Abstract According to Wilkerson and Lang (2003, p.1) with approximately "90% of schools, colleges, and departments of education using portfolios of one form or another as decision-making tools for standards-based decisions regarding certification or licensure (as well as NCATE accreditation), it is appropriate to explore the legal and psychometric aspects of this assessment device." This study was conducted to examine how well the authentic assessments created in the Chalk and Wire ePortfolio initiative, which was created to provide authentic assessments of the Accomplished Practices, relate to the measures in the Professional Knowledge subtests on Florida Teacher Certification Examination. The sample was comprised of 294 graduating student teachers from a single department in the College of Education for the 2009/2010 school year at a large southern university. Multiple regression analyses were employed to examine the relationship between authentic assessments (i.e. critical tasks) in Chalk and Wire and performance on the subtests of the Professional Knowledge Test on the Florida Teacher Certification exam while controlling for gender, ethnicity and overall GPA. Only two of the independent variables were statistically significant from the 12 models examined. The scores from the Professional Knowledge subtests on Florida Teacher Certification Examination for Diversity (AP5) and Technology (AP12) were statistically different for gender, with females scoring higher than males on both. The results provided little evidence of concurrent validity between the authentic assessments of the Chalk and Wire ePortfolio initiative and the Professional Knowledge subtests on Florida Teacher Certification Examination.

The Adequate Yearly Progress (AYP) Model has been used to make many high-stakes decisions concerning schools, though it does not provide a complete assessment of student academic achievement and school effectiveness. To provide a clearer perspective, many states have implemented various Growth and Value Added Models, in addition to AYP. The purpose of this study was to examine two Value Added Model specifications, the Gain Score Model and the Layered Effects Model, to understand similarities and differences in school effect results. Specifically, this study correlated value added school effect estimates, which were derived from two model specifications and two outcome measures (mathematics and reading test scores). Existing data were obtained from a moderately large and rural school district in Florida. The outcome measures of 7,899 unique students were examined using the Gain Score Model and the Layered Effects Model to estimate school effects. Those school effect estimates were then used to calculate and examine the relationship between school rankings. Overall, the findings in this study indicated that the school effect estimates and school rankings were more sensitive to outcome measures than they were to model specifications. The mathematics and reading correlations from the Gain Score Model for school effects and school rankings were low (indicating high sensitivity), when advancing from Grades 4 to 5, and were moderate in other grades. The mathematics and reading correlations from the Layered Effects Model were low at Grade 5 for school effects and school rankings, as were the correlations at Grade 7 for the school rankings. In the other grades, correlations were moderate to high (indicating lower sensitivity). Correlations between the Gain Score Model and the Layered Effects Model from mathematics were high in each grade for both school effects and school rankings. Reading correlations were also high for each of the grades. These results were similar to the findings of previous school effects research and added to the limited body of literature. Depending upon the outcome measure used, school effects and rankings can vary significantly when using Value Added Models. These models have become a popular component in educational accountability systems, yet there is no one perfect model. If used, these models should be used cautiously, in addition to other accountability approaches.

Propensity score analysis has been used to minimize the selection bias in observational studies to identify causal relationships. A propensity score is an estimate of an individual's probability of being placed in a treatment group given a set of covariates. Propensity score analysis aims to use the estimate to create balanced groups, akin to a randomized experiment. This study used Monte Carlo methods to examine the appropriateness of using propensity score methods to achieve balance between groups on observed covariates and reproduce treatment effect estimates in multilevel studies. Specifically, this study examined the extent to which four different propensity score estimation models and three different propensity score conditioning methods produced balanced samples and reproduced the treatment effects with clustered data. One single-level logistic model and three multilevel models were investigated. Conditioning methods included: (a) covariance adjustment, (b) matching, and (c) stratification. Design factors investigated included: (a) level-1sample size, (b) level-2 sample size, (c) level-1 covariate relationship to treatment, (d) level-2 covariate relationship to treatment, (e) level-1 covariate relationship to outcome, (f) level-2 covariate relationship to outcome, and (g) population effect size. The results of this study suggest the degree to which propensity score analyses are able to create balanced groups and reproduce treatment effect estimates with clustered data is largely dependent upon the propensity score estimation model and conditioning method selected. Overall, the single-level logistic and random intercepts models fared slightly better than the more complex multilevel models while covariance adjustment and matching methods tended to be more stable in terms of balancing groups than stratification. Additionally, the results indicate propensity score analysis should not be conducted with small samples. Finally, this study did not identify an estimation model or conditioning method that was consistently able to create adequately balanced groups and reproduce treatment effect estimates.

In this descriptive study, I researched five elementary general education teachers' reading assessment practices as they worked within the context of IDEA (2004), NCLB (2002) and Response to Intervention (RTI). My own connection to the classroom and reading assessment practices brought me to this research. I presented my personal and professional connection through vignettes about my own classroom assessment practices. Relevant literature on both the context and culture of assessment were pertinent to this research. I used a qualitative design, specifically, Colaizzi's (1978) method of phenomenological analysis. Data were three in-depth phenomenological interviews, relevant documents and artifacts, and use of a researcher reflective blog. I summarized the initial findings of this research through 10 clustered themes; shift of focus, ever changing accountability, independent efforts with data, collaborative efforts with data, working environment, interventions and reading assessment practices in action, authenticity in practice, lack of decision making power, teacher emotion, and teacher needs and wants and a composite narrative in order to describe the lived experience of these teachers reading assessment practices. Implications from my research with regard to policy include a perceived incongruence between an RTI framework and the teacher evaluation system with regard to active collaboration. Those toward practice include difficulty with the day-to-day implementation of an RTI framework and the perception of a singular focus of RTI as disability determination. My recommendations for future research include an action research agenda designed to explore increased involvement of stakeholders such as students, parents and other school personnel.

Nursing workforce competency in informatics is crucial to providing safe patient care, improving quality, and reducing healthcare costs. Assurance of informatics competency in a workforce with increasingly diverse educational preparations, demographics, and informatics skills poses significant challenges. The question addressed was the lack of nursing informatics competency assessment tool relevant to bedside nursing. The purpose of this project was to develop and review a new nursing informatics competency assessment tool designed to address the individual educational needs of newly hired nurses. The tool was designed to measure nurses' competency in computer literacy, informatics literacy, and informatics management skills recommended in the American Nurses Association's Standards and Scope of Practice and Technology Informatics Guiding Education Reform. This tool supports practices at the bedside by providing individualized education according to the results of a self-assessment. The project was guided by the Benner's model and the Rosswurm and Larrabee framework. Content validity was established by item analysis, relevancy scale, and validation by the identified experts from the organization's Nursing Informatics Department (n = 4); the Department of Education, Practice, and Research (n =8); the Clinical Outcomes Department (n = 1); and bedside nurses (n = 14). The administration recommended this tool be incorporated into its strategic plan. This project promoted positive social change by developing a tool to assess informatics competencies in newly hired nurses and guide educators in developing future educational strategies. These efforts will assist in creating a workforce that is prepared to deliver healthcare safely, efficiently, and cost-effectively in the increasingly technology-savvy environment of U.S. healthcare in the 21st century.

This dissertation focuses on how rural community college students make decisions regarding their post-secondary plans. To understand these decision processes, I interviewed students, faculty and administrators at Southeast Community and Technical College in Harlan County, Kentucky. The literature informing my research reflects on rural college going patterns. Most studies connect place and post-secondary plans. Central Appalachia has among the lowest population percentages with Bachelor degrees in the country. Studies argue this is because of limited application for such degrees in the region. Matching their education and training to local job market requirements, people hesitate to complete advanced degrees when little if any local application requires such additional education. This study discusses how place informs and shapes students’ decisions around college and degree selection. Unlike those who connect advanced education with outmigration patterns, my research highlights students who pursue post-secondary training in hopes of applying these degrees locally to build their communities and families’ quality of life in a rural place. From the twenty-eight student and fifteen faculty and administrator interviews conducted, rationales regarding the purpose of post-secondary degrees and training surfaced. Through selected follow up oral histories, students further described the application of their degrees towards terminal, transfer and/or transformative ends. Their articulated positions regarding the purpose and application of higher education in Central Appalachia adds to the continuing studies on how advanced degrees informs students’ decisions to stay or leave rural areas. From the Southeast interview data, I provide a critique of policy directives related to advanced education and economic development. Given many of the urban assumptions embedded in development theory, my study was interested in how these rural students, in a place considered underdeveloped partly because of low college attendance rates, attain and then apply their degrees and the rationale they articulate in doing so. As US policy makers continue to require advanced education for more and more of their citizens, my research shows the complications and complexities such rhetoric evokes when people, committed to rural places and ways of life, apply them in their local contexts.

Intercollegiate athletics in the United States have continuously become more commercialized, pressuring athletics departments and coaches to produce winning teams. The commanding expectations for successful programs have been thought to take away from the academic mission of colleges and universities, focusing efforts on athletics over academics. This phenomenon has been examined, but the role head coaches play in support of student-athlete academics has yet to be explored. The purpose of this study is to measure student-athlete perception of academic support from Division I head coaches. Current literature demonstrates the strong influence of coaches on student-athletes, but the effect in the area of academics is unknown. Therefore, the research presented aims to evaluate the connection between student-athletes and the academic support of head coaches.

This study was designed to explore the possible connections between student peer relationships and individual students’ roles in a network as it pertained to outcomes such as self-reported academic achievement and personal satisfaction with the first year of college. The research question directing this inquiry is: How does a student’s role within a residential community of peers relate to success in college? Social network analysis was employed for examination of individual engagement within the context of a larger community. The vast learning community literature tells an interesting story: 1.) a history of co-curricular peer learning environments, 2) a tradition of research intended to assess the value of these programs, 3) a body of literature that provides theoretical explanations for why learning communities should work. The gap in the literature is found regarding what happens within the communities. To learn how individuals within community learn from one another, community of practice was utilized as a framework in this mixed-methods approach to examine the influence of relationships, and exchange, acquisition, & development of social capital within a living learning community While this network study indicated that popularity, relational ties to staff, and being someone sought-after for advice were not statistically significant predictors of higher GPA, the network analyses confirmed strong network density, cohesion, and proper structure for ideal capital flow. The results of this study confirm that this community is effective in establishing familiarity and even more so, providing an environment that fosters friendships among participants and staff. Furthermore, students developed the ability to construct knowledge alongside their peers. Given the density and relation-rich nature of this community, this positive environment is able to foster more complex and self-authored levels of meaning-making for the students involved. Building this scaffolding facilitated student development, which effectively created a student transformation from dependence on external authority to self-authorship. This study confirmed that the primary goals of a learning community have been met: a group of strangers developed into a network of friends who reap social and academic benefits by virtue of being together in a shared and successful living learning community environment.

Setting performance standards is a judgmental process involving human opinions and values as well as technical and empirical considerations and although all cut score decisions are by nature arbitrary, they should not be capricious. Establishing a minimum passing standard is the technical expression of a policy decision and the information gained through standard setting studies inform these policy decisions. To this end, it is necessary to conduct robust examinations of methods and techniques commonly applied to standard setting studies in order to better understand issues that may influence policy decisions. The modified-Angoff method remains one of the most popular methods for setting performance standards in testing and assessment. With this method, is common practice to provide content experts with feedback regarding the item difficulties; however, it is unclear how this feedback affects the ratings and recommendations of content experts. Recent research seems to indicate mixed results, noting that the feedback given to raters may or may not alter their judgments depending on the type of data provided, when the data was provided, and how raters collaborated within groups and between groups. This research seeks to examine issues related to the effects of item-level feedback on the judgment of raters. The results suggest that the most important factor related to item-level feedback is whether or not a Subject Matter Expert (SME) was able to correctly answer a question. If so, then the SMEs tended to rely on their own inherent sense of item difficulty rather than the data provided, in spite of empirical evidence to the contrary. The results of this research may hold implications for how standard setting studies are conducted with regard to the difficulty and ordering of items, the ability level of content experts invited to participate in these studies, and the types of feedback provided.

Of the many potential and espoused outcomes of higher education, it was satisfaction that rose to prominence for Alexander Astin, stating, “it is difficult to argue that student satisfaction can be legitimately subordinated to any other education outcome” (1993, p. 273). This high endorsement of the construct of satisfaction is backed by a plethora of arguments of its importance for college and university decision makers. A thorough and accurate rendering of student satisfaction measurement is requisite. To calculate student satisfaction as the magnitude of item endorsement leaves a measure that is sample specific. The goal of a universal and unidimensional measure is only advanced by determining which items do or do not contribute to a model of linearity and unidimensionality. This research utilizes the Rasch model to advance exploration of the variable of student satisfaction. Using data collected from the Noel-Levitz Student Satisfaction Inventory, analysis was conducted to determine if reported ascribed importance and experienced satisfaction adhered to the assumption of the Rasch model. Results suggest that student satisfaction and ascribed importance do adhere to these assumptions of measurement, but only after ordinal rankings of dissatisfaction are collapsed into a single entity. The determined separation of satisfaction and dissatisfaction likens Herzberg’s Motivation-Hygiene Theory. Additional discussion and implications focus on contrasting analysis when applying the Rasch analysis relative to classical test theory, recommendations of modified instrument scaling to better capture the construct, implications for higher education, and heightened understanding of student satisfaction as a whole.