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1947-4040 a scoring engine. Part 4 offers a broader view of the field inclusive of some neighboring areas, and Part
ef{part5} closes with summary and discussion. This bo978-3-031-01054-5978-3-031-02182-4Series ISSN 1947-4040 Series E-ISSN 1947-4059
1947-4040 rtificial 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 developm
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Genre- and Task-Specific Featuressummarization. The extent of variation in the tasks we review here, as well as in approaches developed for capturing task-specific elements, suggests clearly that assessment of writing is not a one-size-fits-all kind of endeavor.
Looking Back, Looking Aheadw far the field has come, against the backdrop of the expectations and the hurdles laid out in that paper. The discussion in this chapter draws heavily on the theme paper on automated essay scoring presented by the authors at the 2020 meeting of the Association for Computational Linguistics (Beigman Klebanov & Madnani, 2020).
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978-3-031-01054-5Springer Nature Switzerland AG 2022