Publication Date
| In 2026 | 0 |
| Since 2025 | 13 |
| Since 2022 (last 5 years) | 40 |
| Since 2017 (last 10 years) | 56 |
| Since 2007 (last 20 years) | 82 |
Descriptor
Source
Author
Publication Type
| Reports - Research | 73 |
| Journal Articles | 55 |
| Speeches/Meeting Papers | 16 |
| Tests/Questionnaires | 7 |
| Reports - Descriptive | 4 |
| Collected Works - Proceedings | 3 |
| Reports - Evaluative | 2 |
| Dissertations/Theses -… | 1 |
Education Level
| High Schools | 83 |
| Secondary Education | 76 |
| Higher Education | 25 |
| Postsecondary Education | 23 |
| Junior High Schools | 17 |
| Middle Schools | 16 |
| Grade 9 | 9 |
| Elementary Education | 8 |
| Grade 10 | 8 |
| Grade 11 | 6 |
| Grade 8 | 5 |
| More ▼ | |
Audience
| Researchers | 1 |
| Teachers | 1 |
Location
| Pennsylvania | 5 |
| Germany | 4 |
| Australia | 3 |
| California | 3 |
| Canada | 3 |
| Pennsylvania (Pittsburgh) | 3 |
| Taiwan | 3 |
| Arizona (Phoenix) | 2 |
| Brazil | 2 |
| Hong Kong | 2 |
| Turkey | 2 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| Gates MacGinitie Reading Tests | 9 |
| Massachusetts Comprehensive… | 1 |
| National Assessment of… | 1 |
| Program for International… | 1 |
| Writing Apprehension Test | 1 |
What Works Clearinghouse Rating
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2015
This study builds upon previous work aimed at developing a student model of reading comprehension ability within the intelligent tutoring system, iSTART. Currently, the system evaluates students' self-explanation performance using a local, sentence-level algorithm and does not adapt content based on reading ability. The current study leverages…
Descriptors: Reading Comprehension, Reading Skills, Natural Language Processing, Intelligent Tutoring Systems
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2014
In the current study, we utilize natural language processing techniques to examine relations between the linguistic properties of students' self-explanations and their reading comprehension skills. Linguistic features of students' aggregated self-explanations were analyzed using the Linguistic Inquiry and Word Count (LIWC) software. Results…
Descriptors: Natural Language Processing, Reading Comprehension, Linguistics, Predictor Variables
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Psychology, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
Varner, Laura K.; Jackson, G. Tanner; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2013
This study expands upon an existing model of students' reading comprehension ability within an intelligent tutoring system. The current system evaluates students' natural language input using a local student model. We examine the potential to expand this model by assessing the linguistic features of self-explanations aggregated across entire…
Descriptors: Reading Comprehension, Intelligent Tutoring Systems, Natural Language Processing, Reading Ability
Crossley, Scott A.; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Data Mining, 2016
This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…
Descriptors: Essays, Scoring, Writing Evaluation, Natural Language Processing
Snow, Erica L.; Allen, Laura K.; Jacovina, Matthew E.; Crossley, Scott A.; Perret, Cecile A.; McNamara, Danielle S. – Journal of Learning Analytics, 2015
Writing researchers have suggested that students who are perceived as strong writers (i.e., those who generate texts rated as high quality) demonstrate flexibility in their writing style. While anecdotally this has been a commonly held belief among researchers and educators, there is little empirical research to support this claim. This study…
Descriptors: Writing (Composition), Writing Strategies, Hypothesis Testing, Essays
Snow, Erica L.; Allen, Laura K.; Jacovina, Matthew E.; Crossley, Scott A.; Perret, Cecile A.; McNamara, Danielle S. – Grantee Submission, 2015
Writing researchers have suggested that students who are perceived as strong writers (i.e., those who generate texts rated as high quality) demonstrate flexibility in their writing style. While anecdotally this has been a commonly held belief among researchers and educators, there is little empirical research to support this claim. This study…
Descriptors: Writing (Composition), Writing Strategies, Hypothesis Testing, Essays
Jacovina, Matthew E.; McNamara, Danielle S. – Grantee Submission, 2017
In this chapter, we describe several intelligent tutoring systems (ITSs) designed to support student literacy through reading comprehension and writing instruction and practice. Although adaptive instruction can be a powerful tool in the literacy domain, developing these technologies poses significant challenges. For example, evaluating the…
Descriptors: Intelligent Tutoring Systems, Literacy Education, Educational Technology, Technology Uses in Education
Crossley, Scott A.; Roscoe, Rod; McNamara, Danielle S. – Written Communication, 2014
This study identifies multiple profiles of successful essays via a cluster analysis approach using linguistic features reported by a variety of natural language processing tools. The findings from the study indicate that there are four profiles of successful writers for the samples analyzed. These four profiles are linguistically distinct from one…
Descriptors: Essays, Natural Language Processing, Computational Linguistics, Multivariate Analysis
Katz, Sandra; Jordan, Pamela; Litman, Diane – Society for Research on Educational Effectiveness, 2011
The natural-language tutorial dialogue system that the authors are developing will allow them to focus on the nature of interactivity during tutoring as a malleable factor. Specifically, it will serve as a research platform for studies that manipulate the frequency and types of verbal alignment processes that take place during tutoring, such as…
Descriptors: Natural Language Processing, Physics, Logical Thinking, Intelligent Tutoring Systems
Roscoe, Rod D.; Varner, Laura K.; Crossley, Scott A.; McNamara, Danielle S. – Grantee Submission, 2013
Various computer tools have been developed to support educators' assessment of student writing, including automated essay scoring and automated writing evaluation systems. Research demonstrates that these systems exhibit relatively high scoring accuracy but uncertain instructional efficacy. Students' writing proficiency does not necessarily…
Descriptors: Writing Instruction, Intelligent Tutoring Systems, Computer Assisted Testing, Writing Evaluation
Katz, Sandra; Albacete, Patricia L. – Journal of Educational Psychology, 2013
For some time, it has been clear that students who are tutored generally learn more than students who experience classroom instruction (e.g., Bloom, 1984). Much research has been devoted to identifying features of tutorial dialogue that can explain its effectiveness, so that these features can be simulated in natural-language tutoring systems. One…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Interaction, Rhetorical Theory
Katz, Sandra; Albacete, Patricia L. – Grantee Submission, 2013
For some time, it has been clear that students who are tutored generally learn more than students who experience classroom instruction (e.g., Bloom, 1984). Much research has been devoted to identifying features of tutorial dialogue that can explain its effectiveness, so that these features can be simulated in natural-language tutoring systems. One…
Descriptors: Rhetorical Theory, Tutoring, Intelligent Tutoring Systems, Secondary School Science
Crossley, Scott A.; Varner, Laura K.; Roscoe, Rod D.; McNamara, Danielle S. – Grantee Submission, 2013
We present an evaluation of the Writing Pal (W-Pal) intelligent tutoring system (ITS) and the W-Pal automated writing evaluation (AWE) system through the use of computational indices related to text cohesion. Sixty-four students participated in this study. Each student was assigned to either the W-Pal ITS condition or the W-Pal AWE condition. The…
Descriptors: Intelligent Tutoring Systems, Automation, Writing Evaluation, Writing Assignments

Peer reviewed
Direct link
