This paper examines various ways Head Start has been measured across states. The contribution to the literature is to look at new variables, the role they play, and the contribution they make to measuring the effectiveness and enrollment numbers of Head Start Programs across states. / text

African American and Hispanic students and students from families with lower income are particularly at-risk for differential academic achievement and dropout. When students underachieve at school or dropout, they often face severe consequences such as increased risk of incarceration and unemployment. School social workers strive to prevent poor academic achievement and the associated negative outcomes. In recent years, federal and state education policy has focused on reducing disparities in academic achievement through the creation of policies that use high-stakes testing requirements to hold schools accountable for student learning. Research studies on teacher perceptions of high-stakes testing indicate that it is having a negative impact on their job tasks and on school systems. However, there are few studies that examine school social worker perceptions about the impact of high-stakes testing. This study examines school social workers’ perceptions about high-stakes testing. Specifically, it assesses school social worker perceptions about the impact of high-stakes testing on school systems and how school ratings and student performance might influence these perceptions. It also examines school social workers’ perceptions about the impact of high-stakes testing on their abilities to perform their work tasks. The study sample is drawn from respondents to the Texas School Social Work Survey (n=177). Data were analyzed through secondary data analysis using factor analysis and structural equation modeling (SEM). Findings indicate that school social workers perceive high-stakes testing as having a largely negative impact on school systems and their job tasks. School social workers who predominantly worked with students from ethnic minority backgrounds were more likely to have negative opinions about the impact of high-stakes testing on their job tasks. School social workers from schools with lower school ratings and those who felt that the students on their caseload tended to struggle on high-stakes tests had more negative perceptions about the impact of high-stakes testing on school systems. Results indicate the need for school social workers to become more involved in education policy and macro practice, to connect their services to improved academic outcomes for students, and to find new ways to provide school social work services in the “age of accountability.” / text

<p> Approximately 65,000 undocumented immigrants graduate from American high schools annually, among them valedictorians and salutatorians. Only about 6,500 of these prospective future leaders go on to college. There are 50 different state-level immigrant-tuition policies, most of which severely limit undocumented students&rsquo; college/university and financial aid options. This study is situated in the state of California, whose Master Plan for Higher Education aims to grant college access to all Californians and whose favorable immigrant-tuition policies work toward that end; it could serve as a model for U.S. states with restrictive or neutral immigrant-tuition policies. To date, there is limited discussion of undocumented student college choice in the higher education literature. To explore how undocumented students navigate college decision-making in the U.S., this study uses the conceptual constructs of Perna&rsquo;s (2006) contextual college choice model, Hossler and Gallagher&rsquo;s (1987) foundational choice model, and single-element models (chain enrollment and proximity). These frameworks and Dervin&rsquo;s Sense-making Theory (1999-2014) helped me retrospectively explore the college choice of seven undocumented men and women attending a Bay Area Cal State University campus in 2013. </p><p> The study&rsquo;s purpose warranted a qualitative research design and case study approach. I connected with interested students, shared my background, answered questions, and sent them my IRB-approved Study Information Sheet and demographic survey. We developed rapport over several months, engaging in a series of in-person interviews and other interactions. I kept field notes and journaled reflexively. I transcribed all 14 interview recordings via Dragon speech software, coded the transcripts and analyzed the data via MaxQDA data analysis software. </p><p> The findings revealed overarching themes related to: parental expectations and encouragement, habitus (e.g., gender &amp; cultural traditions, birth order &amp; responsibilities, home life), financial situation, K-14 context, higher education context, social context, and policy context. What distinguishes this study is the exploration of undocumented students&rsquo; college choice, inclusion of student voices, and implications for public policy and college enrollment professionals&rsquo; practice. It provides insight into how undocumented youth choose a college located in a state whose country values the common good and economic success yet is torn on its people&rsquo;s higher education rights.</p>

The focus of this research is to understand how different factors, such as state-level EE policies and institutional values, influence the inclusion of environmental education (EE) into pre-service teacher preparation programs. Institutional theory is the main theoretical foundation used for analyzing this issue. This is a mixed methods study with a sequential triangulation design (Morse 1991), using quantitative data from 50 states and 191 public universities to guide the selection process for seven qualitative interviews. While the impact of EE policies is evident, understanding the mechanisms that contribute to such things as political capital and how institutional value for EE is created is more nuanced. The findings from this research point to targeted EE policies, collaborative practices, and research on the development of institutional culture as strategies to bring EE in from the fringes of pre-service teacher preparation programs.

Institutions are the heuristic building blocks of human interactions, or the rules that humans use to structure interaction in the social world. Institutions are both universal, meaning that all people possess them and use them, and institutions are also ever-changing and evolving to adapt to new situations and social dilemmas. This literature review in this study demonstrates the need to use Institutional Analysis in the field of educational policy research, and then establishes groundwork of Institutional literature. The research questions ask whether institutions can be captured, and if so what the institutions of accountability policy are. Accountability policy, specifically the rating system established under ESEA Flexibility, serves as the policy though which institutions are examined because of its complexity and omnipresence in education today. The findings suggest that institutions can be captured and that educators and policymakers are engaged in an institutional clash.

Magistro darbe yra suformuluota Lietuvos švietimo sistemos politikos problema – nors švietimo kokybė yra nurodoma kaip vienas iš svarbiausių švietimo politikos prioritetų, nėra vieningo sutarimo, kas yra švietimo kokybė, kokiais kriterijais remiantis matuoti kokybę švietimo sistemoje. Atlikta Lietuvos Respublikos norminių aktų, kuriais vadovaujantis nustatomi švietimo sistemos prioritetai, analizė. Išanalizuoti įvairių Lietuvos ir užsienio autorių teoriniai ir praktiniai darbai, kuriais siekta patikslinti bendrojo lavinimo vidurinės mokyklos švietimo kokybės sampratą. Patvirtinama autorės suformuluota mokslinio darbo hipotezė, kad švietimo kokybei matuoti sukurta Valstybės švietimo stebėsenos rodiklių sistema nepakankamai apima bendrojo lavinimo mokyklos mokomuosius dalykus, be to, mokyklose vykdomas vidaus ir išorės auditas analizuoja mokyklą kaip atskirą švietimo sistemos vienetą, o abiejų tipų audito rezultatai neatsispindi Valstybės švietimo stebėsenos rodiklių sistemoje. Atsakydama į iškeltus tikslus, autorė formuluoja mokslinio darbo išvadas. Švietimo kokybė – tai visuma požymių, apibūdinančių švietimo įstaigą kaip sudėtinį švietimo sistemos vienetą, kurio kokybišką egzistavimą lemia mokomoji aplinka, mokymo priemonės, kvalifikuoti pedagogai, pamokinė ir popamokinė veikla, moksleivių pasiekimai, mokyklos bendruomenės (tėvų, mokinių, pedagogų ir visuomenės) tarpusavio santykiai, kuriems vertinti pasitelkiamas vidinis vertinimas (savianalizė) ir išorinis (ekspertinis)... [toliau žr. visą tekstą] / The following problem of Lithuanian education system policy is enunciated in the master thesis: although the quality of education is referred as one of the most important priorities in the education policy, there is no unanimous agreement about the quality of education itself and the criteria to measure it. The acts of Lithuanian Republic defining the priorities of education system were analyzed. On purpose to specify the conception of quality at secondary school education, the analysis of works by Lithuanian and foreign authors was performed. The hypothesis stated by the author in the study is confirmed. According to the author, the system of education monitoring indicators developed by the state to measure the quality of education is insufficient as far as the subjects at secondary school are concerned. Moreover, the school is analyzed as a separate unit of the education system while the internal and external audit is being accomplished there. Besides, the results of both the internal and external audit are not reflected in the state’s system of education monitoring indicators. According to objects the author proposed to herself, the inferences of the study are drawn. The quality of education is the whole of features, characterizing educational institution as the multiple unit of the education system which existence of quality is referred to teaching and learning environment, instructional aids, qualified educators, school and extra-curricular activities, the achievements... [to full text]

Using a quasi-experimental design, the author examined the effects of the Professional Development School Partnerships Deliver Success educational model on student academic achievement in science and mathematics in 12 high-needs, urban elementary, middle, and high schools in the southeastern United States. Student achievement was measured for first to eighth grade students by the State Criterion-Referenced Competency Test and for 11th-grade students by the State High School Graduation Test. 6 ANOVAs were used to compare baseline and year 1 performance data. Student ethnicity was used to disaggregate the data to investigate the extent, if any, to which achievement gaps narrowed. For the different ethnic groups, the small changes in proportion passing across the first year of implementation were not correlated with mean scale score changes as measured by Hedges’s g effect sizes. This result has national implications for the No Child Left Behind Act of 2001 policy in terms of reporting results. Three of the 6 ANOVAs showed significant change in achievement means for the PDS schools when using PDS school data only. However, when data from both PDS and matched comparison schools were analyzed, the overall results indicated no statistically significant gains in mathematics and science means for the professional development schools in relation to the comparison schools for the first year of professional development school implementation.

To investigate how federal discourse constructs adolescence, the author analyzed discussions of abstinence-only sexuality education from the U.S. Congressional Record from 2001 to 2007. He used grounded theory methodology to identify theoretical codes and construct a model from the data. The grounded theory developed focused on Congress’s maintenance of its role in mediating concern over the sexual behavior of adolescents as opposed to finding a solution to the problem it had identified. The author relates this theory to Foucault’s (1974/1991) concept of governmentality. He discusses Congress’s discourse about adolescence using Lesko’s (2001) confident characteristics of adolescence as a framework.

In the field of education, decisions are influenced by the results of various high stakes measures. Investigating the presence of differential item functioning (DIF) in a set of items ensures that results from these measures are valid. For example, if an item measuring math self-efficacy is identified as having DIF then this indicates that some other characteristic (e.g. gender) other than the latent trait of interest may be affecting an examinee’s score on that particular item. The use of hierarchical generalized linear modeling (HGLM) enables the modeling of items nested within examinees, with person-level predictors added at level-2 for DIF detection. Unlike traditional DIF detection methods that require a reference and focal group, HGLM allows the modeling of a continuous person-level predictor. This means that instead of dichotomizing a continuous variable associated with DIF into a focal and reference group, the continuous variable can be added at level-2. Further benefits of HGLM are discussed in this study. This study is an extension of work done by Williams and Beretvas (2006) where the use of HGLM with polytomous items (PHGLM) for detection of DIF was illustrated. In the Williams and Beretvas study, the PHGLM was compared with the generalized Mantel-Haenszel (GMH), for DIF detection and it was found that the two performed similarly. A Monte Carlo simulation study was conducted to evaluate HGLM’s power to detect DIF and its associated Type 1 error rates using the constrained form of Muraki’s Rating Scale Model (Muraki, 1990) as the generating model. The two methods were compared when DIF was associated with a continuous variable which was dichotomized for the GMH and used as a continuous person-level predictor with PHGLM. Of additional interest in this study was the comparison of HGLM’s performance with that of the GMH under a variety of DIF and sample size conditions. Results showed that sample size, sample size ratio and DIF magnitude substantially influenced the power performance for both GMH and HGLM. Furthermore, the power performance associated with the GMH was comparable to HGLM for conditions with large sample sizes. The mean performance for both DIF detection methods showed good Type I error control.

ABSTRACT A MONTE CARLO STUDY INVESTIGATING MISSING DATA, DIFFERENTIAL ITEM FUNCTIONING, AND EFFECT SIZE by Phyllis Garrett The use of polytomous items in assessments has increased over the years, and as a result, the validity of these assessments has been a concern. Differential item functioning (DIF) and missing data are two factors that may adversely affect assessment validity. Both factors have been studied separately, but DIF and missing data are likely to occur simultaneously in real assessment situations. This study investigated the Type I error and power of several DIF detection methods and methods of handling missing data for polytomous items generated under the partial credit model. The Type I error and power of the Mantel and ordinal logistic regression were compared using within-person mean substitution and multiple imputation when data were missing completely at random. In addition to assessing the Type I error and power of DIF detection methods and methods of handling missing data, this study also assessed the impact of missing data on the effect size measure associated with the Mantel, the standardized mean difference effect size measure, and ordinal logistic regression, the R-squared effect size measure. Results indicated that the performance of the Mantel and ordinal logistic regression depended on the percent of missing data in the data set, the magnitude of DIF, and the sample size ratio. The Type I error for both DIF detection methods varied based on the missing data method used to impute the missing data. Power to detect DIF increased as DIF magnitude increased, but there was a relative decrease in power as the percent of missing data increased. Additional findings indicated that the percent of missing data, DIF magnitude, and sample size ratio also influenced the effect size measures associated with the Mantel and ordinal logistic regression. The effect size values for both DIF detection methods generally increased as DIF magnitude increased, but as the percent of missing data increased, the effect size values decreased.