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Social Justice Mathematics: Classroom Practices That Give Students Rigor While Building Agency, Emily Marquise
Social Justice Mathematics: Classroom Practices That Give Students Rigor While Building Agency, Emily Marquise
Masters Theses
The purpose of this study is to examine the impact of a social justice approach to mathematics instruction. While many students have math aversion, students in low socioeconomic communities exhibit this to a higher degree putting them at a disadvantage as they progress through their educational career. More than 3.4 million K-12 students in the United States come from families that earn less than the median income yet achieve scores in the top percentile (Wyner et al., 2007). This raises the question of why so many students in low-socioeconomic settings are not given rigorous content that will keep them competitive …
Targeting Macrophytes: Increased Water Quality Through Optimized Vegetation Considerations For Constructed Wetlands, Austin Mcbrady
Targeting Macrophytes: Increased Water Quality Through Optimized Vegetation Considerations For Constructed Wetlands, Austin Mcbrady
Masters Theses
This study of constructed wetland design investigated relationships between macrophyte species selection and planting density for water quality improvement. A lab-scale wetland was compared against a pilot-scale wetland in San Antonio, Texas at Mitchell Lake to measure differences in effluent water quality improvement using three native macrophyte species. Using a novel, two-phase method, a targeting macrophyte was identified from among other species based on its marked capability for improving water quality factors, then was planted in varied majority densities to compare differences in treatment effectiveness. The results of this study showed that this complimentary approach to wetland design displayed significant …
Detecting Ai Generated Text Using Neural Networks, Jesus Guerrero
Detecting Ai Generated Text Using Neural Networks, Jesus Guerrero
Masters Theses
For humans, distinguishing machine generated text from human written text is men- tally taxing and slow. NLP models have been created to do this more effectively and faster. But, what if some adversarial changes have been added to the machine generated text? This thesis discusses this issue and text detectors in general.
The primary goal of this thesis is to describe the current state of text detectors in research and to discuss a key adversarial issue in modern NLP transformers. To describe the current state of text detectors a Systematic Literature Review was done on 50 relevant papers to machine-centric …