ethanporcaro/eric-fulltext-meta huggingface dataset:
Competence Requirements in Early Childhood Education and Care. Final Report
Author: Urban, Mathias
Date: 2012-10-00
Type: Reports - Research
Subjects: Early Childhood Education,Young Children,Foreign Countries,Child Care,Competence,Teacher Competencies,Theory Practice Relationship,Educational Policy,Professional Development,Cross Cultural Studies,Cultural Differences,Teacher Education,Educational Quality,Educational Improvement,Teacher Qualifications,Case Studies

This report presents the findings of a European research project jointly conducted by the University of East London (UEL) and the University of Ghent (UGent). The &quot;study on competence requirements in early childhood education and care&quot; (CoRe) explored conceptualisations of &quot;competence&quot; and professionalism in early childhood practice, and identified systemic conditions for developing, supporting and maintaining competence at all layers of the early childhood system. The European Commission Directorate-General for Education and Culture commissioned the research conducted between January 2010 and May 2011. In the light of the research findings, and intensive consultations with key stakeholders in ECEC [early childhood education and care] in Europe, CoRe has developed policy recommendations, which are also part of this report. (Contains 31 footnotes and 4 tables.)
Measurement Framework for National Key Performance Measures
Author: Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA) (Australia)
Date: 2006-08-00
Type: Reports - Descriptive
Subjects: Foreign Countries,Educational Policy,Program Descriptions,Program Development,Measurement,Educational Indicators,Educational Assessment,Educational Objectives,National Programs,Comparative Analysis,Cohort Analysis,Gender Differences,Indigenous Populations,English (Second Language),Literacy,Numeracy,Science Achievement,Civics,Information Technology,Student Participation,Educational Attainment,Citizenship Education,Definitions,Educational Change,Geographic Location,Vocational Education,Student Characteristics,Socioeconomic Background,Native Language,Benchmarking,Academic Standards,Data Analysis,Comparative Education,Academic Achievement,Elementary Secondary Education,Scheduling

In 1999 Ministers responsible for school education agreed to the new set of &quot;National Goals for Schooling in the Twenty-First Century,&quot; with the aim of providing high quality schooling in Australia which would secure for students the necessary knowledge, understanding, skills and values for a productive and rewarding life. As a consequence, the national council of Ministers (MCEETYA) set in train a process to enable nationally comparable reporting of progress against the &quot;National Goals.&quot; This &quot;Measurement Framework for National Key Performance Measures&quot; takes account of all MCEETYA decisions related to measuring performance against the &quot;National Goals.&quot; It sets out a basis for reporting progress towards the achievement of the &quot;National Goals&quot; by Australian school students drawing on the agreed definitions of Key Performance Measures. The core of the &quot;Framework&quot; is a schedule setting out Key Performance Measures and an agreed assessment and reporting cycle for the period 2003-2011. With the aim of driving school improvement and enhanced outcomes for students, Ministers responsible for school education have agreed to report on progress towards the achievement of the &quot;National Goals for Schooling&quot; in the following priority areas, comparable by State and Territory, and using Key Performance Measures as the basis for reporting: (1) literacy; (2) numeracy; (3) science; (4) civics and citizenship education; (5) information and communication technology; (6) vocational education and training in schools; and (7) participation and attainment. Ministers also noted the need to investigate the development of indicators of performance in enterprise education but have since agreed that work in this area should cease for the time being. Definitions of student characteristics have been agreed by MCEETYA. Student outcomes will be reported for the student cohorts disaggregated by: (1) sex; (2) Indigenous status; (3) language background; (4) geographic location; and (5) socio-economic background. (Contains 21 footnotes.)
MCEETYA Joint Statement on Education and Training in the Information Economy
Author: Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA) (Australia)
Date: 2012-00-00
Type: Reports - Evaluative
Subjects: Foreign Countries,Knowledge Economy,Information Technology,Computer Uses in Education,Innovation,Academic Achievement,Educational Quality,Educational Cooperation,Global Approach

New technologies are transforming our society: the way we work, our social and community life and the way we learn. Embracing information and communications technology in education and training improves the skills and knowledge of all Australians, enhances our international engagement, and moves Australia confidently into the twenty-first century. The everyday use of information and communications technology will transform education and training, and lay a foundation for our future economic and social prosperity. National collaboration is essential to achieve this vision. This paper presents the Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA) joint statement on education and training in the information economy.
Is College Affordable? In Search of a Meaningful Definition. Issue Brief
Author: Baum, Sara
Date: 2012-07-00
Type: Reports - Evaluative
Subjects: Housing,Student Financial Aid,Paying for College,Tuition,Health Services,Family Income,Benchmarking,Outcomes of Education

Rising college prices, stagnating incomes, and diminished asset values have led to the widespread perception that college is "unaffordable" for more and more people. The role of student aid in reducing the prices many students pay is too complex to be widely understood, and in spite of increasing enrollment rates, most people do not question the idea that college is unaffordable. The goal of this brief is to make progress in understanding what it really means for college to be "affordable" or "unaffordable." The idea that college is unaffordable simply because it is "too expensive" is not very constructive, and the common practice of comparing published tuition prices--or the combination of tuition and living expenses--with family incomes is misleading. Understanding the complex factors affecting the actual price of college, perceptions of that price, and the very real (and not so real) struggles facing today's students is vital to efforts to increase educational opportunity. In an effort to develop the foundation for more constructive policy discussions on the financial barriers to postsecondary education, this brief discusses a variety of ways to approach the concept of affordability. The first step is to review work in two other policy areas--housing and health care--in which affordability issues receive considerable attention. Although the subjectivity of the term "affordability" cannot be avoided, housing and health care analysts have made some progress in developing benchmarks. The brief then discusses two important facets of the debate about affordability that should be clear in the minds of policymakers. First, the costs and benefits of college are widely misunderstood. In particular, the concept of "net price"--the price students pay after receiving financial aid that does not have to be repaid--is difficult to communicate. Second, the uncertain return on higher education makes the investment risky and therefore less attractive for many people. (Contains 3 tables and 14 footnotes.)
A New Classification Scheme for For-Profit Institutions
Author: Institute for Higher Education Policy
Date: 2012-07-00
Type: Reports - Descriptive
Subjects: Classification,Proprietary Schools,Postsecondary Education,Institutional Characteristics,College Students,Student Characteristics,Graduation Rate,Enrollment,Competition,School Location,Specialization,Full Time Students,Part Time Students,Enrollment Trends

For-profit institutions are more visible today among policymakers, researchers, and investors, due in large part to the sharp rise in the number of students attending them over the last decade. From 2000 to 2009, enrollment in the for-profit sector tripled while enrollment in the public and not-for-profit sectors increased by less than 25 percent. By 2009, for-profits made up 43 percent of all postsecondary institutions in the United States and enrolled nearly 10 percent of all undergraduate students. Clearly, it is crucial to understand this sector and the ways in which for-profits contribute to educating students. For-profits are often quite different from their counterparts in other sectors. For example, they are smaller in size, less likely to offer degrees, and more likely to be located in metropolitan areas than institutions in other sectors. Most (90 percent) of for-profits have less than 1,000 students, a majority (62 percent) are non-degree granting, and most (86 percent) are located in metropolitan areas. Students attending for-profits are more likely than students in other sectors to be older, female, non-White, independent, and first in their family to attend college. Yet there is also wide variation within the for-profit sector, from small cosmetology schools to local campuses specializing in business or technology to online universities offering a wide range of degrees. Capturing this diversity is essential to understanding the sector--and one way to do so is a classification scheme that can be used to compare institutions and the students they serve. Many classification schemes have been used to group postsecondary institutions, usually based solely on institutional characteristics such as size, degree programs, and student demographics. While the characteristics used in existing classification schemes are acceptable for the public and private not-for-profit sectors, they do not capture the uniqueness of for-profit institutions, causing the sector to be treated as monolithic and broad strokes are used to describe for-profit institutions and students. A multifaceted framework to reflect the diversity in the for-profit sector is needed. To that end, this report describes a new classification scheme solely for the for-profit sector that includes criteria that are different than those used in existing schemes--the markets that for-profits operate in, institutional specialization, and the ways in which students engage for-profits. Appended are: (1) Data Sources and Methodology; and (2) Supplemental Tables. (Contains 2 boxes, 4 figures, 12 tables and 30 footnotes.) [Funding for this paper was provided by the USA Funds. For "A New Classification Scheme for For-Profit Institutions. Fact Sheet," see ED534616.]
Economic Diversity among Selective Colleges: Measuring the Enrollment Impact of &quot;No-Loan&quot; Programs. Issue Brief
Author: Hillman, Nicholas
Date: 2012-08-00
Type: Reports - Evaluative
Subjects: Enrollment,Student Diversity,Colleges,Selective Admission,Undergraduate Students,Low Income Groups,Economically Disadvantaged,Disproportionate Representation,Tuition,Student Financial Aid,Grants,Scholarships,School Policy,Endowment Funds,Private Colleges,Public Colleges,Eligibility

Students from low-income families are underrepresented in higher education, despite the fact that many of them are well qualified to enroll. When low-income students do enroll in college, they tend to be overrepresented in public community colleges and for-profit institutions, or if they attend four-year institutions, tend to attend regional state institutions. These institutions often have lower graduation rates, fewer academic resources for students, and lower faculty-to-student ratios. However, these institutions also charge lower tuition. As a result, they are desirable for many price-sensitive students, regardless of the students' academic achievement. Conversely, highly selective institutions have more academic resources for facilitating student success, and their students have greater chances of earning degrees. Highly selective institutions also charge significantly higher tuition. The sticker price of attending these colleges is often higher than the annual earnings of a low-income family, causing &quot;sticker shock&quot; for many interested students. As a result, few high-achieving students from low-income families enroll in highly selective institutions, despite the fact that they may be academically qualified to do so. In turn, highly selective institutions tend to enroll small proportions of low-income students. Some colleges and universities have often tried to increase the numbers of low-income students on their campuses through scholarship programs, need-blind admissions policies, or other efforts. More recently, some have adopted &quot;no-loan&quot; policies in order to expand access and choice for low-income students. Despite the spread of no-loan policies, little is known about the effects of this strategy on improving economic diversity at the participating institutions. To address this knowledge gap, this brief evaluates the impacts of no-loan policies on low-income student enrollment and assesses the length of time required after policy implementation for any observable effect to be realized. Two equations are appended. (Contains 7 figures, 6 tables, and 33 footnotes.)
A New Classification Scheme for For-Profit Institutions. Fact Sheet
Author: Institute for Higher Education Policy
Date: 2012-07-00
Type: Reports - Descriptive
Subjects: Classification,Proprietary Schools,Postsecondary Education,Institutional Characteristics,Competition,School Location,Specialization,Full Time Students,Part Time Students,College Students,Student Characteristics,Enrollment Trends

For-profit institutions are more visible today among policymakers, researchers, and investors, due in large part to the sharp rise in the number of students attending them over the last decade. From 2000 to 2009, enrollment in the for-profit sector tripled while enrollment in the public and not-for-profit sectors increased by less than 25 percent. By 2009, for-profits made up 43 percent of all postsecondary institutions in the United States and enrolled nearly 10 percent of all undergraduate students. Clearly, it is crucial to understand this sector and the ways in which for-profits contribute to educating students. For-profits are often quite different from their counterparts in other sectors. For example, they are smaller in size, less likely to offer degrees, and more likely to be located in metropolitan areas than institutions in other sectors. Most (90 percent) of for-profits have less than 1,000 students, a majority (62 percent) are non-degree granting, and most (86 percent) are located in metropolitan areas. Students attending for-profits are more likely than students in other sectors to be older, female, non-White, independent, and first in their family to attend college. Yet there is also wide variation within the for-profit sector, from small cosmetology schools to local campuses specializing in business or technology to online universities offering a wide range of degrees. Capturing this diversity is essential to understanding the sector--and one way to do so is a classification scheme that can be used to compare institutions and the students they serve. Many classification schemes have been used to group postsecondary institutions, usually based solely on institutional characteristics such as size, degree programs, and student demographics. While the characteristics used in existing classification schemes are acceptable for the public and private not-for-profit sectors, they do not capture the uniqueness of for-profit institutions, causing the sector to be treated as monolithic and broad strokes are used to describe for-profit institutions and students. A multifaceted framework to reflect the diversity in the for-profit sector is needed. To that end, this report describes a new classification scheme solely for the for-profit sector that includes criteria that are different than those used in existing schemes--the markets that for-profits operate in, institutional specialization, and the ways in which students engage for-profits. (Contains 4 figures.) [For the main report, "A New Classification Scheme for For-Profit Institutions," see ED534614.]
National Education and the Arts Statement
Author: Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA) (Australia)
Date: 2012-00-00
Type: Reports - Descriptive
Subjects: Foreign Countries,Art Education,Educational Quality,Equal Education,Partnerships in Education,School Community Relationship,Art,Culture,Elementary Secondary Education

An arts-rich education can help young people make sense of the world and enhance their awareness of diverse cultures and traditions and the wider global context in which they live. This national statement aims to drive change. It lays the foundation for stronger coordination of government policy, programs and services in education and the arts for children and young people across Australia. It aims to build on the principles of both the Adelaide Declaration and the Stepping Forward declaration on improving pathways for all young people. The statement is underpinned by three key principles: (1) All children and young people should have a high quality arts education in every phase of learning; (2) Creating partnerships strengthens community identity and local cultures; and (3) Connecting schools with the arts and cultural sector enriches learning outcomes. Arising from these principles are four keys areas for collaborative action that were identified through the consultation process: (1) professional development; (2) curriculum, policy and learning resources;  (3) research and communication; and (4) partnerships. The statement is for all educators who want students and schools to achieve and succeed through developing their capacity to discover, imagine and create. It is also for parents who understand the need for challenging and creative learning experiences for their children, for artists and organisations seeking stronger engagement with young people and schools, and for business leaders who recognise the need for new knowledge, skills and capacity for innovation that will lead Australia's growth into the 21st century. The national statement is intended to guide arts and education leaders to ensure our education systems help children and young people to imagine, to dream and to achieve their very best. (Contains 1 footnote.)
Predicting Student Success on the Texas Chemistry STAAR Test: A Logistic Regression Analysis
Author: Johnson, William L.
Date: 2012-08-25
Type: Reports - Research
Subjects: High School Students,Grade 10,Grade 11,Chemistry,Science Tests,Achievement Tests,Science Achievement,Scores,Regression (Statistics),Prediction,Models,Accuracy,Test Preparation,Testing

Background: The context is the new Texas STAAR end-of-course testing program. Purpose: The authors developed a logistic regression model to predict who would pass-or-fail the new Texas chemistry STAAR end-of-course exam. Setting: Robert E. Lee High School (5A) with an enrollment of 2700 students, Tyler, Texas. Date of the study was the 2011-2012 academic year. Study Sample: A sample of n = 100 students from the author's chemistry classes (32 high school sophomores and 68 high school juniors). Intervention: Developed a binary logistic regression prediction model (no control group applicable). Research Design: Statistical Modeling. Control or Comparison Condition: Control or comparison group--not applicable for the study. Data Collection and Analysis: The students' (n = 100) STAAR test scores from the new Texas end-of-course chemistry pilot test were analyzed in the 2011-2012 school year. Variables included in the logistic regression model were as follows:  Students' previous years science TAKS test scores (raw data); science TAKS scores and STAAR end-of-course scores coded pass (1) or fail (0) as categorical variables; and students' grade level coded sophomore (0) or junior (1) as  categorical variables. Findings: A binary logistic regression analysis was performed using the new Texas end-of-course pilot chemistry STAAR test scores as the dependent variable (DV) and the previous year's science TAKS scores and grade level as predictor variables. A total of n = 100 cases were analyzed, and the full model was significantly reliable (chi-square = 102.568, df = 2, p less than 0.000).  This model accounted for between 64.1% and 85.9% of the variance in STAAR status, with 92.9% of the students passing the STAAR test successfully predicted and 93.2% of students failing the STAAR test successfully predicted. Overall, 93.0% of the predictions were correct.  The Wald statistic showed that the TAKS raw score reliably predicted passing or failing the  STAAR end-of-course chemistry test. Conclusion: The binary logistic regression model was significantly reliable (chi-square = 102.568, df = 2, p less than 0.000). Overall, 93% of the predictions were correct. The model had a very high predictive outcome. Logistic Regression Variables are appended to this document.
An Exploration of Maine Community College's Admission Process: A Recommendation to Maine's Department of Education
Author: Woodbury, Amanda L.
Date: 2012-08-12
Type: Reports - Evaluative
Subjects: Community Colleges,College Admission,Language Fluency,English (Second Language),Admission Criteria,Allied Health Occupations Education,Nursing Education,Prerequisites

It is no secret that the United States is falling way behind in world educational rankings. In 1995, the United States ranked 1st in the world for college graduates however, its ranking dramatically fell in 2005, earning 15th place (Woodruff, 2008). According to the U.S. Chamber of Commerce, most states earn a grade of C, D, or F when it comes to preparing college graduates for the workplace (2008). It is going to take a drastic overhaul of the United States educational system in order to reclaim its number one standing. However, one has to be cognizant of the diversity factor when it comes to pre-requisites and other program admission requirements. We cannot continue to admit prospective students into programs where the English language is critical to the success of the student and/or the safety of the public just to reach or exceed college admission department's financial goals. Not only will it be a disservice to the prospective student, but to the public as well.