First-Year Composition as 'Big Data': Towards Examining Student Revisions at Scale
| Autor: | Duncan A. Buell, Chris Holcomb |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
060201 languages & linguistics
Linguistics and Language General Computer Science Process (engineering) business.industry 05 social sciences Big data 050301 education 06 humanities and the arts Minor (academic) Language and Linguistics Education First-year composition Phenomenon Scale (social sciences) 0602 languages and literature ComputingMilieux_COMPUTERSANDEDUCATION Mathematics education Situational ethics business Psychology 0503 education Composition (language) |
| Zdroj: | Computers and Composition. 48:49-66 |
| ISSN: | 8755-4615 |
| Popis: | Given the central role revision plays in our First-Year Composition (FYC) program and the enormous number of papers students produce each semester across all course sections, we approached student revision as a “big data” phenomenon, assembling a large corpus of student papers and developing software to process them. Unlike past studies of revision which found that students focus almost exclusively on minor edits and surface errors, we found that student revisions primarily involve deleting and, more frequently, inserting complete sentences. After describing our software and reviewing its results, we examine several situational variables that may influence this unanticipated practice, and discuss ways to integrate revision more fully into the writing classroom. |
| Databáze: | OpenAIRE |
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