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Rothschild, Karen; Cohen, Marvin; Moeller, Babette; Dubitsky, Barbara; Marshall, Nesta; McLeod, Matt – Grantee Submission, 2018
In order to plan and implement lessons that will be effective for a wide variety of learners, teachers must assess what students know and how they know it. They must also know students' academic strengths, challenges, and preferences. Careful observation of what students do and say as they work provides a rich source of data about both their…
Descriptors: Observation, Skill Development, Regular and Special Education Relationship, Teacher Collaboration
Chi, Michelene T. H.; Adams, Joshua; Bogusch, Emily B.; Bruchok, Christiana; Kang, Seokmin; Lancaster, Matthew; Levy, Roy; Li, Na; McEldoon, Katherine L.; Stump, Glenda S.; Wylie, Ruth; Xu, Dongchen; Yaghmourian, David L. – Grantee Submission, 2018
ICAP is a theory of active learning that differentiates students' engagement based on their behaviors. ICAP postulates that "Interactive" engagement, demonstrated by co-generative collaborative behaviors, is superior for learning to "Constructive" engagement, indicated by generative behaviors. Both kinds of engagement exceed…
Descriptors: Active Learning, Learner Engagement, Outcomes of Education, Learning Theories
Burke, Kathryn M.; Shogren, Karrie A.; Raley, Sheida K.; Wehmeyer, Michael L.; Antosh, A. Anthony; LaPlante, Terri – Grantee Submission, 2018
Implementation science examines the process of how programs are put into action to produce outcomes and represents an emerging approach for analyzing the utilization of evidence-based practices (EBPs) in school settings. When EBPs are implemented effectively, they result in positive student outcomes. The "Self-Determined Learning Model of…
Descriptors: Evidence Based Practice, Self Determination, Teaching Methods, Models
Hassinger-Das, Brenna; Bustamante, Andres S.; Hirsh-Pasek, Kathy; Golinkoff, Roberta Michnick – Grantee Submission, 2018
Children from under-resourced communities regularly enter formal schooling lagging behind their peers. These deficits in areas such as language development, reading readiness, and even in the kind of spatial skills that predict later mathematical knowledge, may persist throughout their lifespan. To address such gaps, policymakers have focused…
Descriptors: Play, Urban Planning, Urban Areas, Child Development
John, Melissa-Sue; Sibuma, Bernadette; Wunnava, Susmitha; Anggoro, Florencia; Dubosarsky, Mia – Grantee Submission, 2018
This paper describes an iterative participatory curriculum design approach to developing a problem-based STEM curriculum for preschool children. The curriculum aims to teach young children problem-solving using an adapted version of the engineering design process (EDP). Despite evidence showing that a rigorous, integrated STEM curriculum promotes…
Descriptors: Early Childhood Education, Problem Based Learning, STEM Education, Curriculum Development
Zhang, Zhiyong; Liu, Haiyan – Grantee Submission, 2018
Latent change score models (LCSMs) proposed by McArdle (McArdle, 2000, 2009; McArdle & Nesselroade, 1994) offer a powerful tool for longitudinal data analysis. They are becoming increasingly popular in social and behavioral research (e.g., Gerstorf et al., 2007; Ghisletta & Lindenberger, 2005; King et al., 2006; Raz et al., 2008). Although…
Descriptors: Sample Size, Monte Carlo Methods, Data Analysis, Models
Yang, Hsiu-Wen; Ostrosky, Michaelene M.; Favazza, Paddy C.; Stalega, Melissa V.; Block, Marty E. – Grantee Submission, 2018
During the preschool years children develop many new skills, including gross motor abilities, which serve as a foundation for school readiness skills in areas such as language, socialization and cognition. Like other domains, motor skill development does not happen without practice opportunities. That is, it requires multiple opportunities whereby…
Descriptors: Psychomotor Skills, Motor Development, Inclusion, Preschool Education
DeWire, Tom; McKithen, Clarissa; Carey, Rebecca – Grantee Submission, 2017
What can the Investing in Innovation (i3) grantees tell us about scaling innovative educational practices? The newly released white paper "Scaling Up Evidence-Based Practices: Strategies from Investing in Innovation (i3)" captures the experiences of nine grantees whose projects collectively have reached over 1.2 million students across…
Descriptors: Scaling, Evidence Based Practice, Federal Aid, Grants
Burstein, Jill; Madnani, Nitin; Sabatini, John; McCaffrey, Dan; Biggers, Kietha; Dreier, Kelsey – Grantee Submission, 2017
K-12 education standards in the U.S. require all students to read complex texts across many subject areas. The "Language Muse™ Activity Palette" is a web-based language-instruction application that uses NLP algorithms and lexical resources to automatically generate language activities and support English language learners' content…
Descriptors: Language Acquisition, Learning Activities, English Language Learners, Web Based Instruction
Carpenter, Bob; Gelman, Andrew; Hoffman, Matthew D.; Lee, Daniel; Goodrich, Ben; Betancourt, Michael; Brubaker, Marcus A.; Guo, Jiqiang; Li, Peter; Riddell, Allen – Grantee Submission, 2017
Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the…
Descriptors: Programming Languages, Probability, Bayesian Statistics, Monte Carlo Methods
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Dascalu, Mihai; Jacovina, Matthew E.; Soto, Christian M.; Allen, Laura K.; Dai, Jianmin; Guerrero, Tricia A.; McNamara, Danielle S. – Grantee Submission, 2017
iSTART is a web-based reading comprehension tutor. A recent translation of iSTART from English to Spanish has made the system available to a new audience. In this paper, we outline several challenges that arose during the development process, specifically focusing on the algorithms that drive the feedback. Several iSTART activities encourage…
Descriptors: Spanish, Reading Comprehension, Natural Language Processing, Intelligent Tutoring Systems
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Perret, Cecile A.; Johnson, Amy M.; McCarthy, Kathryn S.; Guerrero, Tricia A.; Dai, Jianmin; McNamara, Danielle S. – Grantee Submission, 2017
This paper introduces StairStepper, a new addition to Interactive Strategy Training for Active Reading and Thinking (iSTART), an intelligent tutoring system (ITS) that provides adaptive self-explanation training and practice. Whereas iSTART focuses on improving comprehension at levels geared toward answering challenging questions associated with…
Descriptors: Reading Comprehension, Reading Instruction, Intelligent Tutoring Systems, Reading Strategies
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Arenson, Ethan A.; Karabatsos, George – Grantee Submission, 2017
Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…
Descriptors: Bayesian Statistics, Item Response Theory, Nonparametric Statistics, Models
Capin, Philip; Vaughn, Sharon – Grantee Submission, 2017
This article describes evidence-based practices that beginning special education teachers can readily implement in special or general education settings that promote reading and content outcomes for students with disabilities as well as general education students. We describe two approaches: (a) Promoting Adolescents' Comprehension of Text (PACT),…
Descriptors: Reading Improvement, Social Studies, Reading Difficulties, Reading Comprehension
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Zhang, Haoran; Litman, Diane – Grantee Submission, 2017
Manually grading the Response to Text Assessment (RTA) is labor intensive. Therefore, an automatic method is being developed for scoring analytical writing when the RTA is administered in large numbers of classrooms. Our long-term goal is to also use this scoring method to provide formative feedback to students and teachers about students' writing…
Descriptors: Automation, Scoring, Evidence, Scoring Rubrics
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