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Balyan, Renu; Arner, Tracy; Taylor, Karen; Shin, Jinnie; Banawan, Michelle; Leite, Walter L.; McNamara, Danielle S. – International Educational Data Mining Society, 2022
The National Council of Teachers of Mathematics (NCTM) has been emphasizing the importance of teachers' pedagogical communication as part of mathematical teaching and learning for decades. Specifically, NCTM has provided guidance on how teachers can foster mathematical communication that positively impacts student learning. A teacher may have…
Descriptors: Tutoring, Guidelines, Mathematics Instruction, Computer Assisted Instruction
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Corlatescu, Dragos; Watanabe, Micah; Ruseti, Stefan; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2023
Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…
Descriptors: Reading Comprehension, Models, Concept Mapping, Graphs
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Fang, Ying; Li, Tong; Huynh, Linh; Christhilf, Katerina; Roscoe, Rod D.; McNamara, Danielle S. – Grantee Submission, 2023
Literacy assessment is essential for effective literacy instruction and training. However, traditional paper-based literacy assessments are typically decontextualized and may cause stress and anxiety for test takers. In contrast, serious games and game environments allow for the assessment of literacy in more authentic and engaging ways, which has…
Descriptors: Literacy, Student Evaluation, Educational Games, Literacy Education
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Nicula, Bogdan; Dascalu, Mihai; Arner, Tracy; Balyan, Renu; McNamara, Danielle S. – Grantee Submission, 2023
Text comprehension is an essential skill in today's information-rich world, and self-explanation practice helps students improve their understanding of complex texts. This study was centered on leveraging open-source Large Language Models (LLMs), specifically FLAN-T5, to automatically assess the comprehension strategies employed by readers while…
Descriptors: Reading Comprehension, Language Processing, Models, STEM Education
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Mason, Anna E.; Braasch, Jason L. G.; Greenberg, Daphne; Kessler, Erica D.; Allen, Laura K.; McNamara, Danielle S. – Reading Psychology, 2023
This study examined the extent to which prior beliefs and reading instructions impacted elements of a reader's mental representation of multiple texts. College students' beliefs about childhood vaccinations were assessed before reading two anti-vaccine and two pro-vaccine texts. Participants in the experimental condition read for the purpose of…
Descriptors: Immunization Programs, Misconceptions, Beliefs, Accuracy
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Mason, Anna E.; Braasch, Jason L. G.; Greenberg, Daphne; Kessler, Erica D.; Allen, Laura K.; McNamara, Danielle S. – Grantee Submission, 2022
This study examined the extent to which prior beliefs and reading instructions impacted elements of a reader's mental representation of multiple texts. College students' beliefs about childhood vaccinations were assessed before reading two anti-vaccine and two pro-vaccine texts. Participants in the experimental condition read for the purpose of…
Descriptors: College Students, Beliefs, Immunization Programs, Vocabulary
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McCarthy, Kathryn S.; Soto, Christian Marcelo; Gutierrez de Blume, Antonio P.; Palma, Diego; González, Jordan Ignacio; McNamara, Danielle S. – International Journal of Computer-Assisted Language Learning and Teaching, 2020
iSTART-E is a web-based intelligent tutor developed for Spanish-speaking students to improve their reading comprehension through self-explanation strategy training. This study examined the effects of a blended comprehension strategy intervention on students' reading comprehension skill. Chilean high school students (N = 22) completed nine iSTART-E…
Descriptors: Reading Comprehension, High School Students, Computer Assisted Instruction, Teaching Methods
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Roscoe, Rod D.; McNamara, Danielle S. – Journal of Educational Psychology, 2013
The Writing Pal (W-Pal) is a novel intelligent tutoring system (ITS) that offers writing strategy instruction, game-based practice, essay writing practice, and formative feedback to developing writers. Compared to more tractable and constrained learning domains for ITS, writing is an ill-defined domain because the features of effective writing are…
Descriptors: Feasibility Studies, Intelligent Tutoring Systems, Writing Instruction, Writing Strategies
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Allen, Laura K.; Jacovina, Matthew E.; Johnson, Adam C.; McNamara, Danielle S.; Roscoe, Rod D. – Grantee Submission, 2016
Revising is an essential writing process yet automated writing evaluation systems tend to give feedback on discrete essay drafts rather than changes across drafts. We explore the feasibility of automated revision detection and its potential to guide feedback. Relationships between revising behaviors and linguistic features of students' essays are…
Descriptors: Revision (Written Composition), Automation, Writing Evaluation, Feedback (Response)
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Shin, Jinnie; Balyan, Renu; Banawan, Michelle P.; Arner, Tracy; Leite, Walter L.; McNamara, Danielle S. – 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
McCarthy, Kathryn S.; Watanabe, Micah; Dai, Jianmin; McNamara, Danielle S. – Grantee Submission, 2020
Computer-based learning environments (CBLEs) provide unprecedented opportunities for personalized learning at scale. One such system, iSTART (Interactive Strategy Training for Active Reading and Thinking) is an adaptive, game-based tutoring system for reading comprehension. This paper describes how efforts to increase personalized learning have…
Descriptors: Game Based Learning, Reading Comprehension, High School Students, Educational Technology
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McCarthy, Kathryn S.; Watanabe, Micah; Dai, Jianmin; McNamara, Danielle S. – Journal of Research on Technology in Education, 2020
Computer-based learning environments (CBLEs) provide unprecedented opportunities for personalized learning at scale. One such system, iSTART (Interactive Strategy Training for Active Reading and Thinking) is an adaptive, game-based tutoring system for reading comprehension. This paper describes how efforts to increase personalized learning have…
Descriptors: Game Based Learning, Reading Comprehension, High School Students, Educational Technology
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McNamara, Danielle S.; Arner, Tracy; Reilley, Elizabeth; Alvarado, Paul; Clark, Chani; Fikes, Thomas; Hale, Annie; Weigele, Betheny – Grantee Submission, 2022
Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…
Descriptors: Electronic Learning, Educational Technology, Networks, Learning Analytics
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
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Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
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