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Caitlin Snyder; Clayton Cohn; Joyce Horn Fonteles; Gautam Biswas – Grantee Submission, 2025
Recently, there has been a surge in developing curricula and tools that integrate computing (C) into Science, Technology, Engineering, and Math (STEM) programs. These environments foster authentic problem-solving while facilitating students' concurrent learning of STEM+C content. In our study, we analyzed students' behaviors as they worked in…
Descriptors: Learning Analytics, Problem Solving, STEM Education, Computation
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David Bruns-Smith; Oliver Dukes; Avi Feller; Elizabeth L. Ogburn – Grantee Submission, 2024
We provide a novel characterization of augmented balancing weights, also known as automatic debiased machine learning (AutoDML). These popular "doubly robust" or "de-biased machine learning estimators" combine outcome modeling with balancing weights -- weights that achieve covariate balance directly in lieu of estimating and…
Descriptors: Regression (Statistics), Weighted Scores, Data Analysis, Robustness (Statistics)
Dan Soriano; Eli Ben-Michael; Peter Bickel; Avi Feller; Samuel D. Pimentel – Grantee Submission, 2023
Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…
Descriptors: Statistical Analysis, Computation, Mathematical Formulas, Monte Carlo Methods
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Han Du; Brian Keller; Egamaria Alacam; Craig Enders – Grantee Submission, 2023
In Bayesian statistics, the most widely used criteria of Bayesian model assessment and comparison are Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC). A multilevel mediation model is used as an illustrative example to compare different types of DIC and WAIC. More specifically, the study compares the…
Descriptors: Bayesian Statistics, Models, Comparative Analysis, Probability
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Dongho Shin – Grantee Submission, 2024
We consider Bayesian estimation of a hierarchical linear model (HLM) from small sample sizes. The continuous response Y and covariates C are partially observed and assumed missing at random. With C having linear effects, the HLM may be efficiently estimated by available methods. When C includes cluster-level covariates having interactive or other…
Descriptors: Bayesian Statistics, Computation, Hierarchical Linear Modeling, Data Analysis
Amber Y. Wang; Lynn S. Fuchs; Kristopher J. Preacher; Douglas Fuchs; Amelia S. Malone; Rachel Pachmayr – Grantee Submission, 2019
The study has two primary purposes. The first was to examine the efficacy of the "Super Solvers" Fractions Intervention (SSFI) for third-grade students at risk for mathematics learning disabilities (MLD). The second was to test the added value of embedding self-regulation instruction into the SSFI. Students were randomly assigned to a…
Descriptors: Program Effectiveness, Fractions, Problem Solving, Mathematics Instruction
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Burhan Ogut; Blue Webb; Juanita Hicks; Ruhan Circi; Michelle Yin – Grantee Submission, 2024
In this study, we explore the application of process mining techniques on assessment log data to explore problem-solving strategies in Algebra. By analyzing sequences of student activities, we demonstrate the significant potential of process mining in identifying problem-solving strategies that lead to successful and unsuccessful outcomes. Our…
Descriptors: Mathematics Skills, Problem Solving, Learning Analytics, Algebra
Lynn S. Fuchs; Amelia S. Malone; Kristopher J. Preacher; Douglas Fuchs; Amber Y. Wang; Rachel Pachmayr – Grantee Submission, 2019
The purposes of this study were twofold. The first was to test the efficacy of two versions of the "Super Solvers" (SS) intervention for fourth- and fifth-grade students at-risk for mathematics learning disabilities (MLD). The second was to test the value of adding an error analysis component to the SS intervention. Students were…
Descriptors: Program Effectiveness, Fractions, Problem Solving, Mathematics Instruction
Robert C. Schoen; Wendy S. Bray; Amanda M. Tazaz; Charity K. Buntin – Grantee Submission, 2022
Cognitively Guided Instruction (CGI) is a teacher PD program that has been found to have a potentially positive impact on student learning in mathematics through randomized controlled trials. Through a series of grant-funded projects led by FSU, approximately 2,000 Florida teachers have participated in CGI-based professional development in the…
Descriptors: Mathematics Instruction, Teaching Methods, Mathematics Teachers, Faculty Development
Xu, Ziqian; Hai, Jiarui; Yang, Yutong; Zhang, Zhiyong – Grantee Submission, 2022
Social network data often contain missing values because of the sensitive nature of the information collected and the dependency among the network actors. As a response, network imputation methods including simple ones constructed from network structural characteristics and more complicated model-based ones have been developed. Although past…
Descriptors: Social Networks, Network Analysis, Data Analysis, Bayesian Statistics
Chan, Jenny Yun-Chen; Smith, Hannah; Closser, Avery H.; Drzewiecki, Katharine C.; Ottmar, Erin R. – Grantee Submission, 2021
Numbers and variables often follow the same principles of arithmetic operations, yet numbers can be computed to a value whereas variables cannot. We examined the effect of symbols--numbers versus variables--on middle school students' problem-solving behaviors in a dynamic algebra notation system by presenting problems in numbers (e.g., 3+5-3) or…
Descriptors: Symbols (Mathematics), Numbers, Middle School Students, Mathematics Instruction
Sinharay, Sandip – Grantee Submission, 2017
Wollack, Cohen, and Eckerly (2015) suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly (2017) extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This paper suggests two modifications of…
Descriptors: Deception, Identification, Testing Problems, Cheating
Sidney, Pooja G.; Thalluri, Rajaa; Buerke, Morgan L.; Thompson, Clarissa A. – Grantee Submission, 2018
Adults use a variety of strategies to reason about fraction magnitudes, and this variability is adaptive. In two studies, we examined the relationships between mathematics anxiety, working memory, strategy variability and performance on two fraction tasks: fraction magnitude "comparison" and "estimation." Adults with higher…
Descriptors: Adults, Fractions, Mathematics Anxiety, Short Term Memory
Schoen, Robert C.; LaVenia, Mark; Champagne, Zachary M.; Farina, Kristy; Tazaz, Amanda M. – Grantee Submission, 2017
The following report describes an assessment instrument called the Mathematics Performance and Cognition (MPAC) interview. The MPAC interview was designed to measure two outcomes of interest. It was designed to measure first and second graders' mathematics achievement in number, operations, and equality, and it was also designed to gather…
Descriptors: Interviews, Test Construction, Psychometrics, Elementary School Mathematics
Schoen, Robert C.; LaVenia, Mark; Champagne, Zachary M.; Farina, Kristy – Grantee Submission, 2017
This report provides an overview of the development, implementation, and psychometric properties of a student mathematics interview designed to assess first- and second-grade student achievement and thinking processes. The student interview was conducted with 622 first- or second-grade students in 22 schools located in two public school districts…
Descriptors: Interviews, Test Construction, Psychometrics, Elementary School Mathematics
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