Reframing Data-Driven Decision Making as Organizational Learning

• In Event: Performance Funding and Organizational Learning in Higher Education

Abstract

Purpose
Despite the expectation that community college make decisions based on evidence to improve student outcomes, research on data use in post-secondary education is still scant; empirical research on data-driven decision making (DDDM) focuses on K-12 (Coburn & Bueschel, 2012; Coburn & Turner, 2011; Turner & Coburn, 2012). Furthermore, efforts to reform education through externally imposed accountability policies, e.g., those requiring data collection and reporting, frequently neglect schools’ capacity to respond to demands (Abelmann & Elmore, 1999; Smylie & Evans, 2006). If we view data-driven decision making as an organizational learning (OL) effort (Borden & Kezar, 2012) then whether and how members of an organization collaborate and interact (Spillane, 2012) to engage in inquiry to create new knowledge influences the capacity for data-driven change. This paper addresses the following research questions:
1. What role do collaborative activities play in the use of data to inform decisions about student success in community colleges?
2. What forms for organizational social capital exist in community colleges seeking to be data-driven?
3. Does the presence of social capital relate to the extent of data-driven decision making at community colleges?
4. How does organizational social capital facilitate organizational learning?

Theoretical Framework
Viewing DDDM as an OL process (Borden & Kezar, 2012 ) rather than a decision making process emphasizes the collaborative nature of data-driven reform; interactions provide opportunities for knowledge creation (Leana & Van Buren III, 1999) through exchange and combination of information (Nahapiet & Ghoshal, 1998). Social capital theory is useful to understand those interactions. Organizational social capital develops through associability, i.e., the willingness to subordinate individual goals to group goals, and trust, which in turn leads to positive outcomes by facilitating the development of intellectual capital. The framework integrates theory on organizational social capital and OL to understand colleges’ capacity for DDDM.

Methods
Surveys and interviews of faculty and administrators at two community colleges in New Mexico and two in Virginia captured social capital at the organizational level and individual understandings of the collaborative activities contributing to data use. Colleges with varying capacities for data-driven decision making were selected in New Mexico and Virginia because of the rigorous accrediting requirements and performance funding legislation requiring the regular reporting of data in both states.

Findings
Preliminary analyses suggest that collaborative activities such as regular meetings and participation in formal working groups provide faculty and administrators with opportunities to engage with data in groups; such opportunities are related to greater data use. The data also suggest that administrators engage more consistently in collaborative activities than faculty and that trust may not be important to organizational social capital. Finally, the presence of organizational social capital appears related to the extent of data-driven decision making at these community colleges. Colleges with more collaboration and expectations for data use tended to use data more frequently and to a greater extent than colleges with a less collaborative environment and with fewer norms of data use.

Author

• Monica Reid Kerrigan, Rowan University