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Getting off to a good start? First-year undergraduate research experiences and student outcomes

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Abstract

Undergraduate research is widely perceived as a “high-impact practice” that promotes students’ learning, cognition, career planning, and educational attainment. With some exceptions, the existing evidence largely provides support for these beliefs. However, these studies typically examine research experiences that occur later in the undergraduate years, whereas engaging in undergraduate research during the first year is becoming increasingly common. First-year experiences may yield different outcomes than later experiences for a variety of reasons; in addition, previous studies often do not account sufficiently for self-selection into undergraduate research, which may be especially problematic for cross-sectional studies that occur in the junior or senior year. Therefore, this study examines the potential impact of first-year undergraduate research using propensity score analyses within a large, multi-institutional, longitudinal dataset. Research participation is significantly and positively related to first-year university satisfaction and fourth-year undergraduate GPA, but it is unrelated to satisfaction and grades in other years as well as graduate degree intentions, retention at the same institution, and 4-year graduation. Conditional analyses indicate that these effects are largely consistent across student demographics, pre-university achievement, and institutional selectivity.

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References

  • Adedokun, O. A., Bessenbacher, A. B., Parker, L. C., Kirkham, L. L., & Burgess, W. D. (2013). Research skills and STEM undergraduate research students’ aspirations for research careers: mediating effects of research self-efficacy. Journal of Research in Science Teaching, 50(8), 940–951.

    Article  Google Scholar 

  • Arum, R., & Roksa, J. (2011). Academically adrift: limited learning on college campuses. Chicago: University of Chicago Press.

    Google Scholar 

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

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Boyer Commission on Educating Undergraduates in the Research University. (1998). Reinventing undergraduate education: a blueprint for America’s research universities. Stony Brook: State University of New York.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Center for Research on Undergraduate Education. (2008). Quantitative methods section for the Wabash National Study of Liberal Arts Education. Iowa City: Author, University of Iowa Retrieved from https://education.uiowa.edu/sites/education.uiowa.edu/files/documents/centers/crue/research_methods_draft_march2008.pdf.

    Google Scholar 

  • Center of Inquiry. (2016). Outcomes and experiences measures: Wabash National Study 2006–2012. Crawfordsville: Author, Wabash College Retrieved from http://www.liberalarts.wabash.edu/study-instruments/.

    Google Scholar 

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

    Article  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Mahwah: Lawrence Erlbaum.

    Google Scholar 

  • Dong, N., & Maynard, R. A. (2013). Power Up! A tool for calculating minimum detectable effect sizes and sample size requirements for experimental and quasi-experimental designs. Journal of Research on Educational Effectiveness, 6, 24–67.

    Article  Google Scholar 

  • Gregerman, S. R., Lerner, J. S., von Hippel, W., Jonides, J., & Nagda, B. A. (1998). Undergraduate student-faculty research partnerships affect student retention. The Review of Higher Education, 22(1), 55–72.

    Article  Google Scholar 

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

    Google Scholar 

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

    Google Scholar 

  • Hathaway, R. S., Nagda, B. A., & Gregerman, S. R. (2002). The relationship of undergraduate research participation to graduate and professional education pursuit: an empirical study. Journal of College Student Development, 43(5), 614–631.

    Google Scholar 

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

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Hurtado, S., Eagan, M. K., Cabrera, N. L., Lin, M. H., Park, J., & Lopez, M. (2008). Training future scientists: predicting first-year minority student participation in health science research. Research in Higher Education, 49(2), 126–152.

    Article  Google Scholar 

  • Jaccard, J., & Turrisi, R. (2003). Interaction effects in multiple regression (2nd ed.). Thousand Oaks: Sage.

  • Jones, M. T., Barlow, A. E., & Villarejo, M. (2010). Importance of undergraduate research for minority persistence and achievement in biology. The Journal of Higher Education, 81(1), 82–115.

    Article  Google Scholar 

  • Kilgo, C. A., & Pascarella, E. T. (2016). Does independent research with a faculty member enhance four-year graduation and graduate/professional degree plans? Convergent results with different analytical methods. Higher Education, 71(4), 575–592.

    Article  Google Scholar 

  • Kilgo, C. A., Sheets, J. K. E., & Pascarella, E. T. (2014). The link between high-impact practices and student learning: some longitudinal evidence. Higher Education, 69(4), 509–525.

    Article  Google Scholar 

  • Kim, M. M., & Conrad, C. F. (2006). The impact of historically Black colleges and universities on the academic success of African-American students. Research in Higher Education, 47(4), 399–427.

    Article  Google Scholar 

  • Kim, Y. K., & Sax, L. J. (2009). Student–faculty interaction in research universities: differences by student gender, race, social class, and first-generation status. Research in Higher Education, 50(5), 437–459.

    Article  Google Scholar 

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

    Google Scholar 

  • Kuh, G. D. (2008). High-impact educational practices: what they are, who has access to them, and why they matter. Washington, DC: Association of American Colleges and Universities.

    Google Scholar 

  • Kuh, G. D., Chen, P. D., Nelson Laird, T. F., & Gonyea, R. M. (2007). Teacher-scholars and student engagement: some insights from FSSE and NSSE. American Council of Learned Societies (ACLS), student learning and faculty research: connecting teaching and scholarship. A Teagle foundation white paper from the ACLS Teagle Foundation Working Group on the Teacher-Scholar. New York: American Council of Learned Societies. http://education.indiana.edu/dotnetforms/Profile.aspx?u=tflaird

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

    Article  Google Scholar 

  • Lopatto, D. (2006). Undergraduate research as a catalyst for liberal learning. Peer Review, 8(1), 22–25.

    Google Scholar 

  • Lopatto, D. (2010). Undergraduate research as a high-impact student experience. Peer Review, 12(2), 27.

    Google Scholar 

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

    Google Scholar 

  • Merkel, C. A. (2003). Undergraduate research at the research universities. New Directions for Teaching and Learning, 93, 39–53.

    Article  Google Scholar 

  • Nagda, B. A., Gregerman, S. R., Jonides, J., von Hippel, W., & Lerner, J. S. (1998). Undergraduate student-faculty research partnerships affect student retention. Review of Higher Education, 22(1), 55–72.

  • Pace, C. R. (1982). Achievement and the quality of student effort: report prepared for the National Commission on Excellence in Education. Los Angeles: Higher Education Research Institute, University of California at Los Angeles.

    Google Scholar 

  • Patrick, A. R., Schneeweiss, S., Brookhart, M. A., Glynn, R. J., Rothman, K. J., Avorn, J., & Stürmer, T. (2011). The implications of propensity score variable selection strategies in pharmacoepidemiology—an empirical illustration. Pharmacoepidemiology and Drug Safety, 20(6), 551–559.

    Article  Google Scholar 

  • 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.

    Google Scholar 

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

    Google Scholar 

  • Seymour, E., Hunter, A. B., Laursen, S. L., & DeAntoni, T. (2004). Establishing the benefits of research experiences for undergraduates in the sciences: first findings from a three-year study. Science Education, 88(4), 493–534.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Zydney, A. L., Bennett, J. S., Shahid, A., & Bauer, K. W. (2002). Impact of undergraduate research experience in engineering. Journal of Engineering Education, 91(2), 151–157.

    Article  Google Scholar 

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Correspondence to Nicholas A. Bowman.

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Bowman, N.A., Holmes, J.M. Getting off to a good start? First-year undergraduate research experiences and student outcomes. High Educ 76, 17–33 (2018). https://doi.org/10.1007/s10734-017-0191-4

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