Quality Research in Literacy and Science Education
International Perspectives and Gold Standards
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Beschreibung
This book addresses implications for "Gold Standards" of education research—especially in science education and literacy. These standards are meant to provide evidence-based educational outcomes found effective in randomized controlled trials, following patterns of evidence used in medical research. Similar expectations have emerged in other countries—from education ministries, for researchers working with U.S. colleagues, and for researchers with multinational and non-profit support.
The current "Gold Standard" policy, developed in the United States through the 2001 "No Child Left Behind" [NCLB] Act and the 2002 Education Sciences Reform Act, attempts to improve the effects of schooling and enhance educational research. The contributions to this book explore perspectives on how best to implement multiple standards of education research.
Statistical models attempt to describe and quantify relationships between variables. In the models presented in this chapter, there is a response variable (sometimes called dependent variable) and at least one predictor variable (sometimes called independent or explanatory variable). When investigating a possible cause-and-effect type of relationship, the response variable is the putative effect and the predictors are the hypothesized causes. Typically, there is a main predictor variable of interest; other predictors in the model are called covariates. Unknown covariates or other independent variables not controlled in an experiment or analysis can affect the dependent or outcome variable and mislead the conclusions made from the inquiry (Bock, Velleman, & De Veaux, 2009). A p value (p) measures the statistical significance of the observed relationship; given the model, p is the probability that a relationship is seen by mere chance. The smaller the p value, the more confident we can be that the pattern seen in the data 2 is not random. In the type of models examined here, the R measures the prop- tion of the variation in the response variable that is explained by the predictors 2 specified in the model; if R is close to 1, then almost all the variation in the response variable has been explained. This measure is also known as the multiple correlation coefficient. Statistical studies can be grouped into two types: experimental and observational.
Provides uniquely international perspectives on modern applications of research methods in education Demonstrates how researchers and educators in science education and literacy can strengthen their findings and have more impact on teachers’ classroom practice and students’ learning Shows how those who make education policy can be informed and their decisions affected by researchers Deepens and broadens communications among the fields of education, statistics, political science, and public policy Attempts to bring unity to the quantitative and qualitative research traditions
Autor*in
Mack C. Shelley
Themen in »Quality Research in Literacy and Science Education«
Evaluation PISA education education research educational research evidence-based practice gold standard mathematics mixed-methods research no child left behind public policy randomized controlled trails
Stimmen zu »Quality Research in Literacy and Science Education«
The strength of this book, its inclusion of many perspectives that include political and policy pressures, budget priorities, task force reports, research complexities, curriculum complexities, and teaching-learning complexities, will be appreciated by many who see "No Childe Left Behing" and "high-stakes testing" as overly simplistic and potentially harmfull to education. It contains important information and valuable insight into the complexities of conducting quality sience literacy research in particular and education research in general. Also, the emphasis on producing research that can be understood and used properly by policy makers at local, state, and national levels is a strength of the book. I have been in the science education research field for over 40 years, including a stint as editor of the Journal of Research in Science Teaching, and I can say that I profited from reading this book.
Ron Good, Professor Emeritus, Louisiana State University and Florida State University, USA
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