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Roles of working memory, syllogistic inferencing ability, and linguistic knowledge on second language listening comprehension for passages of different lengths ...
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Roles of working memory, syllogistic inferencing ability, and linguistic knowledge on second language listening comprehension for passages of different lengths ...
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Precision communication: Physicians’ linguistic adaptation to patients’ health literacy
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In: Sci Adv (2021)
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Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study
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In: Health Serv Res (2020)
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Please, Please, Just Tell Me: The Linguistic Features of Humorous Deception
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In: Dialogue & Discourse; Vol 11 No 2 (2020); 128-149 ; 2152-9620 (2020)
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Applying Natural Language Processing Tools to a Student Academic Writing Corpus: How Large are Disciplinary Differences Across Science and Engineering Fields?
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In: English Publications (2017)
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To Aggregate or Not? Linguistic Features in Automatic Essay Scoring and Feedback Systems
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In: Journal of Writing Assessment, vol 8, iss 1 (2015)
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Abstract:
This study investigates the relative efficacy of using linguistic micro-features, the aggregation of such features, and a combination of micro-features and aggregated features in developing automatic essay scoring (AES) models. Although the use of aggregated features is widespread in AES systems (e.g., e-rater; Intellimetric), very little published data exists that demonstrates the superiority of using such a method over the use of linguistic micro-features or combination of both micro-features and aggregated features. The results of this study indicate that AES models comprised of micro-features and a combination of micro-features and aggregated features outperform AES models comprised of aggregated features alone. The results also indicate that that AES models based on micro-features and a combination of micro-features and aggregated features provide a greater variety of features with which to provide formative feedback to writers. These results have implications for the development of AES systems and for providing automatic feedback to writers within these systems.
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URL: https://escholarship.org/uc/item/1f21q8ck
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Linguistic microfeatures to predict L2 writing proficiency: A case study in Automated Writing Evaluation
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In: Journal of Writing Assessment, vol 7, iss 1 (2014)
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What's so simple about simplified texts? A computational and psycholinguistic investigation of text comprehension and text processing
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