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Articles 1 - 8 of 8
Full-Text Articles in Life Sciences
Ungrading: Reflections Through A Feminist Pedagogical Lens, Erin M. Eggleston, Shelby Kimmel
Ungrading: Reflections Through A Feminist Pedagogical Lens, Erin M. Eggleston, Shelby Kimmel
Feminist Pedagogy
Ungrading is a pedagogical approach in which no grades are given on any assignments. Instead, students are provided with many opportunities to submit work and gain feedback. The goal is to shift student focus from achieving a grade to growth as a learner and a person. As instructors, our ungrading approach utilized personalized learning plans, checkpoint reflections, and student-professor learning conferences to put agency in the hands of our students. We employed this method in upper-level biology and computer science courses and provide critical reflections here regarding our experiences and the connections between this approach and feminist STEM pedagogy tenets. …
Centering Equity In Stem Teaching: Stem Ideas That Change The World, Ileana Vasu
Centering Equity In Stem Teaching: Stem Ideas That Change The World, Ileana Vasu
Feminist Pedagogy
No discussion on equity/inequity makes sense without bringing power into that discussion. As instructors we need to ask questions such as “who decides and controls what knowledge is”, “whose identities are empowered and whose are erased”, “who has access and opportunity and who doesn’t”. Traditional teaching in STEM, including mathematics, assumes knowledge is objective, transmittable, repeatable to everyone. When educators follow a traditional curriculum, just like their teachers before them, they do so thinking their methods ensure equality and objectivity. These practices not only deny the role that Western patriarchal cultures have played in creating these so-called equitable practices, but …
Feminist Pedagogy In Stem: The Intersection Of Stem Pedagogy And Feminist Theory, Lesley-Ann Giddings, Candice R. Price
Feminist Pedagogy In Stem: The Intersection Of Stem Pedagogy And Feminist Theory, Lesley-Ann Giddings, Candice R. Price
Feminist Pedagogy
No abstract provided.
Fire Effects On Soil Organic Matter In The Creek Fire, Gracie E. Doolin
Fire Effects On Soil Organic Matter In The Creek Fire, Gracie E. Doolin
Master of Science in Environmental Sciences and Management Projects
Wildfires have increased in frequency and severity over the past few decades due to the increased concertation of CO2 emissions from anthropogenic influence. Soil carbon (C) sequestration has been identified as a climate change mitigation strategy; however, the influx of large-scale wildfires has accelerated landscape processes such as erosion, reducing soil aggradation, and soil C and nitrogen (N) protection. This trend is highlighted by the Creek Fire that occurred in September 2020 and burned 379,895 acres in the Sierra National Forest. This research is designed to close the knowledge gap regarding the impact of burn severity on soil organic matter …
Predicting Location And Training Effectiveness (Plate), Erik Rolf Bruenner
Predicting Location And Training Effectiveness (Plate), Erik Rolf Bruenner
Master's Theses
Abstract Predicting Location and Training Effectiveness (PLATE)
Erik Bruenner
Physical activity and exercise have been shown to have an enormous impact on many areas of human health and can reduce the risk of many chronic diseases. In order to better understand how exercise may affect the body, current kinesiology studies are designed to track human movements over large intervals of time. Procedures used in these studies provide a way for researchers to quantify an individual’s activity level over time, along with tracking various types of activities that individuals may engage in. Movement data of research subjects is often collected through …
Neural Tabula Rasa: Foundations For Realistic Memories And Learning, Patrick R. Perrine
Neural Tabula Rasa: Foundations For Realistic Memories And Learning, Patrick R. Perrine
Master's Theses
Understanding how neural systems perform memorization and inductive learning tasks are of key interest in the field of computational neuroscience. Similarly, inductive learning tasks are the focus within the field of machine learning, which has seen rapid growth and innovation utilizing feedforward neural networks. However, there have also been concerns regarding the precipitous nature of such efforts, specifically in the area of deep learning. As a result, we revisit the foundation of the artificial neural network to better incorporate current knowledge of the brain from computational neuroscience. More specifically, a random graph was chosen to model a neural system. This …
Analysis And Installation Of A Demonstration Agroforestry Orchard For Californian Mediterranean Plant Communities, Brandon Hurd
Analysis And Installation Of A Demonstration Agroforestry Orchard For Californian Mediterranean Plant Communities, Brandon Hurd
Master of Science in Environmental Sciences and Management Projects
Climate-appropriate agroforestry can provide low-input food security and ecosystem services for local Californian Mediterranean climates, while conserving natural resources (e.g., water, nitrogen, etc.). This project showcases a variety of agroforestry methods for five common plant communities of California and other analogous Mediterranean climates at the CAFES Experimental Farm on the campus of Cal Poly San Luis Obispo. Plant community species and their ethnobotanical uses were analyzed to mimic and incorporate aspects of native flora. Agricultural plants were also characterized to represent each of the five selected plant communities. GIS was used to assess the project site for soil, slope, and …
Psf Sampling In Fluorescence Image Deconvolution, Eric A. Inman
Psf Sampling In Fluorescence Image Deconvolution, Eric A. Inman
Master's Theses
All microscope imaging is largely affected by inherent resolution limitations because of out-of-focus light and diffraction effects. The traditional approach to restoring the image resolution is to use a deconvolution algorithm to “invert” the effect of convolving the volume with the point spread function. However, these algorithms fall short in several areas such as noise amplification and stopping criterion. In this paper, we try to reconstruct an explicit volumetric representation of the fluorescence density in the sample and fit a neural network to the target z-stack to properly minimize a reconstruction cost function for an optimal result. Additionally, we do …