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Ziqian Xu – Grantee Submission, 2022
With the prevalence of missing data in social science research, it is necessary to use methods for handling missing data. One framework in which data with missing values can still be used for parameter estimation is the Bayesian framework. In this tutorial, different missing data mechanisms including Missing Completely at Random, Missing at…
Descriptors: Research Problems, Bayesian Statistics, Structural Equation Models, Data Analysis
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Austin T. Wyman; Zhiyong Zhang – Grantee Submission, 2023
Emotion recognition application programming interface (API) is a recent advancement in computing technology that synthesizes computer vision, machine-learning algorithms, deep-learning neural networks, and other information to detect and label human emotions. The strongest iterations of this technology are produced by technology giants with large,…
Descriptors: Emotional Response, Computer Software, Emotional Problems, Autism Spectrum Disorders
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Conrad Borchers; Tianze Shou – Grantee Submission, 2025
Large Language Models (LLMs) hold promise as dynamic instructional aids. Yet, it remains unclear whether LLMs can replicate the adaptivity of intelligent tutoring systems (ITS)--where student knowledge and pedagogical strategies are explicitly modeled. We propose a prompt variation framework to assess LLM-generated instructional moves' adaptivity…
Descriptors: Benchmarking, Computational Linguistics, Artificial Intelligence, Computer Software
Du, Han; Enders, Craig; Keller, Brian; Bradbury, Thomas N.; Karney, Benjamin R. – Grantee Submission, 2022
Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…
Descriptors: Bayesian Statistics, Data Analysis, Computer Simulation, Sample Size
Vincent Aleven; Jori Blankestijn; LuEttaMae Lawrence; Tomohiro Nagashima; Niels Taatgen – Grantee Submission, 2022
Past research has yielded ample knowledge regarding the design of analytics-based tools for teachers and has found beneficial effects of several tools on teaching and learning. Yet there is relatively little knowledge regarding the design of tools that support teachers when a class of students uses AI-based tutoring software for self-paced…
Descriptors: Educational Technology, Artificial Intelligence, Problem Solving, Intelligent Tutoring Systems
Julie Sarno Owens; Mary Lee; Kelsey Eackles; Dassiell Medina; Steven W. Evans; Jacob Reid – Grantee Submission, 2022
Technology-based supports offer promise for helping elementary school teachers implement Tier 2 interventions to address challenging student behavior. The Daily Report Card Online (DRCO) platform is a cloud-based web application designed to support teachers' adoption and implementation of a high-quality daily report card (DRC) intervention through…
Descriptors: Intervention, Elementary School Teachers, Educational Technology, Report Cards
Natalie Brezack; Wynnie Chan; Mingyu Feng – Grantee Submission, 2024
This paper explores how learning analytics data provided by a math problem-solving educational technology platform informed 5th and 6th grade teachers' instructional decisions around socioemotional learning (SEL). MathSpring is an educational technology tool that provides teachers with data on students' effort, progress, and emotions while…
Descriptors: Social Emotional Learning, Mathematics Instruction, Teacher Attitudes, Comparative Analysis
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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
Jones, Francesca G.; Gifford, Diane; Yovanoff, Paul; Al Otaiba, Stephanie; Levy, Dawn; Allor, Jill – Grantee Submission, 2018
As part of standards-based reforms, there is increasing emphasis on ensuring that students with moderate intellectual disabilities (ID), including students with Autism Spectrum Disorders (ASD), learn to read. There is also converging evidence that explicit teaching of letter sounds, phonics, and sight words is effective for this population, but…
Descriptors: Alternative Assessment, Intellectual Disability, Progress Monitoring, Autism
Jaciw, Andrew P.; Cabalo, Jessica Villaruz; Vu, Minh-Thien – Grantee Submission, 2007
Introduction: The Maui Hawaii Educational consortium (the Maui School District and Maui Community College) sought scientifically based evidence for the effectiveness of the Cognitive Tutor (CT) Algebra I Curriculum to inform adoption decisions. Decision makers were particularly interested in whether the use of the CT program affects achievement of…
Descriptors: Algebra, Mathematics Instruction, Program Effectiveness, Mathematics Curriculum