Governmentality in higher education : a critical analysis of the National Survey of Student Engagement (NSSE)

In this dissertation, the National Survey of Student Engagement (NSSE) serves as a nodal point through which to examine the power relations shaping the direction and practices of higher education in the twenty-first century. Theoretically, my analysis is informed by Foucault’s concept of governmentality, briefly defined as a technology of power that influences or shapes behavior from a distance. This form of governance operates through apparatuses of security, which include higher education. Foucault identified three essential characteristics of an apparatus—the market, the milieu, and the processes of normalization—through which administrative mechanisms and practices operate and govern populations. In this project, my primary focus is on the governance of faculty and administrators, as a population, at residential colleges and universities. I argue that the existing milieu of accountability is one dominated by the neoliberal assumption that all activity—including higher education—works best when governed by market forces alone, reducing higher education to a market-mediated private good. Under these conditions, what many in the academy believe is an essential purpose of higher education—to educate students broadly, to contribute knowledge for the public good, and to serve as society’s critic and social conscience (Washburn 227)—is being eroded. Although NSSE emerged as a form of resistance to commercial college rankings, it did not challenge the forces that empowered the rankings in the first place. Indeed, NSSE data are now being used to make institutions even more responsive to market forces. Furthermore, NSSE’s use has a normalizing effect that tends to homogenize classroom practices and erode the autonomy of faculty in the educational process. It also positions students as part of the system of surveillance. In the end, if aspects of higher education that are essential to maintaining a civil society are left to be defined solely in market terms, the result may be a less vibrant and, ultimately, a less just society.

Modeling and classifying variable width riparian zones utilizing digital elevation models, flood height data, digital soil data and national wetlands inventory : a new approach for riparian zone delineation

Riparian zones are dynamic, transitional ecosystems between aquatic and terrestrial ecosystems with well defined vegetation and soil characteristics. Development of an all-encompassing definition for riparian ecotones, because of their high variability, is challenging. However, there are two primary factors that all riparian ecotones are dependent on: the watercourse and its associated floodplain. Previous approaches to riparian boundary delineation have utilized fixed width buffers, but this methodology has proven to be inadequate as it only takes the watercourse into consideration and ignores critical geomorphology, associated vegetation and soil characteristics. Our approach offers advantages over other previously used methods by utilizing: the geospatial modeling capabilities of ArcMap GIS; a better sampling technique along the water course that can distinguish the 50-year flood plain, which is the optimal hydrologic descriptor of riparian ecotones; the Soil Survey Database (SSURGO) and National Wetland Inventory (NWI) databases to distinguish contiguous areas beyond the 50-year plain; and land use/cover characteristics associated with the delineated riparian zones. The model utilizes spatial data readily available from Federal and State agencies and geospatial clearinghouses. An accuracy assessment was performed to assess the impact of varying the 50-year flood height, changing the DEM spatial resolution (1, 3, 5 and 10m), and positional inaccuracies with the National Hydrography Dataset (NHD) streams layer on the boundary placement of the delineated variable width riparian ecotones area. The result of this study is a robust and automated GIS based model attached to ESRI ArcMap software to delineate and classify variable-width riparian ecotones.