Abstract
High-impact practices (HIPs), such as undergraduate research, internships, and senior-capstone projects, are prominent within the academy. Scholars surmise aspects of HIP quality (e.g., student effort, peer collaboration, and faculty interaction) are related to desired outcomes for students (e.g., engagement, GPA, and satisfaction). Using data from the 2015 administration of the National Survey of Student Engagement, respondents who participated in these three HIPs were asked additional questions regarding quality of experience. Results from this study indicate that increased levels of expectations, faculty interaction, and real-world application are related to increases in outcomes; however, these relationships are not consistent among underserved populations.
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References
Anakwe, U. P., & Greenhaus, J. H. (2000). Prior work experience and socialization experiences of college graduates. International Journal of Manpower, 21(2), 95–111.
Astin, A. W. (1977). Four critical years: effects of college on beliefs, attitudes, and knowledge. San Francisco: Jossey-Bass.
Bachand, D. J., Huntley, D., Hedberg, M., Dorne, C., Boye-Beaman, J., and Thorns. M. (2006). A monitoring report to the Higher Learning Commission on program assessment, general education assessment, and diversity. Retreieved from https://www.svsu.edu/emplibrary/HLC%20Final%20Report%202006%20-Web.pdf Accessed 13 Feb 2019.
Baird, L. L. (1976). Using self-reports to predict student performance. College Entrance Examination Board Research Monograph No. 7. New York: College Entrance Examination Board (ED 126 116).
Banta, T. W., & Palomba, C. A. (2015). Assessment essentials: planning, implementing, and improving assessment in higher education. San Francisco, CA: Jossey-Bass.
Bauer, K. W., & Bennett, J. S. (2008). Evaluation of the undergraduate research program at the University of Delaware: a multifaceted design. In R. Taraban & R. L. Blanton (Eds.), Creating effective undergraduate research programs in science: the transformation from student to scientist. New York: Teachers College Press.
Borrego, S. (2006). Mapping the learning environment. In R. P. Keeling (Ed.), Learning reconsidered 2: a practical guide to implementing a campus-wide focus on the student experience (pp. 11–16). Washington, DC: ACPA, ACUHOI, ACUI, NACADA, NACA, NASPA, NIRSA.
Bowman, N. A. (2011). Examining systematic errors in predictors of college student self-reported gains. In S. Herzog & N. A. Bowman (Eds.), Validity and limitations of college student self-report data (New Directions for Institutional Research series, No. 150) (pp. 7–20). San Francisco: Jossey-Bass.
Bowman, N. A., & Holmes, J. M. (2018). Getting off to a good start? First-year undergraduate research experiences and student outcomes. Higher Education, 76(1), 17–33.
Bowman, N.A., Kilgo, C.A., & Trolian, T. (2016, April). How problematic is self-selection bias in college impact research? An Examination of experiential propensity. Presented at the 2016 annual meeting of the American Educational Research Association: Washington, DC.
Buckley, J., Korkmaz, A., & Kuh, G. (2008). Disciplinary effects of undergraduate research experience with faculty on select student self-reported gains. Paper presented at the Association for the Study of Higher Education conference, Jacksonville.
Chickering, A. W., & Gamson, Z. F. (1987). Seven principles for good practice in undergraduate education. AAHE Bulletin, 3–7.
Davis, M., Dias-Bowie, Y., Greenberg, K., Klukken, G., Pollio, H. R., Thomas, S. P., & Thompson, C. L. (2004). A fly in the buttermilk: descriptions of university life by successful undergraduate students at a predominately White southeastern university. Journal of Higher Education, 74(4), 420–445.
Elgren, T., & Hensel, N. (2006). Undergraduate research experiences: synergies between scholarship and teaching. Peer Review, 8(1), 4.
Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: a new look at an old issue. Psychological Methods, 12(2), 121–138.
Ethington, C. A. (1997). A hierarchical linear modeling approach to studying college effects. In J. C. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 12). New York: Agathon Press.
Feagin, J. R., Vera, H., & Imani, N. (1996). The agony of education: Black students at White colleges and universities. New York: Routledge.
Fern, A., & Paris, D. (2013). How students, faculty, and institutions can fulfill the promise of capstones. Peer Review, 15(4).
Finley, A. P., & McNair, T. (2013). Assessing underserved students’ engagement in high-impact practices. Washington, D.C.: Association of American Colleges and Universities.
Fries-Britt, S. L., & Turner, B. (2002). Uneven stories: Successful Black collegians at a Black and a White campus. Review of Higher Education, 25(3), 315–330.
Garvey, J. C., BrckaLorenz, A., Latopolski, K., & Hurtado, S. S. (2018). High-impact practices and Student–Faculty interactions for students across sexual orientations. Journal of College Student Development, 59(2), 210–226.
Harper, S. R., Smith, E. J., & Davis, C. H. (2016). A critical race case analysis of black undergraduate student success at an Urban University. SAGE: Urban Education.
Hu, S., Scheuch, K., Schwartz, R., Gayles, J., & Li, S. (2008). Reinventing undergraduate education: engaging students in research and creative activities. ASHE Higher Education Report, Vol. 33, No. 4. San Francisco: Jossey-Bass.
Huber, B. (2010). Does participation in multiple high impact practices affect student success at Cal State Northridge?: Some preliminary insights. Office of Institutional Research: California State University Northridge.
Indiana University – Purdue University Indianapolis. (2017). RISE initiative. Retrieved from https://rise.iupui.edu/resources/course-development/taxonomies/.
Johnson, S. R., & Stage, F. K. (2018). Academic engagement and student success: do high-impact practices mean higher graduation rates?. The Journal of Higher Education, 1-29.
Kilgo, C. A., Sheets, J. K. E., & Pascarella, E. T. (2015). The link between high-impact practices and student learning: some longitudinal evidence. Higher Education, 69(4), 509–525.
Kuh, G. D. (2001). The National Survey of Student Engagement: Conceptual framework and overview of psychometric properties. Bloomington, IN: Indiana University Center for Postsecondary Research.
Kuh, G. D. (2008). High-impact educational practices: what they are, who has access to them, and why they matter. Washington, D.C.: Association of American Colleges and Universities.
Kuh, G.D. & Kinzie, J. (2018). What really makes a ‘high-impact' practice high impact? Inside Higher Ed. Retrieved from https://www.insidehighered.com/views/2018/05/01/kuh-and-kinzie-respond-essay-questioning-high-impact-practices-opinion
Kuh, G. D., O’Donnell, K., & Reed, S. (2013). Ensuring quality and taking high-impact practices to scale. Washington, D.C.: Association of American Colleges and Universities.
Kuh, G. D., O'Donnell, K. O., & Schneider, C. G. (2017). HIPs at ten. Change: The Magazine of Higher Learning, 49(5), 8–16.
Lopatto, D. (2004). Undergraduate research as a catalyst for liberal learning. Peer Review, 8(1), 22–25.
Maas, C., & Hox, M. (2005). Sufficient sample sizes for multilevel modeling. Methodology, 1, 86–92.
Miller, A. L. (2012). Investigating social desirability bias in student self-report surveys. Educational Research Quarterly, 36(1), 30–47.
Miller, A. L., Rocconi, L. M., & Dumford, A. D. (2018). Focus on the finish line: does high-impact practice participation influence career plans and early job attainment? Higher Education, 75(3), 489–506.
Moran, J. D., III, Wells, M. J., & Smitt-Aumen, A. (2015). Making undergraduate research a central strategy in high-impact practice reform: the PASSHE journey. New Directions for Higher Education, 2015(169), 61–71.
Muthén, L. (1999). Intraclass correlations. Downloaded on May 15 2014 from http://www.statmodel.com/discussion/messages/12/18.html
Muthén, B., & Satorra, A. (1995). Complex sample data in structural equation modeling. In P. Marsden (Ed.), Sociological Methodology, 1995 (pp. 267–316). Boston: Blackwell.
National Survey of Student Engagement. (2007). Experiences that matter: enhancing student learning and success. Retrieved from http://nsse.indiana.edu/NSSE_2007_Annual_Report/.
National Survey or Student Engagement. (2018). Retrieved from http://nsse.indiana.edu/html/engagement_indicators.cfm.
Ovink, S., & Veazey, B. (2011). More than “getting us through:” a case study in cultural capital enrichment of underrepresented minority undergraduates. Research in Higher Education, 52(4), 370–394.
Pace, C. R. (1980). Measuring the quality of student effort. In Improving Teaching and Institutional Quality, Current Issues In Higher Education, No. 1. Washington, D.C.: American Association for Higher Education.
Parker, E. T., III, Kilgo, C. A., Sheets, J. K. E., & Pascarella, E. T. (2016). The differential effects of internship participation on end-of-fourth-year GPA by demographic and institutional characteristics. Journal of College Student Development, 57(1), 104–109.
Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: a third decade of research (Vol. 2). San Francisco, CA: Jossey-Bass.
Patton, L. D., Harper, S. R., & Harris, J. (2015). Using critical race theory to (re)interpret widely-studied topics related to students in U.S. higher education. In A. M. Martínez Alemán, E. M. Bensimon, & B. Pusser (Eds.), Critical approaches to the study of higher education (pp. 193–219). Baltimore: Johns Hopkins University Press.
Pike, G. R. (1995). The relationship between self-reports of college experiences and achievement test scores. Research in Higher Education, 36, 1–21.
Pike, G. R. (1996). Limitations of using students’ self-reports of academic development as proxies for traditional achievement measures. Research in Higher Education, 37, 89–114.
Pike, G. R. (1999). The constant error of the halo in educational outcomes research. Research in Higher Education, 40, 61–86.
Pike, G. R., & Rocconi, L. M. (2012). Multilevel modeling: presenting and publishing the results for internal and external constituents. In Lott, J. L. & J. S. Antony. (Eds.), Multilevel modeling: Techniques and applications in institutional research (New Directions for Institutional Research, no.154, pp. 111-124). San Francisco: Jossey-Bass.
Porter, S. R. (2011). Do college student surveys have any validity? The Review of Higher Education, 35, 45–76.
Provencher, A., & Kassel, R. (2017). High-impact practices and sophomore retention: examining the effects of selection bias. Journal of College Student Retention: Research, Theory & Practice, 152102511769772.
Quaye, S. J., & Harper, S. R. (Eds.). (2014). Student engagement in higher education: Theoretical perspectives and practical approaches for diverse populations. Routledge.
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
Sims, L., & Falkenberg, T. (2013). Developing competencies for education for sustainable development: A case study of Canadian faculties of education. International Journal of Higher Education, 2(4), 1.
Simons, L., Fehr, L., Blank, N., Connell, H., Georganas, D., Fernandez, D., & Peterson, V. (2012). Lessons learned from experiential learning: what do students learn from a practicum/internship? International Journal of Teaching and Learning in Higher Education, 24(3), 325–334.
Snijders, T. A., & Bosker, R. J. (2011). Multilevel analysis: an introduction to basic and advanced multilevel modeling. SAGE.
State University of New York. (2017). Applied learning at SUNY. Retrieved from https://www.suny.edu/applied-learning/.
Stephen, J., Parente, D. H., & Brown, R. C. (2002). Seeing the forest and the trees: balancing functional and integrative knowledge using large-scale simulations in capstone business strategy classes. Journal of Management Education, 26(2), 164–193.
The Tennessee Board of Regents. (2016). TBR high impact practices. Retrieved from https://www.tbr.edu/academics/studentaffairs/tbr-high-impact-practices.
Thiry, H., Laursen, S. L., & Hunter, A. B. (2011). What experiences help students become scientists?: A comparative study of research and other sources of personal and professional gains for STEM undergraduates. The Journal of Higher Education, 82(4), 357–388.
Visher, M. G., Weiss, M. J., Weissman, E., Rudd, T., & Wathington, H. D. (2012). The effects of learning communities for students in developmental education: a synthesis of findings from six community colleges. New York: National Center for Postsecondary Research, Teachers College, Columbia University.
Wawrzynski, M., & Baldwin, R. (2014). Promoting high-impact student learning: connecting key components of the collegiate experience. New Directions for Higher Education, 2014(165), 51–62.
Wellman, J. & Brusi, R. (2013). Investing in success: Cost effective strategies to increase student success. Washington, D.C.: Association of American Colleges and Universities.
Wolniak, G. & Engberg, M. (2015). The Influence of “high-impact” college experiences on early career outcomes. Presented at the meeting of the American Education Research Association, Chicago.
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Zilvinskis, J. Measuring quality in high-impact practices. High Educ 78, 687–709 (2019). https://doi.org/10.1007/s10734-019-00365-9
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DOI: https://doi.org/10.1007/s10734-019-00365-9