Cargando…

Composition and big data /

"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 citatio...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Licastro, Amanda (Editor ), Miller, Benjamin (Poet) (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Pittsburgh, PA : University of Pittsburgh Press, [2021]
Colección:Pittsburgh series in composition, literacy, and culture.
Temas:
Acceso en línea:Texto completo

MARC

LEADER 00000cam a2200000 i 4500
001 JSTOR_on1284980993
003 OCoLC
005 20231005004200.0
006 m o d
007 cr cnu---unuuu
008 211110s2021 paua ob 001 0 eng d
040 |a YDX  |b eng  |e rda  |e pn  |c YDX  |d YDX  |d EBLCP  |d JSTOR  |d N$T  |d P@U  |d WAU  |d OCLCO  |d OCLCQ  |d OCLCO  |d K6U  |d UKAHL  |d OCLCQ 
019 |a 1285017041  |a 1285051834 
020 |a 0822988194  |q (electronic book) 
020 |a 9780822988199  |q (electronic bk.) 
020 |z 9780822946748 
020 |z 0822946742 
029 1 |a AU@  |b 000070239821 
035 |a (OCoLC)1284980993  |z (OCoLC)1285017041  |z (OCoLC)1285051834 
037 |a 22573/ctv22rtrx4  |b JSTOR 
050 4 |a PE1404  |b .C6185 2021 
072 7 |a LAN  |x 000000  |2 bisacsh 
072 7 |a LAN  |x 015000  |2 bisacsh 
082 0 4 |a 808/.0420285  |2 23 
049 |a UAMI 
245 0 0 |a Composition and big data /  |c edited by Amanda Licastro and Benjamin Miller. 
264 1 |a Pittsburgh, PA :  |b University of Pittsburgh Press,  |c [2021] 
300 |a 1 online resource (xi, 316 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Pittsburgh series in composition, literacy, and culture 
505 0 |a ! Learning to read again : introducing undergraduates to critical distant reading, machine analysis, and data in humanities writing /! Trevor Hoag and Nicole Emmelhainz --! A corpus of first-year composition : exploring stylistic complexity in student writing /! Chris Holcomb and Duncan A. Buell --! Expanding our repertoire : corpus analysis and the moves of synthesis /! Alexis Teagarden --! Localizing big data : using computational methodologies to support programmatic assessment /! David Reamer and Kyle McIntosh --! Big data as mirror : writing analytics and assessing assignment genres /! Laura Aull --! Peer review in first-year composition and STEM courses : a large-scale corpus anaylsis of key writing terms /! Chris M. Anson, Ian G. Anson, and Kendra Andrews --! Moving from categories to continuums : how corpus analysis tools reveal disciplinary tension in context /! Kathryn Lambrecht --! From 1993 to 2017 : exploring "a giant cache of (disciplinary) lore" on WPA-L /! Jenna Morton-Aiken --! Big-time disciplinarity : measuring professional consequences in candles and clocks /! Kate Pantelides and Derek Mueller --! The boutique is open : data for writing studies /! Cheryl E. Ball, Tarez Samra Graban, and Michelle Sidler --! Ethics, the IRBs, and big data research : toward disciplinary datasets in composition /! Johanna Phelps --! Ethics in big data composition research : cybersecurity and algorithmic accountablitiy as best practices /! Andrew Kulak --! Data do not speak for themselves : interpretation and model selection in unsupervised automated text analysis /! Juho Paakkonen --! "Unsupervised learning" : reflections on a first foray into data-driven argument /! Romeo Garcia --! Making do : working with missing and broken data /! Jill Dahlman. 
520 |a "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"--  |c Provided by publisher 
590 |a JSTOR  |b Books at JSTOR All Purchased 
590 |a JSTOR  |b Books at JSTOR Demand Driven Acquisitions (DDA) 
650 0 |a English language  |x Rhetoric  |x Computer-assisted instruction. 
650 0 |a English language  |x Rhetoric  |x Study and teaching. 
650 0 |a Online data processing  |x Authorship  |x Study and teaching. 
650 0 |a Big data. 
650 0 |a Computational linguistics. 
650 0 |a Digital humanities. 
650 6 |a Anglais (Langue)  |x Rhétorique  |x Enseignement assisté par ordinateur. 
650 6 |a Données volumineuses. 
650 6 |a Linguistique informatique. 
650 6 |a Sciences humaines numériques. 
650 7 |a computational linguistics.  |2 aat 
650 7 |a digital humanities.  |2 aat 
650 7 |a LANGUAGE ARTS & DISCIPLINES  |x General.  |2 bisacsh 
650 7 |a English language  |x Rhetoric  |x Study and teaching.  |2 fast  |0 (OCoLC)fst00911595 
650 7 |a English language  |x Rhetoric  |x Computer-assisted instruction.  |2 fast  |0 (OCoLC)fst00911585 
650 7 |a Digital humanities.  |2 fast  |0 (OCoLC)fst00963599 
650 7 |a Computational linguistics.  |2 fast  |0 (OCoLC)fst00871998 
650 7 |a Big data.  |2 fast  |0 (OCoLC)fst01892965 
700 1 |a Licastro, Amanda,  |e editor. 
700 1 |a Miller, Benjamin  |c (Poet),  |e editor. 
776 0 8 |i Print version:  |z 9780822946748  |z 0822946742  |w (DLC) 2021032860  |w (OCoLC)1152506929 
830 0 |a Pittsburgh series in composition, literacy, and culture. 
856 4 0 |u https://jstor.uam.elogim.com/stable/10.2307/j.ctv22tnmg2  |z Texto completo 
938 |a Askews and Holts Library Services  |b ASKH  |n AH39491799 
938 |a ProQuest Ebook Central  |b EBLB  |n EBL28932922 
938 |a EBSCOhost  |b EBSC  |n 3091656 
938 |a Project MUSE  |b MUSE  |n musev2_94705 
938 |a YBP Library Services  |b YANK  |n 302563425 
994 |a 92  |b IZTAP