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Adult learning is seen as a key factor for enhancing employment, innovation and growth. The aim of this paper is to understand the points in the life cycle at which adult learning takes place and whether it leads to reaching a medium or high level of educational attainment. We perform a synthetic panel analysis of adult learning for cohorts aged 25-64 in 27 European countries using the European Union Labour Force Survey. We find that investment across the life cycle by cohorts older than 25 still occurs: participation in education and training as well as educational attainment increase observably across all cohorts. We also find that the decline with age slows down, or is even reversed for older cohorts, for both participation in education and educational attainment. Finally, we can identify cross-country differences in approach. In Nordic countries, adult learning is achieved primarily through participation in education and training without adding to formal educational attainment. In central Europe, adult learning occurs primarily in the form of increasing educational attainment. In Ireland and the UK, a combination of both approaches to adult learning is observable.

Purpose: The purpose of this paper is to provide an empirical comparison of two measures of school success -- a value-added assessment system and the federally-mandated system of adequate yearly progress (AYP) -- to identify highly effective urban schools in the USA and to explore the predictive relationship between evidence-based decision-making and school improvement. Design/Methodology/Approach: A total of 204 urban schools with 6,684 teachers and 149,665 students in grades 1 through 10 participated in the study. Data included teacher survey and students' standardized reading and math scores from 2002 through 2005. Analyses included factor analysis, growth modeling, and multiple logistic regression analyses. Findings: AYP status was strongly predicted by student and school demographics rather than by organizational climate and instructional practices. In contrast, school growth as measured by the district's value-added assessment system was unrelated to the demographics of the student population and related strongly to specific school practices. Specifically, high growth schools exhibited strong evidence-based decision-making practice where teachers used the district's benchmark assessment to reflect on instructional practice, used the core curriculum to guide instruction, and received frequent and high quality professional development on reading and math instruction. Practical Implications: As states gravitate away from relying on AYP status as a measure of school success, districts will benefit from integrating measures of growth and using school data management systems that integrate benchmark assessment capabilities and provide teachers with the training and tools needed to use the information in their daily practice. Originality/Value: This study provides a direct comparison of evaluation models using a variety of current methods within a single district that has played a central and highly-visible role in the education reform movement in the USA. (Contains 8 tables.)

In this chapter, the authors develop a theory to explain the effects of mentoring and induction activities on new teachers' commitment, instructional quality, and effectiveness, and they describe how utility functions can express variation in these outcomes. Then they explicate the role of three-level models (i.e., with random effects) in estimating the effects of effort on commitment, instructional quality, and student achievement, with teachers nested within subgroups within schools. Unlike fixed effects models, multilevel models do not merely control for effects of social contexts (e.g., subgroups in schools); instead, they feature the capacity to simultaneously test effects at multiple levels as well as cross-level interactions. Thus, multilevel models are ideal for testing the effects on commitment, instruction, and achievement of (a) effort at the individual novice teacher level and (b) conformity at the subgroup level (Frank et al., 2008). The next section of this chapter describes the value of using utility functions to specify theory related to mentoring and induction and to determine how schools and districts can promote high levels of commitment, instructional quality, and effectiveness among beginning teachers. In the third section, the authors present their conceptual framework, define several terms that are key parts of the framework, place them in the context of the existing literature, and explain their relationship to mentoring and induction. Here they introduce the notion of subgroups to scholarship on induction and explicate how they function in relation to mentoring and other school and district factors. The fourth section defines teacher efficacy and several factors that influence the payoffs of effort, situates them in the relevant research literature, and explains their relationship to effort and various teacher and student outcomes. Finally, this chapter considers how multilevel models can be used to estimate the effects of mentoring, subgroups, and other contextual factors on student learning by testing the effects on achievement of effort at the individual novice teacher level and of conformity at the subgroup level. (Contains 5 notes.)

This study examined the relationship between creative teaching and elementary students' achievement gains. Forty-eight upper elementary school teachers' classroom instruction was observed and evaluated over the course of 8 different lessons throughout the year. For each teacher, during each lesson, both a creative teaching frequency score and a quality score were derived. These scores were then used as predictor variables in a structural equation model to determine the magnitude of the relationship between creative teaching and classroom achievement gains in reading, language, and mathematics. Our results demonstrated that (a) the majority of teachers do not implement any teaching strategies that foster student creativity; (b) teachers who elicit student creativity turn out students that make substantial achievement gains; and (c) classrooms with high proportions of minority and low-performing students receive significantly less creative teaching. (Contains 7 tables, 3 figures and 2 footnotes.)

The Teacher Advancement Program (TAP) is a comprehensive school reform with the goal to attract, retain, and motivate quality teachers. By aggressively recruiting new teachers, providing a career continuum, introducing teacher-led professional development, implementing rigorous teacher accountability, and paying teachers based on their position, teaching skills, and how much their students achieve, TAP schools change their organizational structure to support and reward high-quality instruction. This study examined TAP's preliminary impact on student achievement and teacher attitudes. Using a multivariate-multilevel model for measuring student learning, we compared the growth in achievement of students from TAP schools to the growth in achievement of students from matched controls. Our preliminary results suggest that TAP schools' achievement grew significantly (E.S.=.35 and .41 for 2001 and 2002, respectively) more than controls. However, the magnitude of the achievement gains varied by school and fidelity of implementation.

In a sample of 134 married couples randomly assigned to traditional or integrative behavioral couple therapy (TBCT vs. IBCT), a multivariate hierarchical growth curve analysis using latent variable regression revealed that measures of communication, behavior frequency, and emotional acceptance acted as mechanisms of change. TBCT led to greater changes in frequency of targeted behavior early in therapy, whereas IBCT led to greater changes in acceptance of targeted behavior both early and late in therapy. In addition, change in behavioral frequency was strongly related to improvements in satisfaction early in therapy; however, in the 2nd half of therapy, emotional acceptance was more strongly related to changes in satisfaction. Research and clinical implications are discussed.

• Non-respiratory symptoms are common in acute and post-acute coronavirus disease 2019 (COVID-19), including many aspects of cardiovascular diseases (CVDs). • CVDs are still the leading cause of deaths globally. • Sufficient levels of regular physical activity (PA) are crucial for cardiovascular health, healthy bodyweight, and good mental health. • Regular PA reduces the risk of severe COVID-19 outcomes. • New techniques such as fitness tracking apps and wearables, online sports classes, tele-rehabilitations or simple training at home according to special exercise plans are promising tools to achieve regular PA in difficult situations such as lockdowns. Coronaviruses are pathogens thought to primarily affect the respiratory tracts of humans. The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 was also marked mainly by its symptoms of respiratory illness, which were named coronavirus disease 2019 (COVID-19). Since its initial discovery, many other symptoms have been linked to acute SARS-CoV-2 infections as well as to the long-term outcomes of COVID-19 patients. Among these symptoms are different categories of cardiovascular diseases (CVDs), which continue to be the main cause of death worldwide. The World Health Organization estimates that 17.9 million people die from CVDs each year, accounting for ∼32% of all deaths globally. Physical inactivity is one of the most important behavioral risk factors for CVDs. The COVID-19 pandemic has affected CVDs as well as the physical activity in different ways. Here, we provide an overview of the current status as well as future challenges and possible solutions. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper, based on naturalistic data, describes the acquisitional course and use of the articles "a" and "the" in young English-speaking children (18-61 months), with special emphasis on the role of individual variation. A growth modeling approach to the data reveals that children's individual acquisition schedules are similar in trend, but vary in the rate at which they omit determiners at a given point of time. This picture suggests that an analysis that presumes homogeneous development will seriously misrepresent the fluctuations between and within individuals. Interestingly, this variation does not reflect a variation in children's abilities to use determiners correctly--irrespective of the rate in which they used determiners, children seldom used determiners incorrectly. The analysis also reveals that children's optional omission of determiners in obligatory contexts, beginning at 18 months of age, gradually decreases on average by 3-4% a month until 36 months of age, and thereafter plunges by a factor of 10 to an average of 0.3% per month. At 36 month of age the majority of children use determiners at a near-mastery level (Brown, 1973). These findings provide a useful framework for theorizing about possible mechanisms underlying the nature of early language development pre- and post-36 months of age.

The extensive research on teacher quality has led to two conclusions. First, there are large and significant differences among teachers in terms of their capacity to improve student achievement. Second, these differences are not captured by common measures of teacher qualifications (E.A. Hanushek, Teacher quality, in: L.T. Izumi, W.M. Evers (Eds.), Teacher Quality, Hoover Press, Palo Alto, CA, 2002, pp. 1-12). We present the argument that in order to improve teacher quality, one must focus on teacher performance. By creating teaching standards and performance rubrics, rating teachers against those standards, and then employing a multivariate multilevel mixed statistical model to attribute students' achievement gains to teachers, we both designed and provided preliminary validation evidence for a system to judge teachers based on performance. Our results demonstrate that teaching performance as defined by our standards and rubrics is highly predictive of student academic progress across the elementary grades. Implications for our research to improve teaching through implementing performance pay systems are discussed.

Studying change in student achievement is of central importance in numerous areas of educational research, including efforts to monitor school performance, investigations of the effects of educational interventions over time, and school effects studies focusing on how differences in school policies and practices relate to differences in student progress. In this article, we argue that in studying patterns of change, it is often important to consider the relationship between where students start (i.e., their initial status) and how rapidly they progress (i.e., their rates of change). Drawing on recent advances in growth modeling methodology, we illustrate the potential value of such an approach in the context of monitoring school performance. In particular, we highlight the ways in which attending to initial status in analyses of student progress can help draw attention to possible concerns regarding the distribution of achievement within schools. To convey the logic of our approach and illustrate various analysis possibilities, we fit a series of growth models to the time series data for students in several schools in the Longitudinal Study of American Youth (LSAY) sample. In a final section, we discuss some of the possibilities that arise in employing a modeling approach of this kind in evaluating educational programs and in conducting school effects research. (Contains 8 figures, 7 tables and 12 notes.)

Developed and illustrated an analysis for detecting changes in multiple time series for a multilevel setting. Shows how the approach can be used to evaluate intervention effects associated with a treatment to which the lengths of delay in the response may be unique to each treated unit. The approach does not assume a known change point. (SLD)

A class of two-stage models is developed to accommodate three common characteristics of behavioral data: (1) its multivariate nature; (2) the typical small sample size; and (3) the possibility of missing observations. The model, as illustrated, permits estimation of the full spectrum of plausible measurement error structures. (SLD)