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Allen, Laura K.; Mills, Caitlin; Perret, Cecile; McNamara, Danielle S. – Grantee Submission, 2019
This study examines the extent to which instructions to self-explain vs. "other"-explain a text lead readers to produce different forms of explanations. Natural language processing was used to examine the content and characteristics of the explanations produced as a function of instruction condition. Undergraduate students (n = 146)…
Descriptors: Language Processing, Science Instruction, Computational Linguistics, Teaching Methods
Allen, Laura K.; Creer, Sarah D.; Poulos, Mary Cati – Grantee Submission, 2021
Research in discourse processing has provided us with a strong foundation for understanding the characteristics of text and discourse, as well as their influence on our processing and representation of texts. However, recent advances in computational techniques have allowed researchers to examine discourse processes in new ways. The purpose of the…
Descriptors: Natural Language Processing, Computation, Discourse Analysis, Computer Science
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Brendan Bartanen; Andrew Kwok; Andrew Avitabile; Brian Heseung Kim – Grantee Submission, 2025
Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive article examines preservice teachers' expressed motivation for pursuing a teaching career. Using data from a large teacher education program in Texas, we use a natural language processing…
Descriptors: Career Choice, Teaching (Occupation), Teacher Education Programs, Preservice Teachers
Jinnie Shin; Renu Balyan; Michelle P. Banawan; Tracy Arner; Walter L. Leite; Danielle S. McNamara – Grantee Submission, 2023
Despite the proliferation of video-based instruction and its benefits--such as promoting student autonomy and self-paced learning--the complexities of online teaching remain a challenge. To be effective, educators require extensive training in digital teaching methodologies. As such, there's a pressing need to examine and comprehend the…
Descriptors: Algebra, Mathematics Instruction, Video Technology, Personal Autonomy
Michelle P. Banawan; Jinnie Shin; Tracy Arner; Renu Balyan; Walter L. Leite; Danielle S. McNamara – Grantee Submission, 2023
Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities in how they construe and communicate meaning. This study examines the extent to which discourse…
Descriptors: Algebra, Discourse Analysis, Semantics, Syntax
McNamara, Danielle S.; Roscoe, Rod; Allen, Laura; Balyan, Renu; McCarthy, Kathryn S. – Grantee Submission, 2019
Literacy is a critically important and contemporary issue for educators, scientists, and politicians. Efforts to overcome the challenges associated with illiteracy, and the subsequent development of literate societies, are closely related to those of poverty reduction and sustainable human development. In this paper, the authors examine literacy…
Descriptors: Literacy, Reading Comprehension, Language Processing, Discourse Analysis
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Graesser, Arthur C.; Forsyth, Carol M.; Lehman, Blair A. – Grantee Submission, 2017
Background: Pedagogical agents are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with the students in natural language. Dialogues occur between a tutor agent and the student in the case of AutoTutor and other intelligent tutoring systems with natural language…
Descriptors: Intelligent Tutoring Systems, Computer Managed Instruction, Natural Language Processing, Instructional Design
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
Lipschultz, Michael; Litman, Diane; Katz, Sandra; Albacete, Patricia; Jordan, Pamela – Grantee Submission, 2014
Post-problem reflective tutorial dialogues between human tutors and students are examined to predict when the tutor changed the level of abstraction from the student's preceding turn (i.e., used more general terms or more specific terms); such changes correlate with learning. Prior work examined lexical changes in abstraction. In this work, we…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Semantics, Abstract Reasoning
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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