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Reading Motivation in Spanish-Speaking Dual Language Learners: Comparing Two Types of Student Report
Klauda, Susan Lutz; Taboada Barber, Ana; McAllen, Elizabeth B. – Grantee Submission, 2020
Employing a mixed methods approach, this study examined the reading motivations of dual language learners (DLLs) in Grades 3-5 in a suburban Title I school in which the student population was predominantly Hispanic. Twenty-one students completed self-report surveys and participated in interviews focused on two intrinsic motivations (involvement…
Descriptors: Reading Motivation, Bilingual Students, Elementary School Students, Hispanic American Students
Taboada Barber, Ana; Klauda, Susan Lutz; Stapleton, Laura – Grantee Submission, 2020
Previous studies offer mixed evidence regarding whether a unified model of reading comprehension predictors applies to Dual Language Learners (DLLs) and English Speakers (ESs), or whether distinctive models across language groups are empirically supported. The present study adds another dimension to this body of work by examining multiple reading…
Descriptors: Reading Comprehension, Bilingualism, Reading Motivation, Predictor Variables
Taboada Barber, Ana; Cartwright, Kelly B.; Stapleton, Laura; Klauda, Susan Lutz; Archer, Casey; Smith, Peet – Grantee Submission, 2020
Given concerns about the reading achievement of Dual Language Learners (DLLs) in comparison to English Monolinguals (EMs), this study examined individual difference variables contributing to English reading comprehension growth in Spanish-speaking DLLs and their EM counterparts in Grades 1-4. The participants, who included 578 DLLs and 412 EMs,…
Descriptors: Executive Function, Reading Motivation, Reading Comprehension, Second Language Learning
Goodwin, Amanda P.; Petscher, Yaacov; Jones, Sara; McFadden, Sara; Reynolds, Dan; Lantos, Tess – Grantee Submission, 2020
The authors describe Monster, PI, which is an app-based, gamified assessment that measures language skills (knowledge of morphology, vocabulary, and syntax) of students in grades 5-8 and provides teachers with interpretable score reports to drive instruction that improves vocabulary, reading, and writing ability. Specifically, the authors describe…
Descriptors: Computer Assisted Testing, Handheld Devices, Language Maintenance, Language Tests
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 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
McNamara, Danielle S. – Grantee Submission, 2020
This article provides a commentary within the special issue, Integration: The Keystone of Comprehension. According to most contemporary frameworks, a driving force in comprehension is the reader's ability to generate the links among the words and sentences (ideas) in the texts and between the ideas in the text and what the readers already know. As…
Descriptors: Inferences, Language Processing, Reading Comprehension, Reading Research
Dascalu, Marina-Dorinela; Ruseti, Stefan; Dascalu, Mihai; McNamara, Danielle; Trausan-Matu, Stefan – Grantee Submission, 2020
Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to visualize text cohesion both within (intra) and…
Descriptors: Network Analysis, Graphs, Connected Discourse, Reading Comprehension
McIntyre, Nancy S.; Grimm, Ryan P.; Solari, Emily J.; Zajic, Matthew C.; Mundy, Peter C. – Grantee Submission, 2020
Purpose: Extant research indicates that children and adolescents with autism spectrum disorder (ASD) without an intellectual disability (ID) often experience difficulty comprehending written texts that is unexpected in comparison with their cognitive abilities. This study investigated the development of two key skills, narrative and inference…
Descriptors: Autism, Pervasive Developmental Disorders, Children, Adolescents
Denton, Carolyn A.; Montroy, Janelle J.; Zucker, Tricia A.; Cannon, Grace – Grantee Submission, 2020
The purpose of this feasibility study was to inform the development of an intervention to support reading and self-regulation for students with significant reading difficulties and disabilities (RDs), including dyslexia. Participants were 21 special educators, dyslexia specialists, and reading interventionists and 48 students in Grades 2 to 4.…
Descriptors: Intervention, Program Development, Reading Skills, Self Management
McCarthy, Kathryn S.; Watanabe, Micah; McNamara, Danielle S. – Grantee Submission, 2020
The Design Implementation Framework, or DIF, is a design approach that evaluates learner and user experience at multiple points in the development of intelligent tutoring systems. In this chapter, we explore how DIF was used to make system modifications to iSTART, a game-based intelligent tutoring system for reading comprehension. Using DIF as a…
Descriptors: Intelligent Tutoring Systems, Reading Comprehension, Educational Games, Program Development
Botarleanu, Robert-Mihai; Dascalu, Mihai; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2020
A key writing skill is the capability to clearly convey desired meaning using available linguistic knowledge. Consequently, writers must select from a large array of idioms, vocabulary terms that are semantically equivalent, and discourse features that simultaneously reflect content and allow readers to grasp meaning. In many cases, a simplified…
Descriptors: Natural Language Processing, Writing Skills, Difficulty Level, Reading Comprehension
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…
Descriptors: Network Analysis, Reading Comprehension, Automation, Artificial Intelligence
McCarthy, Kathryn S.; Allen, Laura K.; Hinze, Scott R. – Grantee Submission, 2020
Open-ended "constructed responses" promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students' cognition. This study examined how students' constructed responses, generated at different points during learning, relate to their later comprehension outcomes.…
Descriptors: Reading Comprehension, Prediction, Responses, College Students
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
Guerrero, Tricia A.; Griffin, Thomas D.; Wiley, Jennifer – Grantee Submission, 2020
The Predict-Observe-Explain (POE) learning cycle improves understanding of the connection between empirical results and theoretical concepts when students engage in hands-on experimentation. This study explored whether training students to use a POE strategy when learning from social science texts that describe theories and experimental results…
Descriptors: Prediction, Observation, Reading Comprehension, Correlation

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