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Zhang, Haoran; Litman, Diane – Grantee Submission, 2021
Human essay grading is a laborious task that can consume much time and effort. Automated Essay Scoring (AES) has thus been proposed as a fast and effective solution to the problem of grading student writing at scale. However, because AES typically uses supervised machine learning, a human-graded essay corpus is still required to train the AES…
Descriptors: Essays, Grading, Writing Evaluation, Computational Linguistics
Craig K. Enders – Grantee Submission, 2023
The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of "Psychological Methods." Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of…
Descriptors: Data, Research, Theories, Regression (Statistics)
Litman, Diane; Zhang, Haoran; Correnti, Richard; Matsumura, Lindsay Clare; Wang, Elaine – Grantee Submission, 2021
Automated Essay Scoring (AES) can reliably grade essays at scale and reduce human effort in both classroom and commercial settings. There are currently three dominant supervised learning paradigms for building AES models: feature-based, neural, and hybrid. While feature-based models are more explainable, neural network models often outperform…
Descriptors: Essays, Writing Evaluation, Models, Accuracy
Crossley, Scott; Wan, Qian; Allen, Laura; McNamara, Danielle – Grantee Submission, 2021
Synthesis writing is widely taught across domains and serves as an important means of assessing writing ability, text comprehension, and content learning. Synthesis writing differs from other types of writing in terms of both cognitive and task demands because it requires writers to integrate information across source materials. However, little is…
Descriptors: Writing Skills, Cognitive Processes, Essays, Cues
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Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Wilson, Joshua; Huang, Yue; Palermo, Corey; Beard, Gaysha; MacArthur, Charles A. – Grantee Submission, 2021
This study examined a naturalistic, districtwide implementation of an automated writing evaluation (AWE) software program called "MI Write" in elementary schools. We specifically examined the degree to which aspects of MI Write were implemented, teacher and student attitudes towards MI Write, and whether MI Write usage along with other…
Descriptors: Automation, Writing Evaluation, Feedback (Response), Computer Software
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
Mark Bodner; Andrew Coulson – Grantee Submission, 2021
A randomized controlled trial group design study funded by IES NCR Grant R305A090527 was conducted in which 16,307 3rd, 4th, and 5th grade students in 52 school grade-level clusters were randomly assigned to receive ST Math (program revision Gen3), a supplemental mathematics software instructional intervention, or to a business-as-usual…
Descriptors: Mathematics Instruction, Computer Software, Computer Uses in Education, Elementary School Students
Botarleanu, Robert-Mihai; Dascalu, Mihai; Watanabe, Micah; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Age of acquisition (AoA) is a measure of word complexity which refers to the age at which a word is typically learned. AoA measures have shown strong correlations with reading comprehension, lexical decision times, and writing quality. AoA scores based on both adult and child data have limitations that allow for error in measurement, and increase…
Descriptors: Age Differences, Vocabulary Development, Correlation, Reading Comprehension
Wang, Elaine Lin; Matsumura, Lindsay Clare; Correnti, Richard; Litman, Diane; Zhang, Haoran; Howe, Emily; Magooda, Ahmed; Quintana, Rafael – Grantee Submission, 2020
We investigate students' implementation of the feedback messages they received in an automated writing evaluation system ("eRevise") that aims to improve students' use of text evidence in their writing. Seven 5th and 6th-grade teachers implemented "eRevise" (n = 143 students). Qualitative analysis of students' essays across…
Descriptors: Feedback (Response), Writing Evaluation, Computer Software, Grade 5
Jamie J. Jirout; Sierra Eisen; Zoe S. Robertson; Tanya M. Evans – Grantee Submission, 2022
Play is a powerful influence on children's learning and parents can provide opportunities to learn specific content by scaffolding children's play. Parent-child synchrony (i.e., harmony, reciprocity and responsiveness in interactions) is a component of parent-child interactions that is not well characterized in studies of play. We tested whether…
Descriptors: Play, Mothers, Parent Child Relationship, Executive Function
Dore, Rebecca A.; Shirilla, Marcia; Hopkins, Emily; Collins, Molly; Scott, Molly; Shatz, Jacob; Lawson-Adams, Jessica; Valladares, Tara; Foster, Lindsey; Puttre, Hannah; Toub, Tamara Spiewak; Hadley, Elizabeth; Golinkoff, Roberta M.; Dickinson, David; Hirsh-Pasek, Kathy – Grantee Submission, 2019
Despite the prevalence of educational apps for children, there is little evidence of their effectiveness for learning. Here, children were asked to learn ten new words in a narrative mobile game that requires children use knowledge of word meanings to advance the game. Study 1 used a lab-based between-subjects design with middle-SES 4-year-olds…
Descriptors: Vocabulary Development, Computer Software, Preschool Children, Language Tests
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Burstein, Jill; McCaffrey, Dan; Beigman Klebanov, Beata; Ling, Guangming – Grantee Submission, 2017
No significant body of research examines writing achievement and the specific skills and knowledge in the writing domain for postsecondary (college) students in the U.S., even though many at-risk students lack the prerequisite writing skills required to persist in their education. This paper addresses this gap through a novel…
Descriptors: Computer Software, Writing Evaluation, Writing Achievement, College Students
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Foster, Matthew E.; Anthony, Jason L.; Clements, Doug H.; Sarama, Julie; Williams, Jeffrey M. – Grantee Submission, 2016
This study evaluated the effects of a mathematics software program, the Building Blocks software suite, on young children's mathematics performance. Participants included 247 Kindergartners from 37 classrooms in 9 schools located in low-income communities. Children within classrooms were randomly assigned to receive 21 weeks of computer-assisted…
Descriptors: Mathematics Education, Arithmetic, Kindergarten, Computer Assisted Instruction
Hedges, Larry V.; Hedberg, Eric C.; Kuyper, Arend M. – Grantee Submission, 2012
Intraclass correlations are used to summarize the variance decomposition in popula- tions with multilevel hierarchical structure. There has recently been considerable interest in estimating intraclass correlations from surveys or designed experiments to provide design parameters for planning future large-scale randomized experiments. The large…
Descriptors: Correlation, Hierarchical Linear Modeling, Computation, Sampling