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In November 2000, the Board on International Comparative Studies in Education (BICSE) held a symposium to draw on the wealth of experience gathered over a four-decade period, to evaluate improvement in the quality of the methodologies used in international studies, and to identify the most pressing methodological issues that remain to be solved. Since 1960, the United States has participated in 15 large-scale cross-national education surveys. The most assessed subjects have been science and mathematics through reading comprehension, geography, nonverbal reasoning, literature, French, English as a foreign language, civic education, history, computers in education, primary education, and second-language acquisition. The papers prepared for this symposium and discussions of those papers make up the volume, representing the most up-to-date and comprehensive assessment of methodological strengths and weaknesses of international comparative studies of student achievement. These papers answer the following questions: (1) What is the methodological quality of the most recent international surveys of student achievement? How authoritative are the results? (2) Has the methodological quality of international achievement studies improved over the past 40 years? and (3) What are promising opportunities for future improvement?
This special issue is based on a workshop which began with a description and examination of the current National Assessment of Educational Progress (NAEP) standard-setting model, then looked to standard-setting applications outside of education. These applications included those that focus on human performance and the adequacy of human performance; in these contexts, raters were asked to focus on the knowledge and skills that underlie competent performance. Researchers also examined applications that focus on the impact of environmental agents on life and the ecology; in these cases, raters began with the knowledge that more (or less) of a substance is better and, as for NAEP, the judgment task was to determine "how good is good enough." They wished to examine parallels in the objectives, empirical grounding, judgmental requirements, and policy tensions for standard setting in NAEP and in other domains. These papers were commissioned to examine the current state of affairs and residual issues with respect to achievement-level setting in NAEP and to help determine whether the models and methods used in other disciplines have useful application to education. It is important to note that the papers represent the authors' views, not necessarily those of the committee or National Research Council. This issue and the workshop discussion point out a number of analogies between the objectives, requisite data, judgment requirements and policy issues for NAEP and other applications. The editors hope that this issue and wide distribution of these papers will prompt others to join in this interesting analysis and debate.
This dissertation is a three-piece dissertation, including two empirical research (Chapter 1 and Chapter 2) and a methodological improvement of prior work (Chapter 3), to address issues of the effects of approaches to learning on academic achievement in childhood and power analysis for a three-level model in meta-analysis. Approaches to learning as a key domain of school readiness has shown significant effects on student academic achievement. The study in Chapter 1 was designed to examine the potential moderation effects of problem behaviors on the association between approaches to learning and academic achievement (mathematics, reading, and science) in early grades using a recent nationwide longitudinal dataset (ECLS-K:2011). The correlated random effects estimation was applied to deal with the omitted variable issue. At the same time, the estimation method was allowed to compute the impacts of important time-constant variables (e.g., socioeconomic status) on academic achievement. The results indicated non-significant moderation effects of problem behaviors on the relations between approaches to learning and academic outcomes. However, the main effects of approaches to learning were significant associated with academic achievement. Complete data analysis and bootstrap with multiple imputation were conducted in the research to address the missing data issue in large-scale assessments. Similar results were shown in the two approaches, which demonstrated robust findings in the study. To better understand the general relations of approaches to learning on academic performance in childhood in recent years, the study in Chapter 2 conducted a systematic review employing meta-analytic methodology to combine and summarize the results from empirical quasi-experimental studies. The study filled the literature gap and extended the theory to understand the relations between approaches to learning and achievement. The results indicated medium effect sizes of the relations on approaches to learning and concurrent/future achievement (reading and mathematics). The effects on reading achievement were slightly larger than the effects on mathematics achievement. The single timepoint evidence showed stronger effects compared with longitudinal designs. In conclusion, the meta-analysis emphasized the positive and significant effects of approaches to learning on academic achievement in childhood. The methodological improvement in Chapter 3 aimed to address the potential biased power statistics when introducing group dependence in meta-analysis. The study extended the prior work about power analysis for two-level random-effects models to three-level models in the univariate case. The three-level model assumed research teams/labs at the third level. A three-level random-effects model provides more accurate estimates of power under the assumption that variability between research teams is not negligible. Each model in the study was followed by an illustrated example to show how to calculate the power. A simulation study provided evidence about how group-level heterogeneity affected statistical power in meta-analysis in the three-level model. The present study introduced more complicated data structures in meta-analysis and provided the power measures in advanced meta-analytic models.
This book focuses on the effect of psychological, social and demographic variables on student achievement and summarizes the current research findings in the field. It addresses the need for inclusive and interpretive studies in the field in order to interpret student achievement literature and suggests new pathways for further studies. Appropriately, a meta-analysis approach is used by the contributors to show the big picture to the researchers by analyzing and combining the findings from different independent studies. In particular, the authors compile various studies examining the relationship between student achievement and 21 psychological, social and demographic variables separately. The philosophy behind this book is to direct future research and practices rather than addressing the limits of current studies.
Due to the COVID-19 pandemic, the fields of health and education have been extensively revisited worldwide. This book addresses the importance of wellbeing in education. Health and Academic Achievement - New Findings provides recent reflections on the quality of informal learning environments in preschool-aged children, the acceptance of employing online education professionals, the mental health of teachers and students, and the challenges posed by current teaching and learning strategies during COVID-19. This book focuses on human behavior in health and education and will be of interest to readers in fields ranging from biology to sociology as well as readers interested in wellbeing and mental health.
State education departments and school districts face an important challenge in implementing a new law that requires disadvantaged students to be held to the same standards as other students. The new requirements come from provisions of the 1994 reauthorization of Title I, the largest federal effort in precollegiate education, which provides aid to "level the field" for disadvantaged students. Testing, Teaching, and Learning is written to help states and school districts comply with the new law, offering guidance for designing and implementing assessment and accountability systems. This book examines standards-based education reform and reviews the research on student assessment, focusing on the needs of disadvantaged students covered by Title I. With examples of states and districts that have track records in new systems, the committee develops a practical "decision framework" for education officials. The book explores how best to design assessment and accountability systems that support high levels of student learning and to work toward continuous improvement. Testing, Teaching, and Learning will be an important tool for all involved in educating disadvantaged studentsâ€"state and local administrators and classroom teachers.
People providing services to schools, teachers, and students want to know whether these services are effective. With that knowledge, a project director can expand services that work well and adjust implementation of activities that are not working as expected. When finding that an innovative strategy benefits students, a project director might want to share that information with other service providers who could build upon that strategy. Some organizations that fund programs for students will want a report demonstrating the program’s success. Determining whether a program is effective requires expertise in data collection, study design, and analysis. Not all project directors have this expertise—they tend to be primarily focused on working with schools, teachers, and students to undertake program activities. Collecting and obtaining student-level data may not be a routine part of the program. This book provides an overview of the process for evaluating a program. It is not a detailed methodological text but focuses on awareness of the process. What do program directors need to know about data and data analysis to plan an evaluation or to communicate with an evaluator? Examples focus on supporting college and career readiness programs. Readers can apply these processes to other studies that include a data collection component.