The Strategic Use of Data in High-Performing Colleges
Keywords:
higher education, data-based decision-making, leadership, college completion, retention, use of dataAbstract
With the dramatically increasing capabilities of information technology, the effective use of data has become critical in higher education. Nevertheless, extant literature on how top-performing institutions foster data-based decision making is limited. We examined how institutions with higher-than-predicted graduation rates use data in decision-making. Site visits were conducted with in-depth interviews and focus groups at 5 institutions with 172 participants. Recurrent themes included: 1) senior leadership’s embrace of data, 2) emphasis on data relevance and its accessibility, and 3) strategic use of data. The findings may be helpful to policymakers and practitioners seeking effective ways to improve college graduation rates.
References
Adolfsson, C., & Hakansson, J. (2023). Data analysis for school improvement within coupled local school systems: Which data and with what purposes? Leadership and Policy in Schools, 22(3), 714–727.
Armstrong, D., Gosling, A., Weinman, J., & Marteau, T. (1997). The Place of Inter-Rater Reliability in Qualitative Research: An Empirical Study. Sociology, 31(3), 597–606.
Bradley, E.H., Curry, L.A., Ramanadhan, S., Rowe, L., Nembhard, I.M., & Krumholz, H.M. (2009). Research in action: Using positive deviance to improve quality of healthcare. Implementation Science, 4, 25.
Campbell, C., & Levin, B. (2009). Using data to support educational improvement. Educational Assessment, Evaluation, and Accountability, 21, 47–65.
Cardona, T., Cudnet, E., Hoeri, R., & Snyder, J. (2023). Data mining and machine learning retention models in higher education. Journal of College Student Retention: Research, Theory & Practice, 25(1), 51–75.
Carlson, D., Borman, D., & Robinson, M. (2011). A multistate district-level cluster randomized trial of the impact of data-driven reform on reading and mathematics achievement. Educational Evaluation and Policy Analysis, 33, 378–398.
Curry, L.A., Nembhard, I.M., & Bradley, E.H. (2009). Qualitative and mixed methods provide unique contributions to outcomes research. Circulation, 119(10), 1442–1452.
Ebbeler, J., Poortman, C.L., Schildkamp, K., & Pieters, J.M. (2015). Effects of a data use intervention on educators’ use of knowledge and skills. Studies in Educational Evaluation, 48, 19–31. https://doi.org/10.1016/j.stueduc.2015.11.002
Ebbeler, J., Poortman, C.L., Schildkamp, K., & Pieters, J.M. (2017). The effects of a data use intervention on educators’ satisfaction and data literacy. Educational Assessment, Evaluation, and Accountability, 29(1), 83–105.
Eshetu, M., Bjork, C., Maragh Taylor, W., Quock, M., & Bradley, E.H. (2025). “Woven In”: Mental Health and College Graduation Rates. Journal of College Student Retention: Research, Theory & Practice, 0(0), 1–21.
Gesel, S.A., LeJeune, L.M., Chow, J.C., Sinclair, A.C., & Lemons, C.J. (2021). A Meta-Analysis of the Impact of Professional Development on Teachers’ Knowledge, Skill, and Self-Efficacy in Data-Based Decision-Making. Journal of Learning Disabilities, 54(4), 269–283. https://doi.org/10.1177/0022219420970196
Glaser, B., & Strauss, A. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine Publishing Company.
Jimerson, J.B. (2014). Thinking about data: Exploring the development of mental models for “data use” among teachers and school leaders. Studies in Educational Evaluation, 42, 5–14. https://doi.org/10.1016/j.stueduc.2013.10.010
Kippers, W.B., Poortman, C.L., Schildkamp, K., & Visscher, A.J. (2017). Data literacy: What do educators learn and struggle with during a data use intervention? Studies in Educational Evaluation, 56, 21–31. https://doi.org/10.1016/j.stueduc.2017.11.001
Lincoln, Y., & Guba, E.G. (1985). Naturalistic Inquiry. Sage Publications.
Marsh, D.R., Schroeder, D.G., Dearden, K.A., Sternin, J., & Sternin, M. (2004). The power of positive deviance. BMJ (Clinical research ed.), 329(7475), 1177–1179.
Miles, M.B., Huberman, A.M., & Saldana, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). Sage.
Morse, J.M. (1994). Designing funded qualitative research. In N.K. Denzin & Y.S. Lincoln (Eds.), Handbook of qualitative research (pp. 220–235). Sage Publications.
National Center for Education Statistics. (2020). Undergraduate graduation rates. NCES Fast Facts.
Patton, M.Q. (2002). Qualitative research and evaluation methods (3rd ed.). Sage.
Park, V., Dale, A., & Guerra, A.W. (2012). Strategic framing: How leaders craft the meaning of data use for equity and learning. Educational Policy, 27(4), 645–675.
Poortman, C., & Schildkamp, K. (2016). Solving student achievement problems with data use intervention for teachers. Teaching and Teacher Education, 60, 425–433.
Ramaswami, G., Susnjak, T., & Mathrani, A. (2023). Effectiveness of a learning analytics dashboard for increasing student engagement levels. Journal of Learning Analytics, 10(3), 115–134.
Robershaw, K.L., Xiao, M., & Wolf, B.G. (2024). Research Analytics in Higher Education: Systematic Literature Review, Synthesis, and Conceptual Framework. Research Management Review, 27(2).
Schildkamp, K. (2019). Data-based decision-making for school improvement: Research insights and gaps. Educational Research, 61(3), 257–273.
Schildkamp, K., Poortman, C., Luyten, H., & Ebbeler, J. (2017). Factors promoting and hindering data-based decision making in schools. School Effectiveness and School Improvement, 28(2), 242–258.
Staman, L., Timmermans, A.C., & Visscher, A.J. (2017). Effects of a data-based decision-making intervention on student achievement. Studies in Educational Evaluation, 55, 58–67. https://doi.org/10.1016/j.stueduc.2017.07.002
Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed.). Sage Publications.
Tesfamariam, B., Alamo-Pastrana, C., & Bradley, E.H. (2023). Four-Year College Completion Rates: What Accounts for the Variation? Journal of Education, 0(0), 1–9.
Tinto, V., & Pusser, B. (2006). Moving From Theory to Action: Building a Model of Institutional Action for Student Success. National Postsecondary Education Cooperative, 1(15), 89–125.
Wayman, J.C., Jimerson, J.B., & Cho, V. (2012). Organizational considerations in establishing the Data Informed District. School Effectiveness and School Improvement, 23(2), 159–178. https://doi.org/10.1080/09243453.2011.652124
Wilcox, G., Fernandez Conde, C., & Kowbel, A. (2021). Using Evidence-Based Practice and Data-Based Decision Making in Inclusive Education. Education Sciences, 11(3), 129. https://doi.org/10.3390/educsci11030129
