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Yue Zhao – ProQuest LLC, 2024
Multivariate Functional Principal Component Analysis (MFPCA) is a valuable tool for exploring relationships and identifying shared patterns of variation in multivariate functional data. However, interpreting these functional principal components (PCs) can sometimes be challenging due to issues such as roughness and sparsity. In this dissertation,…
Descriptors: Factor Analysis, Functional Literacy, Data Use, Mathematical Applications
Devashi Gulati – ProQuest LLC, 2024
This dissertation explores bridge n-sections of knotted surfaces in 4-manifolds by defining invariants that measure the complexity of their topology and by giving geometric constructions that determine Lagrangian surfaces in 4-manifolds under certain conditions. First, we present an elegant geometric construction that generates all triple grid…
Descriptors: Mathematics Education, Geometric Concepts, Visual Aids, Topology
Tarryn Lovemore – Mathematics Education Research Group of Australasia, 2024
This paper is part of a broader study which explores South African pre-service teachers' use of the jump strategy on the empty number line for enhancing their confidence to do and teach mental mathematics computation strategies. The focus of this paper is the use of micro-teaching in the form of video recordings by pre-service teachers. Forty…
Descriptors: Foreign Countries, Preservice Teachers, Microteaching, Mathematics Instruction
Michael Nagel; Lukas Fischer; Tim Pawlowski; Augustin Kelava – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Bayesian estimations of complex regression models with high-dimensional parameter spaces require advanced priors, capable of addressing both sparsity and multicollinearity in the data. The Dirichlet-horseshoe, a new prior distribution that combines and expands on the concepts of the regularized horseshoe and the Dirichlet-Laplace priors, is a…
Descriptors: Bayesian Statistics, Regression (Statistics), Computation, Statistical Distributions
Eli Ben-Michael; Lindsay Page; Luke Keele – Grantee Submission, 2024
In a clustered observational study, a treatment is assigned to groups and all units within the group are exposed to the treatment. We develop a new method for statistical adjustment in clustered observational studies using approximate balancing weights, a generalization of inverse propensity score weights that solve a convex optimization problem…
Descriptors: Research Design, Statistical Data, Multivariate Analysis, Observation
Hilary Wething – Economic Policy Institute, 2024
Universal voucher programs for schools are rapidly expanding across the country. Under these programs, states give parents stipends to either homeschool their children or send them to private school. The growing popularity of vouchers raises a host of crucial questions and concerns. Key to informing the debate are questions of public finance and…
Descriptors: Educational Vouchers, Public Education, Educational Finance, Costs
Nanette M. Wachter; Evan H. Kreth; Ronald P. D'Amelia – Journal of Chemical Education, 2024
Keto-enol tautomerization is paramount to understanding the mechanisms involved in many organic reactions and biochemical transformations. Isomerization of an enol to a carbonyl compound is typically introduced during the discussion of the acid-catalyzed electrophilic addition of water to alkynes. The tautomerization of carbonyl compounds to enol…
Descriptors: Science Instruction, Chemistry, Scientific Concepts, Concept Formation
Sangbaek Park – ProQuest LLC, 2024
This dissertation used synthetic datasets, semi-synthetic datasets, and a real-world dataset from an educational intervention to compare the performance of 15 machine learning and multiple imputation methods to estimate the individual treatment effect (ITE). In addition, it examined the performance of five evaluation metrics that can be used to…
Descriptors: Artificial Intelligence, Computation, Evaluation Methods, Bayesian Statistics
Sebastian Holt; David Barner – Cognitive Science, 2025
Humans count to indefinitely large numbers by recycling words from a finite list, and combining them using rules--for example, combining sixty with unit labels to generate sixty-one, sixty-two, and so on. Past experimental research has focused on children learning base-10 systems, and has reported that this rule learning process is highly…
Descriptors: Computation, Numbers, Adult Students, Number Concepts
Jianbin Fu; TsungHan Ho; Xuan Tan – Practical Assessment, Research & Evaluation, 2025
Item parameter estimation using an item response theory (IRT) model with fixed ability estimates is useful in equating with small samples on anchor items. The current study explores the impact of three ability estimation methods (weighted likelihood estimation [WLE], maximum a posteriori [MAP], and posterior ability distribution estimation [PST])…
Descriptors: Item Response Theory, Test Items, Computation, Equated Scores
Jess Sullivan; Joseph Alvarez; Sophie Cramer-Benjamin; Sadie Holcomb; Melissa Nolan; Alex Morabito; David Barner – Journal of Numerical Cognition, 2025
When children first learn to count, what do they understand about the structure of the count system? The present study investigated English-speaking children's ability to generalize the rules that structure their count list to novel contexts. A total of N = 86 children (3;0-6;11) completed a battery of tasks aimed at measuring their understanding…
Descriptors: Computation, Young Children, Novelty (Stimulus Dimension), English
Theresa Elise Wege; Taeko Bourque; Rebecca Merkley; Pierina Cheung – Journal of Numerical Cognition, 2025
The Give-N (give-a-number) task has become a popular assessment of children's number words and counting knowledge since Wynn's (1990, 1992) seminal work over 30 years ago. Using the Give-N task, numerous studies have shown that children learn the first few number words slowly, before they understand how counting represents number. This learning…
Descriptors: Knowledge Level, Numbers, Vocabulary, Computation
Wanichaya Srisuk; Suwat Julsuwan – Journal of Education and Learning, 2025
This research aimed to: (1) investigate the components and indicators of computational thinking learning experience management competency of early childhood teachers in educational institutions under the Office of the Basic Education Commission; and (2) examine the congruence of these components and indicators. The research was conducted in two…
Descriptors: Computation, Thinking Skills, Early Childhood Teachers, Early Childhood Education
Andrea Ramirez-Salgado; Christine Wusylko; Lauren Weisberg; Johnny Delgado; Maya Israel – ACM Transactions on Computing Education, 2025
Computational Thinking (CT) is a critical set of 21st-century skills that young learners must develop to be successful in contemporary work and life. As more K-12 schools begin to integrate CT into the curriculum, Elementary Preservice Teachers (EPSTs) must be prepared to teach CT to their future students. Therefore, elementary teacher preparation…
Descriptors: Elementary School Teachers, Preservice Teachers, Computation, Thinking Skills
Ricca, Bernard P.; Blaine, Bruce E. – Journal of Experimental Education, 2022
Researchers are encouraged to report effect size statistics to quantify treatment effects or effects due to group differences. However, estimates of effect sizes, most commonly Cohen's "d," make assumptions about the distribution of data that are not always true. An alternative nonparametric estimate of effect size, relying on the median…
Descriptors: Nonparametric Statistics, Computation, Effect Size

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