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020 _a9783031021824
_9978-3-031-02182-4
024 7 _a10.1007/978-3-031-02182-4
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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072 7 _aUYQ
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082 0 4 _a006.3
_223
100 1 _aKlebanov, Beata Beigman.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980729
245 1 0 _aAutomated Essay Scoring
_h[electronic resource] /
_cby Beata Beigman Klebanov, Nitin Madnani.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXX, 294 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Human Language Technologies,
_x1947-4059
505 0 _aPreface -- Building an Automated Essay Scoring System -- From Lessons to Guidelines -- Models -- Generic Features -- Genre- and Task-Specific Features -- Automated Scoring Systems: From Prototype to Production -- Evaluating for Real-World Use -- Automated Feedback -- Automated Scoring of Content -- Automated Scoring of Speech -- Fooling the System: Gaming Strategies -- Looking Back, Looking Ahead -- Definitions-in-Context -- Index -- References -- Authors' Biographies.
520 _aThis book discusses the state of the art of automated essay scoring, its challenges and its potential. One of the earliest applications of artificial intelligence to language data (along with machine translation and speech recognition), automated essay scoring has evolved to become both a revenue-generating industry and a vast field of research, with many subfields and connections to other NLP tasks. In this book, we review the developments in this field against the backdrop of Elias Page's seminal 1966 paper titled "The Imminence of Grading Essays by Computer." Part 1 establishes what automated essay scoring is about, why it exists, where the technology stands, and what are some of the main issues. In Part 2, the book presents guided exercises to illustrate how one would go about building and evaluating a simple automated scoring system, while Part 3 offers readers a survey of the literature on different types of scoring models, the aspects of essay quality studied in prior research,and the implementation and evaluation of a scoring engine. Part 4 offers a broader view of the field inclusive of some neighboring areas, and Part \ref{part5} closes with summary and discussion. This book grew out of a week-long course on automated evaluation of language production at the North American Summer School for Logic, Language, and Information (NASSLLI), attended by advanced undergraduates and early-stage graduate students from a variety of disciplines. Teachers of natural language processing, in particular, will find that the book offers a useful foundation for a supplemental module on automated scoring. Professionals and students in linguistics, applied linguistics, educational technology, and other related disciplines will also find the material here useful.
650 0 _aArtificial intelligence.
_93407
650 0 _aNatural language processing (Computer science).
_94741
650 0 _aComputational linguistics.
_96146
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aNatural Language Processing (NLP).
_931587
650 2 4 _aComputational Linguistics.
_96146
700 1 _aMadnani, Nitin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980730
710 2 _aSpringerLink (Online service)
_980731
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031001932
776 0 8 _iPrinted edition:
_z9783031010545
776 0 8 _iPrinted edition:
_z9783031033100
830 0 _aSynthesis Lectures on Human Language Technologies,
_x1947-4059
_980732
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02182-4
912 _aZDB-2-SXSC
942 _cEBK
999 _c85024
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