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Matthew T. McCrudden; Linh Huynh; Bailing Lyu; Jonna M. Kulikowich; Danielle S. McNamara – Grantee Submission, 2024
Readers build a mental representation of text during reading. The coherence building processes readers use to build a mental representation during reading is key to comprehension. We examined the effects of self- explanation on coherence building processes as undergraduates (n =51) read five complementary texts about natural selection and…
Descriptors: Reading Processes, Reading Comprehension, Undergraduate Students, Evolution
Dragos-Georgian Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…
Descriptors: Computer Software, Artificial Intelligence, Learning Analytics, Natural Language Processing
Stephanie L. Day; Jin K. Hwang; Tracy Arner; Danielle S. McNamara; Carol M. Connor – Grantee Submission, 2024
The purpose of this feasibility study was to examine the potential impact of reading digital interactive e-books, Word Knowledge e-books (WKe-Books), on essential skills that support reading comprehension with third-fifth grade students. Students (N= 425) read two WKe-Books, that taught word learning and comprehension monitoring strategies in the…
Descriptors: Electronic Books, Reading Comprehension, Word Recognition, Elementary School Students
Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
Peer reviewedAndreea Dutulescu; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This…
Descriptors: Difficulty Level, Reading Tests, Test Items, Reading Comprehension
Danielle S. McNamara – Grantee Submission, 2024
Our primary objective in this Special Issue was to respond to potential criticisms of AIED in potentially "perpetuating poor pedagogic practices, datafication, and introducing classroom surveillance" and to comment on the future of AIED in its coming of age. My overarching assumption in response to this line of critiques is that humans…
Descriptors: Educational Practices, Educational Quality, Intelligent Tutoring Systems, Artificial Intelligence
Peer reviewedMicah Watanabe; Megan Imundo; Katerina Christhilf; Tracy Arner; Danielle S. McNamara – Grantee Submission, 2024
Reading comprehension is essential for students' ability to build knowledge. Students' comprehension abilities can be enhanced by providing students with deliberate practice and formative feedback on reading comprehension strategies. iSTART is an Intelligent Tutoring System (ITS) that is designed to provide instruction in reading strategies with…
Descriptors: Reading Comprehension, Reading Strategies, Intelligent Tutoring Systems, Reading Instruction
Andreea Dutulescu; Stefan Ruseti; Denis Iorga; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
The process of generating challenging and appropriate distractors for multiple-choice questions is a complex and time-consuming task. Existing methods for an automated generation have limitations in proposing challenging distractors, or they fail to effectively filter out incorrect choices that closely resemble the correct answer, share synonymous…
Descriptors: Multiple Choice Tests, Artificial Intelligence, Attention, Natural Language Processing
Razvan Paroiu; Stefan Ruseti; Mihai Dascalu; Stefan Trausan-Matu; Danielle S. McNamara – Grantee Submission, 2023
The exponential growth of scientific publications increases the effort required to identify relevant articles. Moreover, the scale of studies is a frequent barrier to research as the majority of studies are low or medium-scaled and do not generalize well while lacking statistical power. As such, we introduce an automated method that supports the…
Descriptors: Science Education, Educational Research, Scientific and Technical Information, Journal Articles
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
Reese Butterfuss; Kathryn S. McCarthy; Ellen Orcutt; Panayiota Kendeou; Danielle S. McNamara – Grantee Submission, 2023
Readers often struggle to identify the main ideas in expository texts. Existing research and instruction provide some guidance on how to encourage readers to identify main ideas. However, there is substantial variability in how main ideas are operationalized and how readers are prompted to identify main ideas. This variability hinders…
Descriptors: Reading Processes, Reading Comprehension, Reading Instruction, Best Practices
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 Banawan; Reese Butterfuss; Karen S. Taylor; Katerina Christhilf; Claire Hsu; Connor O'Loughlin; Laura K. Allen; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Writing is essential for success in academics and everyday tasks, but the development of writing skills depends on consistent access to high-quality instruction, extended practice, and personalized feedback. To address these demands and meet students' needs, educators and researchers have turned to technology-based writing tools. Ideally, these…
Descriptors: Intelligent Tutoring Systems, Writing (Composition), Technology Uses in Education, Feedback (Response)
Robert-Mihai Botarleanu; Micah Watanabe; Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara – Grantee Submission, 2023
Age of Acquisition (AoA) scores approximate the age at which a language speaker fully understands a word's semantic meaning and represent a quantitative measure of the relative difficulty of words in a language. AoA word lists exist across various languages, with English having the most complete lists that capture the largest percentage of the…
Descriptors: Multilingualism, English (Second Language), Second Language Learning, Second Language Instruction
Danielle S. McNamara; Tracy Arner; Reese Butterfuss; Ying Fang; Micah Watanabe; Natalie Newton; Kathryn S. McCarthy; Laura K. Allen; Rod D. Roscoe – Grantee Submission, 2022
The Interactive Strategy Training for Active Reading and Thinking (iSTART) game-based intelligent tutoring system (ITS) was developed with a foundation of comprehension theory and principles of learning science to improve students' comprehension of complex scientific texts. iSTART has been shown to improve reading comprehension for learners from…
Descriptors: Reading Strategies, Reading Instruction, Reading Programs, Reading Comprehension

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