edited by Amanda Licastro and Benjamin Miller
University of Pittsburgh Press, 2021
Cloth: 978-0-8229-4674-8 | eISBN: 978-0-8229-8819-9
Library of Congress Classification PE1404.C6185 2021
Dewey Decimal Classification 808.0420285

ABOUT THIS BOOK | AUTHOR BIOGRAPHY | REVIEWS | TOC | REQUEST ACCESSIBLE FILE
ABOUT THIS BOOK

In a data-driven world, anything can be data. As the techniques and scale of data analysis advance, the need for a response from rhetoric and composition grows ever more pronounced. It is increasingly possible to examine thousands of documents and peer-review comments, labor-hours, and citation networks in composition courses and beyond. Composition and Big Data brings together a range of scholars, teachers, and administrators already working with big-data methods and datasets to kickstart a collective reckoning with the role that algorithmic and computational approaches can, or should, play in research and teaching in the field. Their work takes place in various contexts, including programmatic assessment, first-year pedagogy, stylistics, and learning transfer across the curriculum. From ethical reflections to database design, from corpus linguistics to quantitative autoethnography, these chapters implement and interpret the drive toward data in diverse ways.