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Descriptors:
Higher Education; Educational Finance; Income; Public Policy; Enrollment Trends; Tax Allocation; Tax Effort; Tuition; Trend Analysis; Educational Trends; Predictor Variables; Educational Resources; Statistical Data; State Aid; Resource Allocation; Expenditure per Student; Financial Support; School Support; State Surveys; Comparative Analysis; Interstate Programs; Tables (Data); School Taxes; School Funds; Local Government; State Government; Student Financial Aid; Costs; Operating Expenses; Public Colleges; Medical Schools; Rural Extension; Economic Climate; Educational Policy

Abstract:
The State Higher Education Finance (SHEF) report is produced annually by the State Higher Education Executive Officers (SHEEO) to broaden understanding of the context and consequences of multiple decisions made every year in each of these areas. No single report can provide definitive answers to such broad and fundamental questions of public policy, but the SHEF report provides information to help inform such decisions. The report includes: (1) An Overview and Highlights of national trends and the current status of state funding for higher education; (2) An explanation of the Measures, Methods, and Analytical Tools used in the report; (3) A description of the Revenue Sources and Uses for higher education, including state tax and non-tax revenues, local tax support, tuition revenue, and the proportion of this funding available for general educational support; (4) An analysis of National Trends in Enrollment and Revenue, in particular, changes over time in the public resources available for general operating support; (5) Interstate Comparisons--Making Sense of Many Variables, using tables, charts, and graphs to compare data among states and over time; and (6) Indicators of Relative State Wealth, Tax Effort, and Allocations for Higher Education, along with ways to take these factors into account when making interstate comparisons. The SHEF report provides the earliest possible review of state and local support, tuition revenue, and enrollment trends for the most recent fiscal year. Appended are: (1) Grapevine Media Tables; (2) Glossary of Terms; (3) State Data Providers; and (4) SSDB Collection Instructions. (Contains 12 figures, 13 tables, and 13 footnotes.) [For "State Higher Education Finance FY 2011," see ED530332.] Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Inquiry; Problem Solving; Science Education; Mathematics Education; Extracurricular Activities; Numeracy; Measurement; Tables (Data); Graphs; Data Interpretation

Abstract:
Science as inquiry and mathematics as problem solving are conjoined fraternal twins attached by their similarities but with distinct differences. Inquiry and problem solving are promoted in contemporary science and mathematics education reforms as a critical attribute of the nature of disciplines, teaching methods, and learning outcomes involving understandings, attitudes, and processes. The investigative and quantitative processes involved in scientific inquiry include seeking problems, identifying researchable questions, proposing hypotheses, designing fair tests, collecting and interpreting data as evidence for claims, constructing evidence-based arguments, and communicating knowledge claims. Within this empirical context, science and mathematics come together to solve problems with evidence, construct knowledge claims, communicate claims, and persuade others that the claims are valid and useful. This study examined the intersection of inquiry and problem solving and the use of mathematics in 26 extracurricular open science inquiries. The category and the appropriateness of the mathematical procedures revealed these students used measurement, numeracy skills of counting and calculation, and tables and graphs in their science inquiries. It was found that most measurements in the science inquiries were used appropriately, but there is room for improvement with other mathematical procedures that involve higher-level thinking skills, such as analyzing and calculating numerical data and interpreting graphs and tables. The findings imply that mathematics and science are connected in inquiry and should be extended to solve real-life problems and that instruction should emphasize comprehending and interpreting data. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Deans; Electronic Learning; Internet; Online Courses; Higher Education; National Surveys; Large Group Instruction; Enrollment; Administrator Attitudes; Outcomes of Education; Teacher Attitudes; Barriers; Tables (Data); Graphs

Abstract:
"Changing Course: Ten Years of Tracking Online Education" in the United States is the tenth annual report on the state of online learning in U.S. higher education. The survey is designed, administered and analyzed by the Babson Survey Research Group. Data collection is conducted in partnership with the College Board. This year's study, like those for the previous nine years, tracks the opinions of chief academic officers and is aimed at answering fundamental questions about the nature and extent of online education. Based on responses from more than 2,800 colleges and universities, the study addresses Massive Open Online Courses (MOOCs). (Contains 6 footnotes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Expenditures; School Districts; Public Schools; School Statistics; State Departments of Education; Income; Federal Aid; Educational Finance; School District Size; Charter Schools; Tables (Data); Elementary Secondary Education; Expenditure per Student; Enrollment; Instruction; Pupil Personnel Services

Abstract:
This report presents data from the School District Finance Survey (F-33) of the Common Core of Data (CCD) survey system for school year (SY) 2009-10, fiscal year 2010 (FY 10). The F-33 is a district-level financial survey that consists of data submitted annually to the National Center for Education Statistics (NCES) and the Governments Division of the U.S. Census Bureau (Census Bureau) by state education agencies (SEAs) in the 50 states and the District of Columbia. The purpose of this report is to introduce new data through the presentation of tables containing descriptive information; therefore, the selected findings chosen for this report demonstrate the range of information available when using the F-33 component of CCD. The selected findings do not represent a complete review of all observed differences in the data and are not meant to emphasize any particular issue. This report presents findings on public education revenues and expenditures at the local education agency (LEA) level using FY 10 provisional data from the F-33 of the CCD survey system. This First Look provides users with an opportunity to access provisional F-33 data that have been fully reviewed, edited, and imputed. Final data, including revisions to the provisional data submitted by the SEAs after the close of data collection, will be available during the following collection year. Appended are: (1) Methodology and Technical Notes; (2) Common Core of Data Glossary; and (3) Reference Tables. (Contains 11 tables and 4 footnotes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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State Standards; Assignments; Probability; Teaching Guides; Grade 6; Grade 7; Grade 8; Internet; Computer Uses in Education; Mathematics Instruction; Mathematics Skills; Mathematical Concepts; Statistical Analysis; Class Activities; Mathematics Activities; Worksheets; Lesson Plans; Instructional Materials; Visual Aids; Academic Standards; National Standards; Relevance (Education); Tables (Data)

Abstract:
"The Power of Probability" is a new math program aligned with the National Council of Teachers of Mathematics (NCTM) and Common Core State Standards, which gives students opportunities to practice their skills and knowledge of the mathematics of probability. Developed by The Actuarial Foundation, the program's lessons and worksheets motivate students through activities that use mathematics for real purposes. [A poster that accompanies this teaching guide can be viewed and/or retrieved at: http://www.actuarialfoundation.org/pdf/poster-conversions-rock.pdf.] Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Academic Achievement; Factor Analysis; Individual Characteristics; Youth; Foreign Countries; Non English Speaking; Academic Persistence; Longitudinal Studies; Institutional Characteristics; College Bound Students; Higher Education; Socioeconomic Background; Success; Tables (Data); Student Attitudes; Models; Transitional Programs

Abstract:
This report uses Longitudinal Surveys of Australian Youth (LSAY) data to look at the impact of schools on a student's tertiary entrance rank (TER) and the probability of them going to university (controlling for TER). It shows that the characteristics of schools do matter: although young people's individual characteristics are the main drivers of success, school attributes are also responsible for almost 20% of the variation in TER scores. The three most important school attributes for TER include sector (Catholic and independent/ government); gender mix (single sex/co-educational) and the extent to which a school is "academic". The socioeconomic status of schools didn't emerge as a significant influence on TER. For the probability of going to university, after controlling for TER, the most significant school characteristics include the proportion on non-English speaking background students; the sector; and the socioeconomic make-up of the student body. Appended are: (1) Descriptive statistics; (2) Student-level measures; (3) Factor analysis for SES measure; (4) Factor analysis for perceptions of schooling measure; (5) Technical details on multi-level modelling; (6) Results from multi-level modelling; and (7) Information on the Logistic scale. (Contains 21 tables, 13 figures and 29 footnotes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Trainees; Foreign Countries; Mathematical Models; Expenditures; Vocational Education; Apprenticeships; Trend Analysis; Classification; Vocabulary; Definitions; Statistical Data; Occupations; Tables (Data); Gender Differences; Industry; Comparative Analysis; Age Differences; Graduation Rate; Certification

Abstract:
This publication presents estimates of apprentice and trainee activity in Australia for the September quarter 2012. The figures in this publication are derived from the National Apprentice and Trainee Collection no.74 (December 2012 estimates). The most recent figures in this publication are estimated (those for training activity from the March quarter 2011 to the September quarter 2012). Estimates take into account reporting lags that occur at the time of data collection. Consequently, the figures in this publication may differ from those published in earlier or later reports. Estimated data are presented in this publication on a seasonally adjusted, quarterly and 12-month ending series basis. The 12-month ending series is particularly useful in showing longer-term data trends, but is less useful in identifying turning points. The seasonally adjusted data involve the use of a mathematical model to smooth out fluctuations due to seasonal influences. Seasonally adjusted data are useful to illustrate trends from one quarter to the next, but cannot be further disaggregated. (Contains 19 tables, 3 figures and 7 notes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Academic Achievement; Research Methodology; Educational Change; Scores; School Restructuring; Mathematics Achievement; Reading Achievement; Educational Trends; Trend Analysis; Low Achievement; School Turnaround; Outcomes of Education; Institutional Characteristics; School Demography; Labor Force; Intervention; Instructional Leadership; Governance; Teachers; Students; Elementary Secondary Education; Tables (Data); School Closing

Abstract:
Specific strategies for "turning around" chronically low-performing schools have become prominent, with the U.S. Department of Education enacting policies to promote four school improvement models that include "fundamental, comprehensive changes in leadership, staffing, and governance." Despite the attention and activity surrounding these types of school improvement models, there is a lack of research on whether or how they work. To date, most evidence has been anecdotal, as policymakers have highlighted specific schools that have made significant test score gains as exemplars of school turnaround, and researchers have focused on case studies of particular schools that have undergone one of these models. This has led to a tremendous amount of speculation over whether these isolated examples are, in fact, representative of turnaround efforts overall--in terms of the way they were implemented, the improvements they showed in student outcomes, and whether these schools actually served the same students before and after reform. To begin addressing this knowledge gap, the University of Chicago Consortium on Chicago School Research and American Institutes for Research (AIR) partnered to examine five different models initiated by the Chicago Public Schools (CPS) in 36 schools. The goals of the study were to make clear how school reform occurred in Chicago--showing the actual changes in the student population and teacher workforce at the schools--and to learn whether these efforts had a positive effect on student learning overall. Appended are: (1) Description of Low-Performing Schools that Underwent Intervention; (2) Data and Data Sources; and (3) Research Methods and Results. (Contains 19 figures, 24 tables, 62 endnotes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Job Search Methods; Profiles; Occupational Information; Employment Statistics; Data; Information Utilization; Geographic Location; Industry; Tables (Data)

Abstract:
Using occupation profiles, jobseekers can see which industries employ the most workers in a particular field, which geographical areas have high concentrations of those jobs, and how wages differ by industry and geographical area. This article gives an overview of the data in the Occupational Employment Statistics (OES) occupation profiles. It describes different jobseeking situations and shows how employment and wage data could be useful in each case. The first section describes how to use the three types of data in each profile: national, industry, and geographic. The second section explains how to get additional data by creating customized tables. The final section provides more information, including how to use industry profiles of occupations. (Contains 1 chart and 3 illustrations.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Postdoctoral Education; Accreditation (Institutions); Internship Programs; Residential Programs; College Programs; Check Lists; Professional Training; Statistical Data; Tables (Data); Psychology; Psychologists; Information Sources

Abstract:
This is the official listing of accredited internship and postdoctoral residency programs in psychology. It reflects all Commission on Accreditation decisions through July 22, 2012. (Contains 15 footnotes.)

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