The Quality Schools Model Of Education Reform: A Description Of Knowledge Management Beliefs And Practices Using Baldrige In Education Criteria

Thesis (Ph.D.) University of Alaska Fairbanks, 2008This study used a concurrent nested mixed-methods approach to analyze the implementation of the Quality Schools Model of education reform through the lens of the seven Malcolm Baldrige Education criteria. Specifically, this study was an inquiry to determine the difference in beliefs and implementation related to knowledge constructs between and within groups of school staff based on professional role, years of education experience and years of experience working in the Quality Schools Model district. This research also used structural equation modeling to examine the fit between the Baldrige in Education theoretical model and actual practice of the Baldrige concepts in the context of rural Alaska school districts implementing the Quality Schools Model of comprehensive education reform. A 72-item questionnaire was used to measure beliefs about importance of concepts and perceptions of the concepts in practice. The questionnaire was administered to a convenience sample of 212 administrators, teachers, and classified staff in three rural Alaska school districts. Qualitative data was gathered through 14 semi-structured interviews with community members, elders, school board members, parents, and school staff. Results from the questionnaire data showed that job classification was the greatest predictor of mean responses. Administrators perceived knowledge activities were in practice to a greater degree than teachers. There were no significant differences in beliefs about importance or practice among participants based on years of education work experience or on experience in the current school district. The results showed ambivalence and sticky transfer in the street-level implementation of the QSM with significant large differences between belief and practice scores for all groups. A structural model of Baldrige in Education factors with leadership as the exogenous factor was created for the QSM. Results showed that leadership had a direct effect on knowledge management, and knowledge management had a direct effect on strategic planning, and an indirect effect on process management and the outcome variables of student, stakeholder and market focus, and results. There was no direct or indirect path between the knowledge factor and staff focus factor, leading to a recommendation to increase knowledge creation and sharing opportunities for that group

The Cost of Teacher Turnover in Alaska

Low teacher retention - high turnover - affects student learning. Teacher recruitment and retention are challenging issues in Alaska. Rates vary considerably from district to district and year to year, but between 2004 and 2014, district-level teacher turnover in rural Alaska averaged 20%, and about a dozen districts experienced annual turnover rates higher than 30%. High turnover rates in rural Alaska are often attributed to remoteness and a lack of amenities (including healthcare and transportation); teachers who move to these communities face additional challenges including finding adequate housing and adjusting to a new and unfamiliar culture and environment. Though urban districts have lower teacher turnover rates, they also have challenges with teacher recruitment and retention, particularly in hard-to-fill positions (such as special education and secondary mathematics) and in difficult-to-staff schools. Annually, Alaskan school districts hire about 1,000 teachers (500-600 are hired by its five largest districts), while Alaska’s teacher preparation programs graduate only around 200. The costs associated with teacher turnover in Alaska are considerable, but have never been systematically calculated,1 and this study emerged from interests among Alaska education researchers, policymakers, and stakeholders to better understand these costs. Using data collected from administrators in 37 of Alaska’s 54 districts, we describe teacher turnover and the costs associated with it in four key categories: separation, recruitment, hiring, and induction and training. Our calculations find that the total average cost of teacher turnover is $20,431.08 per teacher. Extrapolating this to Alaska’s 2008-2012 turnover data, this constitutes a cost to school districts of approximately$20 million per year. We focused on costs to Alaskan school districts, rather than costs to individual communities, schools, or the state. Our calculation is a conservative estimate, and reflects typical teacher turnover circumstances - retirement, leaving the profession, or moving to a new school district. We did not include unusual circumstances, such as mid-year departures or terminations. Our cost estimate includes costs of separation, recruitment, hiring, and orientation and training, and excludes the significant costs of teacher productivity and teacher preparation. We suggest that not all turnover is bad, nor are all turnover costs; and emphasize the need to focus on teacher retention as a goal, rather than reducing turnover costs. Even with conservative estimates, teacher turnover is a significant strain on districts’ personnel and resources, and in an era of shrinking budgets, teacher turnover diverts resources from teaching and learning to administrative processes of filling teacher vacancies. Our recommendations include: • Better track teacher turnover costs • Explore how to reduce teacher turnover costs • Support ongoing research around teacher turnover and its associated costs • Explore conditions driving high teacher turnover, and how to address themUniversity of Alaska FoundationExecutive Summary / Acknowledgements / Funding / Contact / What is teacher turnover? / What are the impacts of teacher turnover? / What factors are associated with teacher turnover? / What are the costs associated with teacher turnover? / Challenges in calculating turnover costs / Method / Analysis / Findings / Implications / Recommendations / Limitations / Conclusions / References / Appendix A: Detail costs of teacher turnover / Appendix B: Occupation codes & wages used for cost calculation

Sex on TV 2

Part of a series that examines the nature and extent of sexual messages conveyed on TV. Tracks changes that occur over time in the treatment of sexual topics, including references to possible risks or responsibilities. Based on a 1999-2000 program sample

Sex on TV 3

Part of a series that examines the nature and extent of sexual messages conveyed on TV. Tracks changes that occur over time in the treatment of sexual topics, including references to possible risks or responsibilities. Based on a 2001-2002 program sampl

Sex on TV: Content and Context

Part of a series that examines the nature and extent of sexual messages conveyed on American television. Focuses on references to contraception, safer sex, and waiting to have sex. Based on a sample of 1997-1998 programs

Sediment structure and physicochemical changes following tidal inundation at a large open coast managed realignment site

Managed realignment (MR) schemes are being implemented to compensate for the loss of intertidal saltmarsh habitats by breaching flood defences and inundating the formerly defended coastal hinterland. However, studies have shown that MR sites have lower biodiversity than anticipated, which has been linked with anoxia and poor drainage resulting from compaction and the collapse of sediment pore space caused by the site's former terrestrial land use. Despite this proposed link between biodiversity and soil structure, the evolution of the sediment sub-surface following site inundation has rarely been examined, particularly over the early stages of the terrestrial to marine or estuarine transition. This paper presents a novel combination of broad- and intensive-scale analysis of the sub-surface evolution of the Medmerry Managed Realignment Site (West Sussex, UK) in the three years following site inundation. Repeated broad-scale sediment physiochemical datasets are analysed to assess the early changes in the sediment subsurface and the preservation of the former terrestrial surface, comparing four locations of different former land uses. Additionally, for two of these locations, high-intensity 3D-computed X-ray microtomography and Itrax micro-X-ray fluorescence spectrometry analyses are presented. Results provide new data on differences in sediment properties and structure related to the former land use, indicating that increased agricultural activity leads to increased compaction and reduced porosity. The presence of anoxic conditions, indicative of poor hydrological connectivity between the terrestrial and post-inundation intertidal sediment facies, was only detected at one site. This site has experienced the highest rate of accretion over the terrestrial surface (ca. 7 cm over 36 months), suggesting that poor drainage is caused by the interaction (or lack of) between sediment facies rather than the former land use. This has significant implications for the design of future MR sites in terms of preparing sites, their anticipated evolution, and the delivery of ecosystem services

Unoccupied aerial systems temporal phenotyping and phenomic selection for maize breeding and genetics

Emerging tools in plant phenomics and high throughput field phenotyping are redefining possibilities for objective decision support in plant breeding and agronomy as well as discoveries in plant biology and the plant sciences. Unoccupied aerial systems (UAS, i.e. drones) have allowed inexpensive and rapid remote sensing for many genotypes throughout time in relevant field settings. UAS phenomics approaches have iterated rapidly, mimicking genomics progression over the last 30 years; the progression of UAS equipment parallels that of DNA-markers; while UAS analytics parallels progression from single marker linkage mapping to genomic selection. The TAMU maize breeding program first focused on using UAS to automate routine traits (plant height, plant population, etc.) comparing these to ground reference measurements. Finding success, we next focused on developing novel measurements impractical or impossible with manual collection such as plant growth and vegetation index curves. UAS plant growth curves measured in a genetic mapping populations has allowed discovery of temporal variation in quantitative trait loci (QTL). Now, phenomic selection approaches are being tested using temporal UAS, as first described using near infrared reflectance spectroscopy (NIRS) of grain. Phenomic selection is similar to genomic selection but uses a multitude of plant phenotypic measurements to identify relatedness and predict germplasm performance. Phenotypic measurements are thus treated as random markers with the underlying genetic or physiological cause remaining unknown. Using multiple extracted image features from multiple time points, genotype rankings have been successfully predicted for grain yield. Among the most exciting aspects have been identifying novel segregating physiological phenotypes important in prediction, which occur in growth stages earlier than previously evaluated. Similarly, UAS have allowed investigating plant responses to biotic and abiotic stress over time. UAS findings and approaches permit new fundamental plant biology and physiology research, which is catalyzing a new era in the plant sciences

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1-the summer 2015 and winter 2016 growing seasons-of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project's goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs

TNPO2 variants associate with human developmental delays, neurologic deficits, and dysmorphic features and alter TNPO2 activity in Drosophila

Transportin-2 (TNPO2) mediates multiple pathways including non-classical nucleocytoplasmic shuttling of >60 cargoes, such as developmental and neuronal proteins. We identified 15 individuals carrying de novo coding variants in TNPO2 who presented with global developmental delay (GDD), dysmorphic features, ophthalmologic abnormalities, and neurological features. To assess the nature of these variants, functional studies were performed in Drosophila. We found that fly dTnpo (orthologous to TNPO2) is expressed in a subset of neurons. dTnpo is critical for neuronal maintenance and function as downregulating dTnpo in mature neurons using RNAi disrupts neuronal activity and survival. Altering the activity and expression of dTnpo using mutant alleles or RNAi causes developmental defects, including eye and wing deformities and lethality. These effects are dosage dependent as more severe phenotypes are associated with stronger dTnpo loss. Interestingly, similar phenotypes are observed with dTnpo upregulation and ectopic expression of TNPO2, showing that loss and gain of Transportin activity causes developmental defects. Further, proband-associated variants can cause more or less severe developmental abnormalities compared to wild-type TNPO2 when ectopically expressed. The impact of the variants tested seems to correlate with their position within the protein. Specifically, those that fall within the RAN binding domain cause more severe toxicity and those in the acidic loop are less toxic. Variants within the cargo binding domain show tissue-dependent effects. In summary, dTnpo is an essential gene in flies during development and in neurons. Further, proband-associated de novo variants within TNPO2 disrupt the function of the encoded protein. Hence, TNPO2 variants are causative for neurodevelopmental abnormalities