PROFESSIONAL LEARNING COMMUNITIES: AN EXAMINATION OF TEACHERS’ PERSPECTIVES ON PROFESSIONAL CONVERSATIONS AND STUDENT LEARNING

Professional Learning Communities (PLCs) have emerged in the last 20 years as a popular professional development initiative. However, despite a wealth of PLC literature available, researchers have found that forming teacher communities does not automatically result in improved teaching practices that support student learning. This qualitative study was used to explore the ways in which humanities teachers perceive their work in existing PLCs. Specifically, it examined the ways teachers experience their work together related to subject knowledge, pedagogical knowledge, and the influence the work within the PLC has on changing instructional practices. Using an embedded unit case study design with each PLC representing a unit, data were gathered from a sample of 19 English, social studies, and world languages teachers who belonged to five PLCs that met regularly during the school day in a Connecticut high school. The researcher completed an interview with each teacher, the high school principal, and the high school assistant principals (n = 23) and each of the five PLCs were observed three times for the duration of a full meeting block (81 minutes). Interview transcripts, participant observations, and field notes were coded to allow themes to emerge within and across cases, triangulation of the data was essential for developing themes. The researcher concluded that although the feelings about peer collaboration in PLCs were positive, teachers believed their work was limited because they needed training in several areas. This was communicated through interviews and supported by observations that identified several areas of insufficiency. To increase the likelihood that the PLCs make an impact on improving teaching practices and student achievement, it is recommended that the district develop a shared vision about PLC work, increase the participation from school leaders around the PLC work, and provide teacher training on the use of data and on the dynamics of group discourse

Potential impacts of statewide relaxation of COVID-19 policies, the B.1.1.7 variant, and vaccination in Austin - March 2021

To support public health decision-making and healthcare planning, we developed a model for the five-county Austin-Round Rock Metropolitan Statistical Area (henceforth Austin​) that can provide real-time estimates of the prevalence and transmission rate of COVID-19 and project healthcare needs into the future. The model incorporates key epidemiological characteristics of the disease, demographic information for Austin, and local mobility data from anonymized cell phone traces. It uses daily COVID-19 hospitalization data to estimate the changing transmission rate and prevalence of disease. The framework can be readily applied to provide pandemic situational awareness and short-term healthcare projections in other cities around the US. In this report, we use COVID-19 hospitalization data for Austin from March 13, 2020 to March 5, 2021 to estimate the state of the pandemic in early March and project hospitalizations up to June of 2021.Integrative Biolog

Spatial distribution of COVID-19 infections and vaccinations in Austin, Texas

In this report, we estimate the spatial distribution of SARS-CoV-2 infections and vaccine administration across Austin, TX. We find marked geographic differences in these outcomes. In particular, ZIP codes on the western side of the city tend to have higher vaccine coverage and lower estimated cumulative infections than ZIP codes on the eastern side of the city. These differences mirror disparities in social vulnerability, as measured by the CDC's social vulnerability index (SVI), which tends to be higher in eastern ZIP codes than in western ZIP codes.Integrative Biolog

A Simple, Quick, and Precise Procedure for the Determination of Water in Organic Solvents

A procedure for the UV/VIS-spectroscopic determination of water by the use of a solvatochromic pyridiniumphenolate betaine is given. The water content of organic solvents is calculated by a two parameter equation from λmax of the dye. A typical, detection limit is of the order of 1 mg in 1 ml solvent for routine spectrometers. The parameters for the determination of water are given for a number of commonly used solvents

COVID-19 scenario projections for Austin, Texas - August 2021

To support public health decision-making and healthcare planning, we developed a model for the five-county Austin-Round Rock Metropolitan Statistical Area (henceforth Austin) that can provide real-time estimates of the prevalence and transmission rate of COVID-19 and project healthcare needs into the future. The model incorporates key epidemiological characteristics of the disease, demographic information for Austin, local vaccination estimates, and local mobility data from anonymized cell phone traces. It uses daily COVID-19 hospitalization data to estimate the changing transmission rate and prevalence of the disease. In this report, we use COVID-19 hospitalization data for Austin from March 13, 2020 to July 28, 2021 to estimate the state of the pandemic in the summer of 2021 and project hospitalizations through November of 2021.Integrative Biolog

Emergence of the B.1.1.7 SARS-CoV-2 variant at the University of Texas at Austin - March 5, 2021

Recent identification of the highly transmissible novel SARS-CoV-2 variant in the UK (B.1.1.7) has raised concerns for renewed pandemic surges around the globe [1]. While this variant has only recently been identified in the United States, it has been predicted to become dominant as early as March of 2021 [2]. Starting in January of 2021, the University of Texas at Austin (UT) began sequencing positive SARS-CoV-2 specimens to accelerate the detection of novel variants. An estimated 390 to 1,000 University of Texas at Austin (UT) students arrived in Austin infected with SARS-CoV-2 at the start of the spring semester (January 2021) [3]. Some of these cases may have been infected with novel variants [4,5]. Given that UT had confirmed via sequencing 22 cases of the B.1.1.7 variant among students as of March 5th, we conducted a rapid risk assessment to estimate the prevalence and future spread of the variant within the UT community.Integrative Biolog

Early introductions and projections of the B.1.1.7 SARS-CoV-2 variant at the University of Texas at Austin

Recent identification of the highly transmissible novel SARS-CoV-2 variant in the UK (B.1.1.7) has raised concerns for renewed pandemic surges around the globe [1]. While this variant has only recently been identified in the United States, it has been predicted to become dominant as early as March of 2021 [2]. Starting in January of 2021, the University of Texas at Austin (UT) began sequencing positive SARS-CoV-2 specimens to accelerate the detection of novel variants. An estimated 390 to 1,000 University of Texas at Austin (UT) students arrived in Austin infected with SARS-CoV-2 at the start of the spring semester (January 2021) [3]. Some of these cases may have been infected with novel variants [4,5]. Given that UT recently confirmed its first cases of the B.1.1.7 variant among students, we conducted a rapid risk assessment to estimate the prevalence and future spread of the variant within the UT community.Integrative Biolog