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Physical Eloquence and the Biology of Writing
As a statement about literacy, this book recommends an approach to teaching writing that stresses the neurological foundations of written English, mastered almost like a foreign language. "Physical eloquence" refers to neurological processes of hand, eye, and ear that every writer must control in order to generate and simultaneously to interpret a written text. "Biology of writing" refers to innate or otherwise untaught abilities that all people have for acquiring prose and which are not enhanced by formal learning. Ochsner promotes a realistic writing curriculum that stresses subconscious processes in the biology of the writing process rather than planned, rehearsed, and formally practiced activities for learning to write. He concludes that successful literacy instruction depends on a teacher's willingness to take into account the supremacy of popular culture and the ascendancy of its spoken idiom.
Error Analysis in the World. A Bibliography
Linguistic errors are manifold, e.g. in the mother tongue, in the acquisition of foreign languages, in translations, as slip of the tongue or typo. The present compilation of all subject-related publications is a comprehensive bibliography for the field of linguistic errors. In a compact introduction, Bernd Spillner additionally provides an overview of linguistic, didactic and psycholinguistic methods of the analysis and assessment of the errors and their therapy. For the first time, publications from numerous countries around the world were included which have not yet been considered. With the attached CD-ROM making the bibliography searchable for keywords in many languages to find relevant publications among the more than 6.000 titles, this is a very useful handbook for all linguists and teachers.
After Whiteness
What comes after white becomes a minority in the United States.
The Cooperstown Symposium on Baseball and American Culture, 2000
This is an anthology of 19 papers that were presented at the Twelfth Cooperstown Symposium on Baseball and American Culture, held June 7-9, 2000 and co-sponsored by the State University of New York at Oneonta and the National Baseball Hall of Fame and Museum. Capped by Roger Kahn's essay on the rise and fall of great baseball prose, this Symposium plumbed such topics as baseball in the classroom, the national pastime and American Christianity, corporate encroachment, and the difficult course pursued by a Negro League team owner who also happened to be white and female. These essays, divided into sections titled "Baseball and Culture," "Baseball as History," "The Business of Baseball" and "Race, Gender and Ethnicity in the National Pastime," cut through the quick and easy judgments of the media and offer instead the longer, more informed view of scholars and researchers.
Using Evidence of Student Learning to Improve Higher Education
American higher education needs a major reframing of student learning outcomes assessment Dynamic changes are underway in American higher education. New providers, emerging technologies, cost concerns, student debt, and nagging doubts about quality all call out the need for institutions to show evidence of student learning. From scholars at the National Institute for Learning Outcomes Assessment (NILOA), Using Evidence of Student Learning to Improve Higher Education presents a reframed conception and approach to student learning outcomes assessment. The authors explain why it is counterproductive to view collecting and using evidence of student accomplishment as primarily a compliance activi...
Robust Regression
Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weight each observation discusses generalized properties of Lp-estimators. Includes an algorithm for identifying outliers using least absolute value criterion in regression modeling reviews redescending M-estimators studies Li linear regression proposes the best linear unbiased estimators for fixed parameters and random errors in the mixed linear model summarizes known properties of Li estimators for time series analysis examines ordinary least squares, latent root regression, and a robust regression weighting scheme and evaluates results from five different robust ridge regression estimators.
