Publication Date
| In 2024 | 0 |
| Since 2023 | 4 |
| Since 2020 (last 5 years) | 20 |
| Since 2015 (last 10 years) | 25 |
| Since 2005 (last 20 years) | 25 |
Descriptor
| Natural Language Processing | 17 |
| Reading Comprehension | 16 |
| Models | 12 |
| Semantics | 11 |
| Artificial Intelligence | 8 |
| Computational Linguistics | 8 |
| Scores | 7 |
| Computer Software | 6 |
| Graphs | 6 |
| Network Analysis | 6 |
| Prediction | 6 |
| More ▼ | |
Source
| Grantee Submission | 25 |
Author
Publication Type
| Reports - Research | 22 |
| Speeches/Meeting Papers | 20 |
| Reports - Descriptive | 3 |
| Journal Articles | 2 |
Education Level
| Higher Education | 6 |
| Postsecondary Education | 5 |
| Adult Education | 1 |
| Elementary Education | 1 |
| High Schools | 1 |
| Secondary Education | 1 |
Audience
Location
| Romania | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| Flesch Reading Ease Formula | 1 |
What Works Clearinghouse Rating
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…
Descriptors: Phrase Structure, Networks, Semantics, Feedback (Response)
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
Botarleanu, Robert-Mihai; Dascalu, Mihai; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2020
A key writing skill is the capability to clearly convey desired meaning using available linguistic knowledge. Consequently, writers must select from a large array of idioms, vocabulary terms that are semantically equivalent, and discourse features that simultaneously reflect content and allow readers to grasp meaning. In many cases, a simplified…
Descriptors: Natural Language Processing, Writing Skills, Difficulty Level, Reading Comprehension
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
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
Panaite, Marilena; Ruseti, Stefan; Dascalu, Mihai; Balyan, Renu; McNamara, Danielle S.; Trausan-Matu, Stefan – Grantee Submission, 2019
Intelligence Tutoring Systems (ITSs) focus on promoting knowledge acquisition, while providing relevant feedback during students' practice. Self-explanation practice is an effective method used to help students understand complex texts by leveraging comprehension. Our aim is to introduce a deep learning neural model for automatically scoring…
Descriptors: Computer Assisted Testing, Scoring, Intelligent Tutoring Systems, Natural Language Processing
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2019
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: Prediction, Reading Comprehension, Network Analysis, Information Sources
Dascalu, Mihai; Jacovina, Matthew E.; Soto, Christian M.; Allen, Laura K.; Dai, Jianmin; Guerrero, Tricia A.; McNamara, Danielle S. – Grantee Submission, 2017
iSTART is a web-based reading comprehension tutor. A recent translation of iSTART from English to Spanish has made the system available to a new audience. In this paper, we outline several challenges that arose during the development process, specifically focusing on the algorithms that drive the feedback. Several iSTART activities encourage…
Descriptors: Spanish, Reading Comprehension, Natural Language Processing, Intelligent Tutoring Systems
Dascalu, Mihai; Allen, Laura K.; McNamara, Danielle S.; Trausan-Matu, Stefan; Crossley, Scott A. – Grantee Submission, 2017
Dialogism provides the grounds for building a comprehensive model of discourse and it is focused on the multiplicity of perspectives (i.e., voices). Dialogism can be present in any type of text, while voices become themes or recurrent topics emerging from the discourse. In this study, we examine the extent that differences between…
Descriptors: Dialogs (Language), Protocol Analysis, Discourse Analysis, Automation
Allen, Laura K.; Jacovina, Matthew E.; Dascalu, Mihai; Roscoe, Rod D.; Kent, Kevin M.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2016
This study investigates how and whether information about students' writing can be recovered from basic behavioral data extracted during their sessions in an intelligent tutoring system for writing. We calculate basic and time-sensitive keystroke indices based on log files of keys pressed during students' writing sessions. A corpus of prompt-based…
Descriptors: Essays, Writing Processes, Writing (Composition), Writing Instruction
« Previous Page | Next Page
Pages: 1 | 2
Peer reviewed
Direct link
