Your search found 13 results.

Descriptors:
Rural Schools; Mathematics Achievement; Teacher Surveys; Grade 9; Algebra; Blended Learning; Instructional Effectiveness; Program Effectiveness; Professional Development; Course Descriptions; Instructional Materials; Computer Assisted Instruction; Virtual Classrooms; Intermode Differences; Comparative Analysis; Intervention

Abstract:
The 2006-11 Regional Educational Laboratory Appalachia at CNA conducted a rigorous evaluation of the Kentucky Virtual Schools hybrid algebra I curriculum. The curriculum combines traditional face-to-face instruction with an online program. This study used a two-cohort sample with 25 high schools in year 1 (SY 07/08: 13 treatment and 12 control) and 22 in year 2 (SY 08/09: 11 and 11), the randomized sample included 6,908 students, 61.4 percent of whom were in rural schools. As reported in the study, "Effects of the Kentucky Virtual Schools Hybrid Program for Algebra I on Grade 9 Student Math Achievement," researchers found that the hybrid class format was no more effective at increasing student achievement and future coursetaking in math than algebra offered in the traditional face-to-face format Eight appendixes present: (1) Power Analysis; (2) Data Collected but Not Analyzed; (3) Sample Detail; (4) Technical Information; (5) Data Cleaning and File Construction; (6) Professional Development Timeline; (7) Detailed Teacher Survey Results; and (8) Results of Sensitivity Analyses. (Contains 38 footnotes, 17 figures, and 43 tables.) [This report was prepared for the National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences with Regional Educational Laboratory Appalachia administered by CNA Education.] Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

 ERIC Full Text (2228K)

Descriptors:
Higher Education; Political Science; State Colleges; Governance; Agenda Setting; Access to Education; Tuition; Undocumented Immigrants; Political Influences; In State Students; Economic Factors; Educational Policy; Unemployment; Predictor Variables; Females; Legislators; Educational Legislation; Federal Legislation; State Legislation; Disproportionate Representation

Abstract:
Few recent issues in higher education have been as contentious as that of legislation extending in-state college tuition benefits to undocumented students, initiatives now known as in-state resident tuition (ISRT) policies. Building on several strands of literature in political science and higher education studies, we analyze the effects of demographic, economic, political, and policy conditions on the likelihood of these initiatives becoming positioned for legislative action during the period 1999-2007. In particular, we develop and test a theoretical framework distilled from research on "descriptive and substantive representation" in U.S. politics. Our event history analysis finds that the percentage of female legislators (an indicator of descriptive representation), the percentage of the population that is foreign born, the level of unemployment, and the type of higher education governance in a state are associated with the likelihood of an ISRT initiative achieving the legislative agenda. To conclude, we explore several conceptual and policy implications of our findings. (Contains 6 tables, 4 figures and 23 notes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Wages; Demand Occupations; Industrial Education; Labor Market; High School Graduates; Engineering; Trade and Industrial Education; Vocational Education; Technology; Engineering Technology

Abstract:
This study examines the availability of career and technical education program areas in Tennessee high schools, concentrations (a three-or-more credit sequence in a program area) completed by 2007/08 high school graduates, and how these concentrations align with jobs in the labor market. It looks at how these outcomes differ, statewide and by region, and identifies corresponding high-wage and high-demand occupations projected over 2006-16. Key findings include: (1) Statewide, the average number of program areas offered in non-career and technical education schools (schools where students received their diploma and that offer courses in addition to those in career and technical education program areas) was 3.6 (out of 7). Across regions, it ranged from 2.9 to 4.7; (2) Statewide, 92 percent of graduates were enrolled in a school offering trade and industrial education, the program area most commonly available, and 26 percent were enrolled in a school offering technology engineering, the program area least commonly available; (3) Statewide, 18 percent of concentrators would need to change program areas to match the distribution of workers in the labor market; (4) Except for technology engineering occupations, which were high wage in all regions, occupations classified as high-wage varied by region; (5) No program area corresponded to a high-demand occupation in all regions. Business technology and trade and industrial education were the only program areas that did not correspond to a high-demand occupation in any region; and (6) Up to 7.1 percent of jobs in high-demand occupations projected over 2006-16 could potentially be filled by 2007/08 concentrators in corresponding program areas, suggesting that up to 71 percent of these jobs could be filled over the 10-year period if the number of these concentrators remains constant. Appended are: (1) Data sources and methodology; (2) Detailed supporting data; and (3) Sensitivity analyses with alternate crosswalk. (Contains 4 boxes, 3 maps, 31 tables and 18 notes.) [For "Aligning Career and Technical Education with High-Wage and High-Demand Occupations in Tennessee. Summary. Issues & Answers. REL 2011-No. 111," see ED522341.] Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

 ERIC Full Text (1762K)

Descriptors:
Wages; Demand Occupations; Industrial Education; Labor Market; High School Graduates; Engineering; Trade and Industrial Education; Vocational Education; Technology; Engineering Technology

Abstract:
This study examines the availability of career and technical education program areas in Tennessee high schools, concentrations (a three-or-more credit sequence in a program area) completed by 2007/08 high school graduates, and how these concentrations align with jobs in the labor market. It looks at how these outcomes differ, statewide and by region, and identifies corresponding high-wage and high-demand occupations projected over 2006-16. Key findings include: (1) Statewide, the average number of program areas offered in non-career and technical education schools (schools where students received their diploma and that offer courses in addition to those in career and technical education program areas) was 3.6 (out of 7). Across regions, it ranged from 2.9 to 4.7; (2) Statewide, 92 percent of graduates were enrolled in a school offering trade and industrial education, the program area most commonly available, and 26 percent were enrolled in a school offering technology engineering, the program area least commonly available; (3) Statewide, 18 percent of concentrators would need to change program areas to match the distribution of workers in the labor market; (4) Except for technology engineering occupations, which were high wage in all regions, occupations classified as high-wage varied by region; (5) No program area corresponded to a high-demand occupation in all regions. Business technology and trade and industrial education were the only program areas that did not correspond to a high-demand occupation in any region; and (6) Up to 7.1 percent of jobs in high-demand occupations projected over 2006-16 could potentially be filled by 2007/08 concentrators in corresponding program areas, suggesting that up to 71 percent of these jobs could be filled over the 10-year period if the number of these concentrators remains constant. [For the full report, "Aligning Career and Technical Education with High-Wage and High-Demand Occupations in Tennessee. Issues & Answers. REL 2011-No. 111," see ED522342.] Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

 ERIC Full Text (427K)

Descriptors:
Quasiexperimental Design; Probability; Grants; Intervention; Program Evaluation; High Schools; Identification; Selection; Comparative Analysis; Evaluation Criteria; Scores; Academic Achievement; Consortia

Abstract:
This presentation focuses on the quasi-experimental methods used to select comparison schools for an evaluation of a federal investing in innovation (i3) validation grant. The Northeast Tennessee College and Career Ready Consortium (NETCO) consists of 29 high schools participating in a five-year program to expand students' access to rigorous courses. The research question for this presentation is: How can propensity score matching be used to identify comparison schools for the evaluation of the NETCO intervention? This report describes the propensity score model used to select comparison schools, the techniques used to refine the model, and the recruitment of the comparison schools. Twenty-nine high schools in fifteen school districts from Northeast Tennessee were selected to participate in the intervention prior to the award of the grant. Overall, the preliminary propensity score analysis for the NETCO evaluation is able to substantially reduce differences in observable characteristics between the i3 schools and non-i3 schools in the state. There are no statistically significant differences in t-tests of the covariates between the treatment group and the matched comparison group, and the absolute standardized bias is less than 0.5 for all covariates. (Contains 1 table, 3 figures and 2 footnotes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

 ERIC Full Text (133K)

Descriptors:
High School Graduates; Public Schools; Enrollment Rate; Two Year Colleges; Colleges; Student Characteristics; Vocational Education; Economically Disadvantaged; Limited English Speaking; Reading Achievement; Mathematics Achievement; Gender Differences; Racial Differences

Abstract:
This brief document summarizes findings from "Estimating College Enrollment Rates for Virginia Public High School Graduates. Issues & Answers. REL 2011-No. 104." Using data from the National Student Clearinghouse and the Virginia Department of Education, the report examines college enrollment rates overall and by student academic and demographic characteristics for the Virginia public high school class of 2008. [This report was prepared for the National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences (IES) by the Regional Educational Laboratory Appalachia administered by the CNA Corporation. For the main report, see ED515839.] Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

 ERIC Full Text (429K)

Descriptors:
High School Graduates; Public Schools; Enrollment Rate; Two Year Colleges; Colleges; Student Characteristics; Vocational Education; Economically Disadvantaged; Limited English Speaking; Reading Achievement; Mathematics Achievement; Gender Differences; Racial Differences; White Students; Hispanic American Students; African American Students; Asian American Students

Abstract:
Using data from the National Student Clearinghouse and the Virginia Department of Education, this report examines college enrollment rates overall and by student academic and demographic characteristics for the Virginia public high school class of 2008. College enrollment is an issue of national concern. And many states, including Virginia, use college enrollment data to understand what types of students are ready for college--to prepare them for enrollment and improve their outcomes when they get there. But historically, Virginia state and local officials have had to rely on limited information (such as the state and national average percentages of high school students who enroll in college immediately after graduation) to identify enrollment patterns. These averages can be informative, but they mask substantial demographic variation and say little about what types of students enroll. This report uses the best available data on college enrollment from the National Student Clearinghouse (NSC) and on high school graduates from the Virginia Department of Education to disaggregate enrollment by academic characteristics (diploma type, career and technical education [CTE] completer status, proficiency on state end-of-course assessments) and by demographic characteristics (race/ethnicity, sex, economically disadvantaged status, limited English proficiency status). It compares these data for enrollment in both two- and four-year colleges within one year of high school graduation. Cross-group differences identified in this report can serve as a benchmark for assessing rates of change over time as new data become available. Data sources and methodology are appended. (Contains 7 notes, 2 boxes, 3 tables, and 12 figures.) [This report was prepared for the National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences (IES) by the Regional Educational Laboratory Appalachia administered by the CNA Corporation. For the summary, see ED515847.] Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

 ERIC Full Text (566K)

Descriptors:
Educational Change; State Officials; Role; Elementary Secondary Education; Higher Education; Governance; State Boards of Education; Influences; Leadership; Administrative Organization; Social Influences

Abstract:
This study examines the role of governors in the P-16 education reform movement through their influence in the adoption of policies creating statewide P-16 councils. Network theory is used to distill three sets of hypotheses to predict how leadership influences of governors, the structure of state educational governance organizations, and environmental characteristics of states may help to explain the spread of voluntary and mandatory P-16 councils from 1992 to 2008. These hypotheses are tested empirically through the use of event history analysis. The results indicate that the presence of an education governor, as well as certain environmental conditions, may affect a state's decision of both whether to form a P-16 council and the type of P-16 council that is formed. (Contains 13 notes, 3 tables, and 2 figures.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Higher Education; Research Universities; Educational Finance; Resource Allocation; Financial Policy; Expenditures; Educational Policy; Policy Analysis; Economics; Correlation; Longitudinal Studies; State Aid; State Government; Politics of Education; Institutional Characteristics; Public Colleges

Abstract:
No empirical studies have attempted to explain why states invest differentially in their research and in their non-research universities, although these differences hold important implications for students, postsecondary systems, and society. Deploying a form of hierarchical-linear modeling, our study examines across-state variation in state appropriations allocated to public four-year universities, and the distribution of these appropriations to Carnegie research universities relative to other non-research universities. The analysis suggests that a primary reason why some states "privilege" their research universities is because the research universities in these states tend to engage in more expensive types of activities than do their non-research counterparts. Our analysis, however, points also to certain political influences that tend disproportionately to benefit research universities, including the proportion of appropriations committee members in a state legislature that graduated from the institution. These findings evidence the need for a closer examination of the link between state-policy outputs in higher education, the characteristics of legislative committees and of the individuals who serve on them. (Contains 6 figures, 3 tables, and 8 endnotes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Higher Education; State Aid; Political Influences; Power Structure; Longitudinal Studies; Income; Political Attitudes; Public Officials; Taxes; Expenditures; State Legislation

Abstract:
State funding remains one of the most prominent and debated issues confronting U.S. higher education. In this paper, the authors report the results of a longitudinal analysis of factors associated with state funding efforts for higher education. They begin by developing a conceptual framework that more closely integrates key state political indicators that have received insufficient attention in the past. The focus then turns to describing the construction of a panel data set and a fixed-effects analysis that the authors conducted on the drivers of state appropriations to higher education, measured as appropriations per $1,000 of personal income, over a period of nearly two decades, from 1984 to 2004. The concluding section identifies several findings providing distinctively new perspectives on patterns of state support for higher education over this period. (Contains 3 tables and 13 notes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website