Exploring the dynamics of organizational learning: identifying the decision chains science and math faculty use to plan and teach undergraduate courses

Background The field of STEM education is increasingly focusing on processes of individual, cultural, and organization-level change in postsecondary institutions, yet current approaches tend to focus on individual leverage points isolated from other factors and the broader institutional context. Research on reform implementation highlights how individual decision-making is shaped by a variety of inter-connected factors - or what we call 'decision chains’. Organizational learning theory offers a way to conceptualize how these decision chains are implicated in the change process. Organizational learning refers to the processes whereby organizations store information in what is known as the ‘organizational memory’, how this information is retrieved, and how alterations to these processes can affect organizational. In this paper, we report findings from a qualitative case study of how 24 science and math faculty at a large, public research university in the United States engaged with their organization’s memory while planning courses. We also explore how a reform initiative—the Undergraduate Science Education (USE) project—influenced these memory functions. We analyzed semi-structured interviews using a structured approach to grounded theory as well as techniques for graphically depicting verbal data. Results Results indicate that faculty accessed five repositories of curricular information within the organizational memory: individual memory, cultural norms, social networks and human resources, curricular artifacts, and external archives. When retrieving information from these repositories, faculty primarily ‘fine-tuned’ existing curricular artifacts (i.e., lecture notes and PowerPoint slides). Analyses of decision chains used by faculty highlight the idiosyncratic manner in which planning unfolds in practice, the centrality of existing artifacts, the role of contextual factors, and the absence of continuous improvement systems. Analyses of the USE project’s effects indicate changes to features of the organizational memory. Conclusions Besides contributing new insights into the nature of organizational learning in higher education, the decision chain method described in this paper can be used to complement existing metrics for program evaluation and to diagnose leverage points for new STEM education change efforts. A potentially useful approach may target curricular artifacts for regular updating and the imposition of continuous improvement systems, while allowing faculty local control over this process.