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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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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
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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McCarthy, Kathryn S.; Likens, Aaron D.; Kopp, Kristopher K.; Perret, Cecile A.; Watanabe, Micah; McNamara, Danielle S. – Grantee Submission, 2018
The current study explored relations between non-cognitive traits (Grit, Learning Orientation, Performance Orientation), reading skill, and performance across three experiments conducted in the context of two intelligent tutoring systems, iSTART and Writing Pal. Results showed that learning outcomes (comprehension score, holistic essay score) were…
Descriptors: Persistence, Individual Characteristics, Reading Skills, Performance
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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
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Banawan, Michelle P.; Shin, Jinnie; Arner, Tracy; Balyan, Renu; Leite, Walter L.; McNamara, Danielle S. – 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
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
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Snow, Erica L.; Likens, Aaron D.; Allen, Laura K.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2016
Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning…
Descriptors: Student Behavior, Pretests Posttests, High School Students, Teaching Methods
Wang, Zuowei; O'Reilly, Tenaha; Sabatini, John; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2021
We compared high school students' performance in a traditional comprehension assessment requiring them to identify key information and draw inferences from single texts, and a scenario-based assessment (SBA) requiring them to integrate, evaluate and apply information across multiple sources. Both assessments focused on a non-academic topic.…
Descriptors: Comparative Analysis, High School Students, Inferences, Reading Tests
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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
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Snow, Erica L.; Allen, Laura K.; Jackson, G. Tanner; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2015
Using students' process data from the game-based Intelligent Tutoring System (ITS) iSTART-ME, the current study examines students' propensity to use system currency to unlock game-based features, (i.e., referred to here as "spendency"). This study examines how spendency relates to students' interaction preferences, in-system performance,…
Descriptors: Intelligent Tutoring Systems, Educational Games, High School Students, Preferences
Snow, Erica L.; Likens, Aaron D.; Allen, Laura K.; McNamara, Danielle S. – Grantee Submission, 2015
Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning…
Descriptors: High School Students, Pretests Posttests, Teaching Methods, Technology Uses in Education
San Pedro, Maria Ofelia Z.; Snow, Erica L.; Baker, Ryan S.; McNamara, Danielle S.; Heffernan, Neil T. – International Educational Data Mining Society, 2015
There is increasing evidence that fine-grained aspects of student performance and interaction within educational software are predictive of long-term learning. Machine learning models have been used to provide assessments of affect, behavior, and cognition based on analyses of system log data, estimating the probability of a student's particular…
Descriptors: Mathematics Tests, Achievement Tests, Middle School Students, Intelligent Tutoring Systems
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