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Descriptors:
Educational Finance; Evidence; Stakeholders; Expenditures; Voting; Tax Effort; Community Characteristics; School District Wealth; Operating Expenses; Political Attitudes; Consciousness Raising; Change Strategies; Multiple Regression Analysis; Data Analysis; Statistical Data; Input Output Analysis; Cost Effectiveness; Audits (Verification); School Budget Elections; Politics of Education; Schematic Studies

Abstract:
Using logistic regression, this study sought to understand the relationship between district characteristics, district finances, levy characteristics, and campaign expenditures with new operating levy outcomes. We found that employee benefits as a percentage of the district's budget were negatively associated with levy outcomes, while salaries were positively associated with levy outcomes, suggesting that voters may be more sensitive to retirement and healthcare benefits than salaries when voting. While campaign spending was related to levy success, types of expenditures were largely insignificant. School district personnel must be cognizant of the local conditions in crafting campaigns and recruiting community stakeholders. (Contains 4 tables, 1 figure, and 6 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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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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 ERIC Full Text (15644K)

Descriptors:
Supplementary Education; Tutoring; Peer Teaching; Guides; Study Guides; Program Guides; Instructional Materials; Training Methods; Training Objectives; Tutors; Bibliographies; Pretests Posttests; Educational Principles; Teacher Responsibility; Program Improvement; Records (Forms); Statistical Data; Problem Sets; Learning Activities; Reference Materials; Program Descriptions; Educational Strategies; Educational Practices

Abstract:
This manual consists of an introduction to our Academic Peer Instruction (API) program at LaGuardia Community College, a compilation of the materials we have developed and use for training of our tutors (with answers), and a bibliography. API is based on an internationally recognized peer tutoring program, Supplemental Instruction. (Contains 6 tables and 23 figures.)

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Older Adults; Foreign Countries; Statistical Data; Income; Data Collection; Labor Market; Poverty; Social Indicators; Nursing Homes; Validity; Retirement Benefits

Abstract:
Growing life expectancy and changes in financial, marriage and labour markets have placed the income position of the elderly at the center of scientific and political discourse. As a consequence, the last decades witnessed the publication of various influential reports that contained comparative statistics on old age income inequalities on the basis of international surveys. Common to these surveys is that they exclude the elderly who live in institutions. The divergence between the target population (e.g. the population aged 65 and over) and the survey population (e.g. the noninstitutionalized population aged 65 and over) that thus arises, might lead to important bias in the survey results. However, hardly any research has been conducted quantifying the direction and strength of this bias. This article tries to fill this gap and assesses the consequences of excluding the institutionalized elderly for the validity and international comparability of a number of indicators. Analyses with the Belgian Datawarehouse Labour Market and Social Protection show that the resulting bias is negligible for average equivalent pension income, but that assistance dependency among pensioners is underestimated by 10%. Furthermore, on the basis of international statistics, it is shown that the share of elderly in institutions varies substantially across countries. It is argued how this jeopardizes the international comparability of old age statistics. Finally, the article opens up a discussion on the meaning of lack of income and wealth among institutionalized elderly. It concludes that depending on how this question is answered, poverty will be under- or overestimated in countries with a high share of institutionalized elderly. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Adolescents; Vocational Schools; Foreign Countries; Statistical Data; Young Adults; Video Games; Mental Disorders; Predictor Variables; Behavior Patterns; Models; Risk; Screening Tests; Self Control; Therapy; Longitudinal Studies; Scores

Abstract:
Although excessive video gaming has been linked to a range of psychological problems in young people, there have been few systematic attempts to conceptualize problem gaming using established psychological theory. The aim of this study was to examine problematic game use (PGU) using the Theory of Planned Behavior (TPB). A two-wave, six-month longitudinal study examined relationships between core components of the TPB model, video gaming activity and problematic video-game play. Respondents were recruited from nine pre-vocational and senior vocational schools in the western region of the Netherlands. The sample consisted of 810 video game-playing adolescents and young adults (72.8% boys) aged 12 to 22 years. The results showed that TPB predictors, including subjective norm, perceived behavioral control (PBC) and descriptive norm, explained 13% of the variance in video gaming intention. Although TBP variables accounted for a significant amount of variance in PGU scores at baseline, the TPB model was less useful in predicting future gaming behavior and PGU. Perceived behavioral control was found to be the most important factor in predicting problem video-gaming behavior, this has some practical implications with regard to the treatment of problem video-gaming among young people. For example, assessing a client's perceived lack of control over gaming may be a simple but useful screening measure to evaluate risk of future problem play. Furthermore, treatment strategies may be aimed at helping the client to rebuild self-control. 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:
Foreign Countries; Social Indicators; Census Figures; Cross Cultural Studies; Surveys; Religious Cultural Groups; Classification; Trust (Psychology); Interpersonal Relationship; Scores; Correlation; Geographic Regions; Cultural Pluralism; Ethnicity; Second Languages; Statistical Data

Abstract:
For a long time, researchers investigate the impact of diversity on society. To measure diversity, either archival data at the national level of census data at the neighborhood level, within a single country are used. Both approaches are limited. The first approach does not allow to investigate variation in diversity within countries and the second approach misses the possibility to investigate cross national differences. The present study aims at bringing these two approaches closer together by constructing diversity measures based on the European Social Survey (ESS). The ESS is collected every 2 years since 2002 and includes individual level data that allow replicating earlier measures of ethnic, linguistic, and religious diversity for 30 European countries. Furthermore, since respondents are asked to indicate in what region they live, measured with the Nomenclature of Territorial Units for Statistics classification, it is possible to construct disaggregated measures. Comparing the new indicators with existing diversity scores leads to the following conclusions. First, the new and old measures are strongly correlated at the national level. Secondly, investigating the relationship between diversity and different kinds of sociality (interpersonal trust, institutional trust, and support for government redistribution) shows that regional diversity is more strongly related to them than diversity at the national level. (Contains 10 tables.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Difficulty Level; Cognitive Processes; Computer Assisted Instruction; Novices; Statistical Data; Computer Software; Expertise; Effect Size; Experiments; Data Analysis; Educational Environment

Abstract:
The expertise reversal effect occurs when learner's expertise moderates design principles derived from cognitive load theory. Although this effect is supported by numerous empirical studies, indicating an overall large effect size, the effect was never tested by inducing expertise experimentally and using instructional explanations in a computer-based environment. The present experiment used an illustrated introductory text and a computer program about statistical data analyses with 93 students. Retention and transfer tests were employed as dependent measures. Each learner was randomly assigned to one condition of a 2 x 2 between subjects factorial design with the two factors expertise (novices vs. "experts") and explanations (with vs. without). Expertise was induced by adding expository examples and illustrations to the introductory text to enhance text coherence and facilitate text comprehension. The expertise reversal effect was replicated for the dependent measure transfer, but not for retention. Results and implications for adaptive learning environments are discussed. 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:
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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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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Descriptors:
Outcomes of Education; Expertise; Law Schools; College Graduates; Job Placement; Court Litigation; Profiles; Colleges; Surveys; Employment; Employment Level; Universities; Higher Education; Reliability; Statistical Data

Abstract:
As colleges and lawmakers seek better data about the employment success of graduates, a lack of standardized tracking makes much of the information unreliable. Many colleges release placement rates based on scant information: More than a third of colleges' reported rates in 2010 were based on responses from half of their graduates or fewer, according to the National Association of Colleges and Employers. That raises the question of whether the results are skewed by greater participation among happily employed graduates. Some career and for-profit colleges, as well as law schools, have faced high-profile accusations of job-placement fraud, in the form of lawsuits and scrutiny from accreditors. Meanwhile, experts also question the reliability of some of the data that traditional undergraduate institutions release. Even when job-placement surveys yield high response rates, they can be fuzzy on what counts as a job. Many colleges do not ask graduates whether their jobs are related to their degrees or if they feel those jobs have career potential. Most colleges do not account for underemployment or know if a graduate is reporting an unpaid internship. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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