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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
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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
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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
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Ardoin, Scott P.; Binder, Katherine S.; Kulesz, Paulina A.; Nimocks, Eloise; Mellott, Joshua A. – Grantee Submission, 2024
Understanding test-taking strategies (TTSs) and the variables that influence TTSs is crucial to understanding what reading comprehension tests measure. We examined how passage and student characteristics were associated with TTSs and their impact on response accuracy. Third (n = 78), fifth (n = 86), and eighth (n = 86) graders read and answered…
Descriptors: Test Wiseness, Eye Movements, Reading Comprehension, Reading Tests
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Xueye Yan; Peng Peng; Yuting Liu – Grantee Submission, 2024
Mayer (2017, 2020) proposed three major design features of computer-assisted instructions (CAI) within the Cognitive Theory of Multimedia Learning: reducing extraneous processing (i.e., excluding irrelevant content), managing essential processing (i.e., focusing on the complex but essential learning materials), and fostering generative processing…
Descriptors: Computer Assisted Instruction, Reading Instruction, Instructional Design, Reading Difficulties
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Andreea 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
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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Jorge Salas – Grantee Submission, 2024
Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore,…
Descriptors: Item Response Theory, Reaction Time, Models, Accuracy
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Philip Capin; Sharon Vaughn; Joseph E. Miller; Jeremy Miciak; Anna-Mari Fall; Greg Roberts; Eunsoo Cho; Amy E. Barth; Paul K. Steinle; Jack M. Fletcher – Grantee Submission, 2024
Purpose: This study investigated the reading profiles of middle school Spanish-speaking emergent bilinguals (EBs) with significantly below grade level reading comprehension and whether these profiles varied in their reading comprehension performance over time. Method: Latent profile analyses were used to classify Grade 6 and 7 Hispanic EBs (n =…
Descriptors: Profiles, Reading Comprehension, Reading Difficulties, Middle School Students
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Virginia Clinton-Lisell; Sarah E. Carlson; Heather Ness-Maddox; Amanda Dahl; Terrill Taylor; Mark L. Davison; Ben Seipel – Grantee Submission, 2024
The purpose of this study was to examine clusters of less-skilled college readers. College students with below average reading comprehension skills (N = 77) read and thought aloud about four texts, recalled the texts, and completed standardized assessments of reading skills. Based on the findings of cluster analyses of the cognitive processes…
Descriptors: Vocabulary, Reading Comprehension, Reading Tests, Reading Skills
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Micah 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
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David A. Klingbeil; Ethan R. Van Norman; Peter M. Nelson; David C. Parker; Patrick Kaiser; Monica L. Vidal; Angelos Ntais; Zhuanghan Dong; Kirsten Truman – Grantee Submission, 2024
Text reading fluency (TRF) is a common reading intervention target in second and third grade. TRF requires the integration of several skills that result in several pathways to dysfluent reading. However, when applying the drill-down approach to intervention targeting, practitioners are guided to consider students' rate and accuracy when reading…
Descriptors: Elementary School Students, Elementary School Teachers, Grade 2, Grade 3
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Nicula, Bogdan; Panaite, Marilena; Arner, Tracy; Balyan, Renu; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2023
Self-explanation practice is an effective method to support students in better understanding complex texts. This study focuses on automatically assessing the comprehension strategies employed by readers while understanding STEM texts. Data from 3 datasets (N = 11,833) with self-explanations annotated on different comprehension strategies (i.e.,…
Descriptors: Reading Strategies, Reading Comprehension, Metacognition, STEM Education
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McNamara, Danielle S.; Newton, Natalie; Christhilf, Katerina; McCarthy, Kathryn S.; Magliano, Joseph P.; Allen, Laura K. – Grantee Submission, 2023
Analyzing constructed responses, such as think-alouds or self-explanations, can reveal valuable information about readers' comprehension strategies. The current study expands on the extant work by (1) investigating combinations and patterns of comprehension strategies that readers use and (2) examining the extent to which these patterns relate to…
Descriptors: Metacognition, Reading Comprehension, Inferences, Reading Strategies
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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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Morris, Wesley; Crossley, Scott; Holmes, Langdon; Ou, Chaohua; McNamara, Danielle; Dascalu, Mihai – Grantee Submission, 2023
As intelligent textbooks become more ubiquitous in classrooms and educational settings, the need arises to automatically provide formative feedback to written responses provided by students in response to readings. This study develops models to automatically provide feedback to student summaries written at the end of intelligent textbook sections.…
Descriptors: Textbooks, Electronic Publishing, Feedback (Response), Formative Evaluation
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