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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 Hits 1 – 20 of 89 1 Precision communication: Physicians’ linguistic adaptation to patients’ health literacy Schillinger, Dean; Duran, Nicholas D.; McNamara, Danielle S.... In: Sci Adv (2021) BASE Show details 2 Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links Dascalu, Maria-Dorinela; Ruseti, Stefan; Dascalu, Mihai... In: Artificial Intelligence in Education (2020) BASE Show details 3 Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study Schillinger, Dean; Balyan, Renu; Crossley, Scott A.... In: Health Serv Res (2020) BASE Show details 4 Extended Multi-document Cohesion Network Analysis Centered on Comprehension Prediction Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. In: Artificial Intelligence in Education (2020) Abstract: Theories of discourse argue that comprehension depends on the coherence of the learner’s mental representation. Our aim is to create a reliable automated representation to estimate readers’ level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network Analysis to model a cohesion graph composed of semantic links between multiple reference texts and student productions. From this graph, a set of features was derived and used to build machine learning models to predict student comprehension scores. In this paper, we build on top of the previous study by: a) extending the CNA graph by adding new semantic links targeting specific sentences that should have been captured within the learner’s productions, and b) cleaning the self-explanations by eliminating frozen expression, as well as entries which seemed nearly identical to the source text. The results are in line with the conclusions of the previous study regarding the importance of both self-explanations and question answers in predicting the students’ reading comprehension level. They also outline the limitations of our feature generation approach, in which no substantial improvements were detected, despite adding more fine-grained features. Keyword: Article URL: https://doi.org/10.1007/978-3-030-52240-7_42 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334696/ BASE Hide details 5 Sequence-to-Sequence Models for Automated Text Simplification Botarleanu, Robert-Mihai; Dascalu, Mihai; Crossley, Scott Andrew... In: Artificial Intelligence in Education (2020) BASE Show details 6 Challenges and solutions to employing natural language processing and machine learning to measure patients’ health literacy and physician writing complexity: The ECLIPPSE study Brown, William; Balyan, Renu; Karter, Andrew J.... In: J Biomed Inform (2020) BASE Show details 7 Secure Messaging with Physicians by Proxies for Patients with Diabetes: Findings from the ECLIPPSE Study Semere, Wagahta; Crossley, Scott; Karter, Andrew J.... In: J Gen Intern Med (2019) BASE Show details 8 Writing flexibility in argumentative essays: a multidimensional analysis [<Journal>] Allen, Laura K. [Verfasser]; Likens, Aaron D. [Verfasser]; McNamara, Danielle S. [Verfasser] DNB Subject Category Language Show details 9 Incorporating Learning Characteristics into Automatic Essay Scoring Models: What Individual Differences and Linguistic Features Tell Us about Writing Quality ... Crossley, Scott; Allen, Laura K.; Snow, Erica L.. - : Zenodo, 2016 BASE Show details 10 Incorporating Learning Characteristics into Automatic Essay Scoring Models: What Individual Differences and Linguistic Features Tell Us about Writing Quality ... Crossley, Scott; Allen, Laura K.; Snow, Erica L.. - : Zenodo, 2016 BASE Show details 11 To Aggregate or Not? Linguistic Features in Automatic Essay Scoring and Feedback Systems Crossley, Scott A.; Kyle, Kristopher; McNamara, Danielle S. In: Journal of Writing Assessment, vol 8, iss 1 (2015) BASE Show details 12 Automated evaluation of text and discourse with Coh-Metrix McNamara, Danielle S.. - New York [u.a.] : Cambridge Univ. Press, 2014 Leibniz-Zentrum Allgemeine Sprachwissenschaft Show details 13 Does writing development equal writing quality? A computational investigation of syntactic complexity in L2 learners Crossley, Scott A.; McNamara, Danielle S. In: Journal of second language writing. - Amsterdam ˜[u.a]œ : Elsevier 26 (2014), 66-79 OLC Linguistik Show details 14 Analyzing Discourse Processing Using a Simple Natural Language Processing Tool Crossley, Scott A.; Allen, Laura K.; Kyle, Kristopher... In: Discourse processes. - London [u.a.] : Routledge, Taylor and Francis Group 51 (2014) 5, 511-534 OLC Linguistik Show details 15 Society for Text and Discourse Annual Meeting 2013: Introduction to the Special Issue McNamara, Danielle S.; Schober, Michael F. In: Discourse processes. - London [u.a.] : Routledge, Taylor and Francis Group 51 (2014) 5, 357-358 OLC Linguistik Show details 16 What Is Successful Writing? An Investigation Into the Multiple Ways Writers Can Write Successful Essays Crossley, Scott A.; Roscoe, Rod; McNamara, Danielle S. In: Written communication. - Beverly Hills, Calif. [u.a.] : Sage Publ. 31 (2014) 2, 184-214 OLC Linguistik Show details 17 Emergent behaviors in computer-based learning environments: Computational signals of catching up Snow, Erica L.; Jackson, G. Tanner; McNamara, Danielle S. In: Computers in human behavior. - Amsterdam [u.a.] : Elsevier 41 (2014), 62-70 OLC Linguistik Show details 18 Analyzing discourse processing using a simple natural language processing tool Crossley, Scott A.; Allen, Laura K.; Kyle, Kristopher... In: Discourse Processes 51 (2014) 5, 511-534 IDS Bibliografie zur Gesprächsforschung Show details 19 Linguistic microfeatures to predict L2 writing proficiency: A case study in Automated Writing Evaluation Crossley, Scott A.; Kyle, Kristopher; Allen, Laura K.... In: Journal of Writing Assessment, vol 7, iss 1 (2014) BASE Show details 20 What's so simple about simplified texts? A computational and psycholinguistic investigation of text comprehension and text processing Crossley, Scott A.; Yang, Hae Sung; McNamara, Danielle S.. - : University of Hawaii National Foreign Language Resource Center, 2014. : Center for Language & Technology, 2014 BASE Show details Page: 1 2 3 4 5

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