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Robert-Mihai Botarleanu; Mihai Dascalu; Scott Andrew Crossley; Danielle S. McNamara – Grantee Submission, 2022
The ability to express yourself concisely and coherently is a crucial skill, both for academic purposes and professional careers. An important aspect to consider in writing is an adequate segmentation of ideas, which in turn requires a proper understanding of where to place paragraph breaks. However, these decisions are often performed…
Descriptors: Paragraph Composition, Text Structure, Automation, Identification
Dascalu, Marina-Dorinela; Ruseti, Stefan; Dascalu, Mihai; McNamara, Danielle; Trausan-Matu, Stefan – Grantee Submission, 2020
Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to visualize text cohesion both within (intra) and…
Descriptors: Network Analysis, Graphs, Connected Discourse, Reading Comprehension
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Allen, Laura Kristen; Magliano, Joseph P.; McCarthy, Kathryn S.; Sonia, Allison N.; Creer, Sarah D.; McNamara, Danielle S. – Grantee Submission, 2021
The current study examined the extent to which the cohesion detected in readers' constructed responses to multiple documents was predictive of persuasive, source-based essay quality. Participants (N=95) completed multiple-documents reading tasks wherein they were prompted to think-aloud, self-explain, or evaluate the sources while reading a set of…
Descriptors: Reading Comprehension, Connected Discourse, Reader Response, Natural Language Processing
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
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…
Descriptors: Network Analysis, Reading Comprehension, Automation, Artificial Intelligence
Cioaca, Valentin Sergiu; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2021
Numerous approaches have been introduced to automate the process of text summarization, but only few can be easily adapted to multiple languages. This paper introduces a multilingual text processing pipeline integrated in the open-source "ReaderBench" framework, which can be retrofit to cover more than 50 languages. While considering the…
Descriptors: Documentation, Computer Software, Open Source Technology, Algorithms
Flynn, Lauren E.; McNamara, Danielle S.; McCarthy, Kathryn S.; Magliano, Joseph P.; Allen, Laura K. – Grantee Submission, 2021
Successful text comprehension requires readers to engage in a number of coherence-building processes. This study examined how analyzing the cohesion of students 'constructed responses can be used to evaluate these coherence-building processes and the extent to which they vary across readers' individual differences and across types of texts. We…
Descriptors: Reading Comprehension, Individual Differences, Protocol Analysis, Literary Genres
Li, Haiying; Graesser, Art C. – Grantee Submission, 2020
This study investigated how computer agents' language style affects summary writing in an Intelligent Tutoring System, called CSAL AutoTutor. Participants interacted with two computer agents in one of three language styles: (1) a "formal" language style; (2) an "informal" language style; and (3) a "mixed" language…
Descriptors: Intelligent Tutoring Systems, Language Styles, Writing (Composition), Writing Improvement
Sonia, Allison N.; Joseph, Magliano P.; McCarthy, Kathryn S.; Creer, Sarah D.; McNamara, Danielle S.; Allen, Laura K. – Grantee Submission, 2022
The constructed responses individuals generate while reading can provide insights into their coherence-building processes. The current study examined how the cohesion of constructed responses relates to performance on an integrated writing task. Participants (N = 95) completed a multiple document reading task wherein they were prompted to think…
Descriptors: Natural Language Processing, Connected Discourse, Reading Processes, Writing Skills
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
Rod D. Roscoe; Kyrsten Novak; Amanda King; Melissa M. Patchan – Grantee Submission, 2018
Educational technologies with multimedia content can support effective learning, but these outcomes are moderated by learners' level of cognitive engagement or self-regulation. As a way to encourage deeper cognitive engagement without redesigning or redeveloping software (e.g., building more prompts, scaffolds, or automated support), this study…
Descriptors: Educational Technology, Multimedia Instruction, Student Role, Learner Engagement
Joseph P. Magliano; Lauren Flynn; Daniel P. Feller; Kathryn S. McCarthy; Danielle S. McNamara; Laura Allen – Grantee Submission, 2022
The goal of this study was to assess the relationships between computational approaches to analyzing constructed responses made during reading and individual differences in the foundational skills of reading in college readers. We also explored if these relationships were consistent across texts and samples collected at different institutions and…
Descriptors: Semantics, Computational Linguistics, Individual Differences, Reading Materials
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Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara; Philippe Dessus; Stefan Trausan-Matu – Grantee Submission, 2018
A critical task for tutors is to provide learners with suitable reading materials in terms of difficulty. The challenge of this endeavor is increased by students' individual variability and the multiple levels in which complexity can vary, thus arguing for the necessity of automated systems to support teachers. This chapter describes…
Descriptors: Reading Materials, Difficulty Level, Natural Language Processing, Artificial Intelligence
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Crossley, Scott A.; McNamara, Danielle S. – Grantee Submission, 2016
This study examines links between essay quality and text elaboration and text cohesion. For this study, 35 students wrote two essays (on two different prompts) and for each, were given 15 minutes to elaborate on their original text. An expert in discourse comprehension then modified the original and elaborated essays to increase cohesion,…
Descriptors: Essays, Writing Assignments, Writing Skills, Connected Discourse
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Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2017
The current study examined the degree to which the quality and characteristics of students' essays could be modeled through dynamic natural language processing analyses. Undergraduate students (n = 131) wrote timed, persuasive essays in response to an argumentative writing prompt. Recurrent patterns of the words in the essays were then analyzed…
Descriptors: Writing Evaluation, Essays, Persuasive Discourse, Natural Language Processing
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Allen, Laura K.; Jacovina, Matthew E.; McNamara, Danielle S. – Grantee Submission, 2016
This study investigates how cohesion manifests in readers' thought processes while reading texts when they are instructed to engage in self-explanation, a strategy associated with deeper, more successful comprehension. In Study 1, college students (n = 21) were instructed to either paraphrase or self-explain science texts. Paraphrasing was…
Descriptors: Reading Comprehension, Reading Processes, Reading Strategies, Protocol Analysis
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