Public school administrators' knowledge of special education law

The purpose of this study was to assess the knowledge of public school administrators with respect to special education (ESE) law. The study used a sample of 220 public school administrators. A survey instrument was developed consisting of 19 demographic questions and 20 situational scenarios. The scenarios were based on ESE issues of discipline, due process (including IEP procedures), identification, evaluation, placement, and related services. The participants had to decide whether a violation of the ESE child's rights had occurred by marking: (a) Yes, (b) No, or (c) Undecided. An analysis of the scores and demographic information was done using a two-way analysis of variance, chi-square, and crosstabs after a 77% survey response rate.^ Research questions addressed the administrators' overall level of knowledge. Comparisons were made between principals and assistant principals and differences between the levels of schooling. Exploratory questions were concerned with ESE issues deemed problematic by administrators, effects of demographic variables on survey scores, and the listing of resources utilized by administrators to access ESE information.^ The study revealed: (a) a significant difference was found when comparing the number of ESE courses taken and the score on the survey, (b) the top five resources of ESE information were the region office, school ESE department chairs, ESE teachers, county workshops, and county inservices, (c) problematic areas included discipline, evaluation procedures, placement issues, and IEP due process concerns, (d) administrators as a group did not exhibit a satisfactory knowledge of ESE law with a mean score of 12 correct and 74% of responding administrators scoring in the unsatisfactory level (below 70%), (e) across school levels, elementary administrators scored significantly higher than high school administrators, and (f) a significant implication that assistant principals consistently scored higher than principals on each scenario with a significant difference at the high school level.^ The study reveals a vital need for administrators to receive additional preparation in order to possess a basic understanding of ESE school law and how it impacts their respective schools and school districts so that they might meet professional obligations and protect the rights of all individuals involved. Recommendations for this additional administrative preparation and further research topics were discussed. ^

Application of intervention analysis to evaluate the impacts of special events on freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

Community Development Districts: The entrepreneurial side of government

In an effort to reduce the cost and size of government public service delivery has become more decentralized, flexible and responsive. Public entrepreneurship entailed, among other things, the establishment of special-purpose governments to finance public services and carry out development projects. Community Development Districts (CDDs) are a type of special-purpose governments whose purpose is to manage and finance infrastructure improvements in the State of Florida. They have important implications for the way both growth management and service delivery occur in the United States. This study examined the role of CDDs for growth management policy and service delivery by analyzing the CDD profile and activity, the contribution of CDDs to the growth management and infrastructure development as well as the way CDD perceived pluses and minuses impact service delivery. The study used a mixed methods research approach, drawing on secondary data pertaining to CDD features and activity, semi-structured interviews with CDD representatives and public officials as well as on a survey of public officials within the counties and cities that have established CDDs. Findings indicated that the CDD institutional model is both a policy and a service delivery tool for infrastructure provision that can be adopted by states across the United States. Results showed that CDDs inhibit rather than foster growth management through their location choices, type and pattern of development. CDDs contributed to the infrastructure development in Florida by providing basic infrastructure services for the development they supported and by building and dedicating facilities to general-purpose governments. Districts were found to be both funding mechanisms and management tools for infrastructure services. The study also pointed to the fact that specialized governance is more responsive and more flexible but less effective than general-purpose governance when delivering services. CDDs were perceived as being favorable for developers and residents and not as favorable for general-purpose governments. Overall results indicated that the CDD is a flexible institutional mechanism for infrastructure delivery which has both advantages and disadvantages. Decision-makers should balance districts’ institutional flexibility with their unintended consequences for growth management when considering urban public policies.

A comprehensive assessment of self -report experiences of adoptive parents of special needs children in Florida

Adoption of special needs children is now seen as a life long event whereby the adoptive child and family have unique needs. The need for postplacement resources throughout the life cycle of the adoption process is evident. This exploratory-descriptive research employed a random stratified cross-sectional design. The purpose of the study was to describe, identify, examine, and assess the relative influence of identified empirically and conceptually relevant variables of self-report experiences of adoptive parents of special needs children. Primary areas of exploration included: (1) adoptive children and families' characteristics, (2) postplacement service needs, utilization and satisfaction, and (3) adoptive parents' perceptions of their adoption experiences. A proportionate stratified random mail survey was used to obtain 474 families who had adopted special needs children from the 15 geographic districts which make up the state adoption social service agency in Florida. A 144-item survey questionnaire was used to collect basic information on demographic data, service provision, and adoption experiences. Four research questions were analyzed to test the effect the predictor variables had on willingness to adopt another special needs child, successful adoption, satisfying experience, and realism about problems. All four research questions revealed that the full model and the child's antecedent and the adoptive parents' intervening variable blocks were significant in explaining the variance in the dependent variables. The child's intervening variables alone were only significant in explaining the variance for one of the dependent variables. The results of the statistical analysis on the fifth research question and the three hypotheses determined that (1) only one postplacement service, crisis intervention, had a statistically significant impact on the adoptive parents' perceived level of satisfaction with the adoption experience; (2) adoptive parents who rate their adoption as successful are more likely to express a desire to adopt another special needs child; (3) the more adequate information on the child the adoptive parents perceived that they had prior to placement, the more they perceived they were realistic about the problems they would encounter; and (4) six specific postplacement services were found to be significant in predicting successful adoptions--crisis intervention, outpatient drug/alcohol treatment, maintenance subsidy, physical therapy, special medical equipment, and family counseling. Implications for the social work field and future research are discussed. ^

Application of Intervention Analysis to Evaluate the Impacts of Special Events on Freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.