In 1991 EPA embraced the watershed protection approach for environmental management. EPA defines watershed protection as â a strategy for effectively protecting and restoring aquatic ecosystems and protecting human health.â To encourage statewide watershed protection, EPA developed the “Statewide Watershed Protection Approach” document, which is designed to aid states in developing their own watershed protection program. The watershed protection approach is not a program or policy required by EPA, rather a flexible framework that outlines the essential elements and components of a comprehensive statewide watershed protection approach. It allows for varying conditions in a state, but attempts to ensure a consistent general approach. This paper describes the elements and components of EPA’s comprehensive statewide watershed protection framework. It then analyzes Washington, Minnesota, and Oregon’s statewide watershed protection programs, and examines how these state approaches reflect EPA's framework. In addition, the paper analyzes a case study in each of these states to explore how these statewide watershed management approaches are implemented at the local level. By analyzing states that have successfully implemented a statewide watershed protection approach, this paper aims to identify the critical elements in a statewide watershed protection approach, and identify the issues that are critical to successful local implementation. / Master of Urban and Regional Planning

This dissertation includes three different topics concerning the political business cycles in developed countries. In the first section, we use annual data for 48 states from 1951 to 2004 by the method of instrumental variables estimation. We find that the partisan theory created in statewide via two channels including the partisanship effect which include the interactive relationships between president and governors or among governors, and the partisan ideology including the policy preferences are both potential shocks to a real business cycle. Next, we investigate the theory of partisan cycles using panel cointegration and fully modified OLS techniques based on the same data as earlier. We propose the long-run co-movement and the causal relationships between partisan target and cycle variables. Meanwhile, the panel error correction model shows evidence of long-run unidirectional causality running from partisan variables to target variables. This shows that, in the long run, statewide economic performance must be directly based on politicians¡¦ concerns for policies and outcomes, as well as on exhibiting strong ideological differences in those preferences across parties in the United States. Overall, we contribute an essential reference to the voters. Finally, a new government popularity index (GPI) is constructed and using variables that include real GDP, industrial production, the unemployment rate and the inflation rate as measures of bilateral activity correlation beginning in 1981Q1 and ending in 2005Q4 for 15 European countries. The estimation procedure is developed by rolling the correlation of bilateral activity every twenty quarters and running it on partisan variables, namely, as a kind of government popularity index and the difference between partisan ideologies combined with traditional bilateral trade intensity variables. Overall, a strong and striking empirical finding is uncovered: countries with closer popular governments, incumbent ideologies as well as trade links, tend to have more closely correlated business cycles.

Census data indicates people with higher levels of education are leaving Appalachian Kentucky as they do in other rural areas. Aside from anecdotal information and primarily qualitative community studies, there is little quantitative evidence of the factors which may influence these migration decisions. State policies and regional efforts to increase educational attainment of people in the region have focused on producing more college degrees however may be contributing to the out-migration of those with higher levels of education. The study incorporates community level data with demographic, academic, and employment data from a cohort of 2005-06 college graduates from Appalachian Kentucky. The study includes an analysis of migration rates for a variety of different types of graduates and a set of three complimentary logistic regression models developed to understand the impact of individual demographic and academic factors, factors about the communities where these graduates came from, and the factors related to the communities where they went after completing their degrees and credentials to predict likelihood of migrating. This study builds upon previous efforts by providing extensive, externally validated data about a large population of individuals. It leverages sociological, demographic, and neoclassical microeconomic research methods and leverages data from Kentucky's statewide longitudinal data system to serve as an illustration for how these systems can be used for complex statistical analyses.

An accelerated growth in the volume of freight shipped on Florida's highways has led to a significant increase in truck traffic, influencing traffic operations, safety, and the state of repair of highway infrastructure. Traffic congestion in turn has impeded the speed and reliability of freight movement on the highway system. Appropriate planning and decision making processes are necessary to address these issues. However, a main challenge in establishing such processes is the lack of adequate data on statewide freight movements. As traditional data sources on freight movement are either inadequate or no longer available, new sources of data must be investigated. A recently available source of data on nationwide freight flows is based on a joint venture by the American Transportation Research Institute (ATRI) and the Federal Highway Administration (FHWA) to develop and test a national system for monitoring freight performance measures on key corridors in the nation. This data is obtained from trucking companies who use GPS-based technologies to remotely monitor their trucks. The database contains GPS traces of a large number of trucks as they traveled through the national highway system. This provides unprecedented amounts of data on freight truck movements throughout the nation (and in Florida). Such truck GPS data can potentially be used to support planning, operation, and management processes associated with freight movements. Further, the data can be put to better use when used in conjunction with other freight data obtained from other sources. The overarching goal of this thesis is to investigate the use of large streams of truck-GPS data from the American Transportation Research Institute (ATRI) for the estimation of statewide freight truck flows in Florida. To this end, first, an algorithm was devised to convert large streams of raw GPS data into a database of truck trips. The algorithm was applied to four months of ATRI's truck-GPS data comprising over 145 Million GPS records to derive a database of more than 1.2 million truck trips starting and/or ending in Florida. This database was used to analyze truck travel characteristics and origin-destination truck flow patterns for different geographical regions in Florida. The resulting database was used in conjunction with the GPS data to analyze the extent to which ATRI's data represents observed truck traffic flows in the state. It was found that at an aggregate level, almost 10% of heavy truck traffic flows in Florida is captured in the ATRI data. Finally, the database of truck trips derived from ATRI's truck-GPS data was combined with observed heavy truck traffic volumes at different locations within and outside Florida to derive an origin-destination (OD) table of truck flows within, into, and out of the state. To this end, first, the truck trip database developed from ATRI's truck-GPS data was converted into a seed OD table at the TAZ-level spatial resolution used in FLSWM. Subsequently, a mathematical procedure called origin-destination matrix estimation (ODME) method was employed to combine the OD flow table generated from the ATRI data with observed truck traffic volume information at different locations within and outside Florida. The OD table of truck flows estimated from this procedure can be used for a variety of purposes, including the calibration and validation of the heavy truck modeling components of FLSWM.

This study examined the long-term predictive validity of four reading fluency measures on a statewide reading assessment. The reading fluency measures were administered to a group of first and second grade students and their utility for predicting outcomes on a state's reading assessment in third grade was examined. Specifically, the amount of variance accounted for on the outcome assessment by Curriculum-Based Measurement - Reading (R-CBM) probes from two sources, a list fluency measure, and a group measure of fluency was investigated. The extent to which each is an accurate predictor of long-term performance when considered individually and in combination with the other measures was included in the analyses, along with an examination of whether a difference exists in the obtained prediction between grade levels.

The nature of the decision-making processes and the resulting changes made in school programs and curricula in Indiana elementary schools was the focus of this research. The changes were required of these schools by the State of Indiana through the Performance-Based Accreditation division of the Indiana Department of Education. These schools were expected to make changes because they had performed below standard on the math portion of ISTEP+, the State standardized assessment test, during the 1997-98 school year. The objective of the study was to examine the perceptions of the participants as to the influence that mediating factors had on their schools' decision-making processes.The survey population consisted of principals and teachers from 18 Indiana elementary schools from accreditation group IV. In the 18 schools surveyed, 14 principals (78%) and 182 teachers (50%) responded. The participants were grouped as principals and teachers, and were organized for data analysis by location of their respective schools. Two of the schools were urban, seven suburban and nine were rural. The purpose of the study was to explore the decision-making processes used at these elementary schools. Little is known about these decision-making processes in schools that are faced with the requirement to make changes as the result of low test scores. Data gathered in the study included the types of changes and the factors influencing the change-related decisions. Through analysis of the data, the researcher attempted to gain insights that could be used to assist educators in future efforts relating to change and decision-making.Findings of the study indicated that schools primarily used new textbooks to address new approaches to the math curriculum and remediation programs or test skills programs to focus more specifically on improving test scores. The principals and teachers generally felt the decision-making processes in their schools were very collaborative; however, while teachers perceived those processes to be collaborative, their perception reflected a lesser degree of collaboration than the principals. Concern on the part of the teachers and principals for student learning and the school systems' accountability to the Preformance-Based Accreditation program were perceived as the factors having the greatest influence on the decisions to improve math performance. Clearly, these professionals felt the need to change; however, findings indicated that these changes were motivated in part by professionalism and, in part, by the pressures of accountability to the State.Recommendations for further study were included. / Department of Educational Leadership

The focus of this study was to assess the ability to predict performance on the Indiana Statewide Test for Educational Progress (ISTEP) from oral reading fluency scores on the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) Oral Reading Fluency Test (ORF). The scores of both assessments from 306 Indiana students from four different elementary schools were examined. Results of these students’ end of year (EOY) ORF scores were compared to their ISTEP scores in third grade in 2008-2009. During that school year ISTEP was administered twice, once in the Fall and once in the Spring. Results from both tests were analyzed using linear, multiple, and logistic regression models. The results showed r values between the ORF scores and the English/Language Arts portion of ISTEP to be .76 (Fall) and .72 (Spring). The correlations between ORF and ISTEP Math were .54 (Fall) and .61 (Spring). Regression coefficients ranged from 1.30 – 1.13 indicating a positive linear relationship between the results of the two assessments. The scores from demographic subgroups were also examined and some differences in the strength of the relationships were found among the groups. The oral reading fluency test was a better predictor for students generally considered at-risk (non-white, disabled, and non-English speaking). Logistic regression results showed a moderate to strong ability to predict whether or not students would pass ISTEP based on DIBELS scores. After using Beta values to calculate probabilities, it was found a DIBELS ORF score of 100 would provide a strong probability a student would pass ISTEP, both in English/Language Arts and Math. The results imply the need to monitor students’ oral reading and provide timely interventions when they struggle, and to focus more on helping children learn to read and less on preparing for ISTEP. / Department of Educational Leadership

Department of Educational Leadership

xiii, 92 p. : ill. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / In recent years, state and national policy created the need for higher accountability standards for student academic performance. This increased accountability creates an imperative to have a formative assessment system reflecting validity in inferences about the effectiveness of instruction and performance on statewide large-scale assessments. Curriculum-based measurement (CBM) satisfies both functions. However, research shows the predictive power of oral passage reading fluency (PRF) diminishes in middle and high school. Because of the decreased predictive validity of PRF in the upper grade levels, additional reading CBMs should be explored. This study compares PRF and Vocabulary CBM data for all sixth grade students in a school district using two statistical procedures: correlation and regression. The correlation coefficients were moderately high among PRF, Vocabulary CBM, and the Reading test in Oregon Assessment of Knowledge and Skills (OAKS). A regression analysis indicated that the Vocabulary CBM explained more variance than PRF in predicting reading performance on OAKS. A second multiple regression analysis introduced three non-performance indicators (Gender, Attendance, and NCLB At-Risk), along with the two CBMs (Vocabulary and PRF). The second regression results revealed that Vocabulary again was more predictive than PRF, Gender, Attendance, or NCLB At-Risk. At-Risk status was the only non-performance indicator that was significant. All the findings have been discussed within the context of understanding reading skills using CBMs and their relation to performance on a large-scale test used for accountability. The findings have been framed as part of an information system that allows schools and districts to better tailor staffing, instruction, and schedules to student needs. Suggestions for future research also have been discussed, particularly in enhancing the predictions on large-scale test outcomes using a variety of CBMs. / Committee in charge: Gerald Tindal, Chairperson, Educational Methodology, Policy, and Leadership; Paul Yovanoff, Member, Educational Methodology, Policy, and Leadership; Keith Hollenbeck, Member, Educational Methodology, Policy, and Leadership; Jean Stockard, Outside Member, Planning Public Policy & Mgmt

This study examined the relation and predictive validity of the three seventh-grade reading curriculum-based measurements (CBMs), (a) passage reading fluency, (b) vocabulary, and (c) comprehension, on student performance on the Oregon Assessment of Knowledge and Skills Reading (OAKS-R). This question was examined using extant data collected from 857 seventh-grade students in a Pacific Northwest school district during spring quarter. Of the total sample of 857, only 557 students' records were analyzed: 499 general education students and 58 students with learning disabilities who met the a priori participation criteria of having scores on all three spring easyCBM Reading measures (PRF, VOC and MCRC) and an OAKS-R score. Correlational analysis revealed different outcomes for the two groups. For the general education population, the highest correlation coefficient was between CBM vocabulary and OAKS-R (r = .65). Follow-up regression analysis also indicated that CBM Vocabulary (&beta = .44) was the best predictor for students in the general education population. However, for students with learning disabilities, CBM comprehension was the most strongly correlated to OAKS-R (r = .60), and regression analysis showed comprehension (&beta = .40) as the best predictor of students' OAKS-R performance. When specific nonacademic variables were added to the regression model for general education, CBM vocabulary (&beta = .41) and CBM comprehension (&beta = .43) were still the best predictors for students in general education and students with learning disabilities, respectively. Practical implications of the predictive validity of the CBM reading measures for practitioners are discussed in relation to assessment, instruction, and resource allocations. Finally, suggestions for future research in the areas of improving CBM utility as a predictor of success on statewide assessments in reading at the middle school level are discussed.