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008			220601s2022 sz | s |||| 0|eng d
020			_a9783031021824
024	7		_a10.1007/978-3-031-02182-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aLB3060.37 _b2022 EB
100	1		_aKlebanov, Beata Beigman _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687400
245	1	0	_aAutomated Essay Scoring _cby Beata Beigman Klebanov, Nitin Madnani
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XX, 294 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_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.
988			_aSynthesis Collection of Technology_2022
650		7	_2embne _9147775 _aTests escolares _xProceso de datos
650		7	_2embne _9158738 _aProceso en lenguaje natural (Informática)
650		7	_2embne _9158274 _aEvaluación educativa _xProceso de datos
700	1		_aMadnani, Nitin _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687459
776	0	8	_iPrinted edition: _z9783031001932
776	0	8	_iPrinted edition: _z9783031010545
776	0	8	_iPrinted edition: _z9783031033100
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02182-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI