From Democratic to “Need to Know”: Linking Distributed Leadership to Data Cultures in the Florida College System

Abstract

This multiple case study examines the extent and ways in which leaders and administrators in Florida College System (FCS) institutions engage in distributed leadership through data sharing with frontline staff. Based on focus groups and individual interviews with administrators, faculty, and staff (659 participants) from 21 state colleges, we found a continuum of three data cultures ranging from democratic data cultures to blended data cultures to “need to know” data cultures. We triangulate these results with survey data from FCS institutional leaders and find considerable variation in the extent of data sharing and perceptions of effectiveness of institutional data use. Institutions with democratic data cultures tended to have distributed leadership that encouraged information sharing and collaboration among staff to use data to inform change. Need-to-know institutions faced challenges, including weak data quality, concerns about adequate time and resources among staff for reviewing data, and perceptions that staff lack data literacy skills.

Does the Method of Acceleration Matter? Exploring the Likelihood of College Coursetaking Success Across Four Developmental Education Instructional Strategies

“…Third, this study demonstrates the importance of using data to inform future decisions regarding which types of reform efforts to continue and where additional changes may be needed in order to address instructional strategies that tend to be ineffective in a particular subject area. Prior research on the implementation of Florida's developmental education reform has shown that there is substantial variation across institutions in the extent to which data are shared with frontline staff, as well as perceptions regarding the effectiveness of data use among the colleges (Brower et al, 2020). Nearly half of FCS institutions exhibited characteristics of "need to know" data cultures, such as not collecting data critical to improving practice, rarely making data available to staff at all levels, or failing to systematically collect or analyze data.…”

“…This is problematic because literature in organizational behavior has indicated that higher levels of data sharing may improve organizational performance (e.g., Bartol & Srivastava, 2002;Constant et al, 1994). Administrators should engage in a more distributive leadership style by increasing the accessibility of data to all staff, valuing staff's unique expertise in understanding underlying data trends, developing organizational procedures to promote data sharing, and facilitating communications across departments to inform data-driven decision making (Brower et al, 2020).…”

The Perceptions and Experiences of Faculty Implementing Florida’s Developmental Education Reform

“…Although initial research of SB 1720 revealed positive outcomes, most faculty were not aware of these findings and continued to hold some skepticism about the long-term effects of bypassing remediation. Presently, access to student outcome data is unevenly distributed throughout Florida College System institutions (Brower et al, 2020). If legislators and college administrators are explicit about the motivations behind reform, as well as positive and negative outcomes during the roll-out of reform efforts—particularly reform efforts which are highly contentious—morale can be increased and feelings of alienation, decreased.…”

Big Qual: Defining and Debating Qualitative Inquiry for Large Data Sets

“…In addition, big qual can present challenges for reporting theories and findings in a cohesive narrative when drawn from so much data. Collectively, we have learned to report the theory and research findings generated from big qual in a variety of ways, including single case studies with sections linking individuals' lived experiences within broad institution-level or system-level patterns (e.g., Brower, Bertrand Jones, & Hu, 2018;Nix et al, in press;Rutledge et al, 2015), and multiple case studies with vignettes illustrating findings within cases coupled with figures and/or tables summarizing patterns across all cases (e.g., Brower et al, in press;Brower, Mokher, Bertrand Jones, Cox, & Hu, 2019;Cohen-Vogel, Rutledge, & Osborne-Lampkin, 2011;Rutledge et al, 2015), and individual examples nested within composite institutions (e.g., Arnault, 2002;Brower et al, 2017;Conant, 2014). Composite institutions (or individuals) involve presenting data in vignettes that contain data from more than one institution or individual.…”