program related to retention and graduation rates? Journal of the National Collegiate Honors Council, 9(2), 59–69.

  80. Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling (2nd ed.). Thousand Oaks, CA: Sage.

  81. Somers, P., Woodhouse, S., & Cofer, J. (2004). Pushing the boulder uphill: The persistence of first-generation college students. NASPA Journal, 41(3), 418–435.

  82. St John, E. P., Hu, S., Simmons, A., Carter, D. F., & Weber, J. (2004). What difference does a major make? The influence of college major field on persistence by African American and White students. Research in Higher Education, 45(3), 209–232.

  83. Steiner, P. M., Cook, T. D., Li, W., & Clark, M. H. (2015). Bias reduction in quasi-experiments with little selection theory but many covariates. Journal of Research on Educational Effectiveness, 8, 552–576.

  84. Strayhorn, T. L. (2012). College students’ sense of belonging: A key to educational success for all students. New York: Routledge.

  85. Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.). Chicago: University of Chicago Press.

  86. Vaughan, A. L., Lalonde, T. L., & Jenkins-Guarnieri, M. A. (2014). Assessing student achievement in large-scale educational programs using hierarchical propensity scores. Research in Higher Education, 55, 564–580.

  87. Wang, Q. (2015). Propensity score matching on multilevel data. In W. Pan & H. Bai (Eds.), Propensity score analysis: Fundamentals and developments (pp. 217–235). New York: Guilford.

  88. Westreich, D., Cole, S. R., Funk, M. J., Brookhart, M. A., & Stürmer, T. (2011). The role of the c-statistic in variable selection for propensity score models. Pharmacoepidemiology and Drug Safety, 20(3), 317–320.

  89. Wolgemuth, A., Whalen, D., Sullivan, J., Nading, C., Shelley, M., & Wang, Y. (2007). Financial, academic and environmental influences on the retention and graduation of students. Journal of College Student Retention, 8(4), 457–475.

  90. Xiang, Y., & Wang, S. (2013). An application of propensity score stratification using multilevel models: Do charter schools make a difference in student achievement and growth?. Portland: Northwest Evaluation Association.

  91. Yeager, D. S., & Walton, G. M. (2011). Social-psychological interventions in education: They’re not magic. Review of Educational Research, 81, 267–301.

Download references


This research was supported by a grant from the Center of Inquiry in the Liberal Arts at Wabash College to the Center for Research on Undergraduate Education at the University of Iowa.

Author information

Correspondence to Nicholas A. Bowman.

Appendix: Descriptive statistics overall and by honors participation

Appendix: Descriptive statistics overall and by honors participation

Variable All students Honors students Non-honors students
College GPA in the first year .00 1.00 .61 .82 −.10 .99
College GPA in the fourth year .00 1.00 .40 .90 −.06 1.00
College satisfaction at end of first year .00 1.00 .02 1.01 −.01 .99
College satisfaction at end of fourth year .00 1.00 −.01 1.00 .01 1.00
Retention to fall of second year .92 .28 .95 .21 .91 .28
Retention to fall of third year .84 .37 .90 .30 .83 .37
Retention to fall of fourth year .82 .39 .87 .34 .81 .39
Graduated within 4 years .61 .49 .67 .47 .60 .49
Honors participation .15 .36 1.00 .00 .00 .00
Standardized test scores 24.58 4.81 26.02 4.77 24.42 4.76
B HSGPA .40 .49 .26 .44 .42 .49
C or lower HSGPA .05 .21 .02 .13 .05 .21
High school studying alone 4.07 .98 4.18 .97 4.06 .98
High school studying with friends 2.75 1.01 2.80 .98 2.75 1.01
High school activities 3.72 1.23 3.90 1.16 3.70 1.24
High school socializing 4.42 .76 4.41 .77 4.43 .76
High school teacher interactions 3.37 1.00 3.46 1.03 3.35 .99
High school volunteering 3.11 1.11 3.23 1.07 3.10 1.11
High school working for pay 3.30 1.40 3.30 1.41 3.29 1.40
High school drinking .53 .94 .48 .94 .54 .93
High school smoking 1.06 .30 1.05 .25 1.06 .30
Asian American/Pacific Islander .06 .23 .05 .21 .06 .24
Black/African American .11 .31 .11 .31 .11 .31
Latino/Hispanic/Chicano .05 .21 .04 .19 .05 .22
Other race/ethnicity .02 .16 .02 .14 .02 .15
Male .44 .50 .43 .49 .44 .50
Parental education 15.22 2.22 15.44 2.16 15.21 2.22
Highest intended degree 4.33 1.18 4.60 1.19 4.29 1.18
Academic motivation 3.57 .57 3.69 .58 3.55 .56
Need for cognition 3.39 .61 3.51 .64 3.37 .60
Psychological well-being 4.50 .61 4.58 .63 4.50 .60
Importance of social/political involvement 2.63 .53 2.67 .55 2.63 .52
Intended business major .15 .35 .16 .36 .14 .35
Intended education major .08 .27 .07 .25 .08 .26
Intended engineering major .07 .26 .06 .24 .07 .26
Intended humanities/fine arts major .11 .31 .11 .31 .11 .31
Intended health major .11 .31 .13 .33 .11 .31
Intended mathematics/statistics major .02 .12 .02 .14 .01 .12
Intended natural sciences major .12 .32 .12 .33 .11 .32
Intended other major .11 .31 .12 .32 .10 .31
Regional university .30 .46 .26 .44 .29 .46
Research university .38 .49 .47 .50 .38 .48
Institutional selectivity 3.72 1.18 3.52 1.07 3.77 .48

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Bowman, N.A., Culver, K. When Do Honors Programs Make the Grade? Conditional Effects on College Satisfaction, Achievement, Retention, and Graduation. Res High Educ 59, 249–272 (2018).

Download citation


  • Honors programs
  • College honors
  • College satisfaction
  • Academic achievement
  • Retention
  • Graduation
  • Institutional selectivity