Browsing by Subject "Winter"

Now showing 1 - 2 of 2

"At First It was Annoying": Results from Requiring Writers in Developmental Courses to Visit the Writing Center
(2017) Pfrenger, Wendy; Blasiman, Rachael N.; Winter, James
From fall 2013 through spring 2016, 1,301 students were enrolled in composition courses on our regional campus, with 349 of these enrolled in developmental courses. Our writing center serves approximately 14% of the campus population every year, a number we have seen increase since two professors in 2013-2014 began requiring students in their developmental courses to attend a minimum number of writing sessions each semester. The D-Fwithdrawal rates for developmental writing courses on our campus have averaged 32.7% over the past six semesters, an improvement over previous years. Analysis of data from a study of student outcomes during this period demonstrates that requiring frequent visits to the writing center in early semesters results in a statistically significant, positive relationship with increased passing rates and voluntary usage of the writing center.
Enhanced Migratory Waterfowl Distribution Modeling by Inclusion of Depth to Water Table Data
(Public Library of Science, 2012-01-17) Kreakie, Betty J.; Fan, Ying; Keitt, Timothy H.
In addition to being used as a tool for ecological understanding, management and conservation of migratory waterfowl rely heavily on distribution models; yet these models have poor accuracy when compared to models of other bird groups. The goal of this study is to offer methods to enhance our ability to accurately model the spatial distributions of six migratory waterfowl species. This goal is accomplished by creating models based on species-specific annual cycles and introducing a depth to water table (DWT) data set. The DWT data set, a wetland proxy, is a simulated long-term measure of the point either at or below the surface where climate and geological/topographic water fluxes balance. For species occurrences, the USGS' banding bird data for six relatively common species was used. Distribution models are constructed using Random Forest and MaxEnt. Random Forest classification of habitat and non-habitat provided a measure of DWT variable importance, which indicated that DWT is as important, and often more important, to model accuracy as temperature, precipitation, elevation, and an alternative wetland measure. MaxEnt models that included DWT in addition to traditional predictor variables had a considerable increase in classification accuracy. Also, MaxEnt models created with DWT often had higher accuracy when compared with models created with an alternative measure of wetland habitat. By comparing maps of predicted probability of occurrence and response curves, it is possible to explore how different species respond to water table depth and how a species responds in different seasons. The results of this analysis also illustrate that, as expected, all waterfowl species are tightly affiliated with shallow water table habitat. However, this study illustrates that the intensity of affiliation is not constant between seasons for a species, nor is it consistent between species.