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Showing 1 to 15 of 217 results Save | Export
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Alexander Kwon; Kyungtae Lee – Evaluation Review, 2025
We study the external validity of instrumental variable estimation. The key assumption we impose for external validity is conditional external unconfoundedness among compliers, which means that the treatment effect and target selection are independent among compliers conditional on covariates. We study this assumption with a case study about the…
Descriptors: Validity, Computation, Time Management, Fuels
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Valentina Gliozzi – Cognitive Science, 2024
We propose a simple computational model that describes potential mechanisms underlying the organization and development of the lexical-semantic system in 18-month-old infants. We focus on two independent aspects: (i) on potential mechanisms underlying the development of taxonomic and associative priming, and (ii) on potential mechanisms underlying…
Descriptors: Infants, Computation, Models, Cognitive Development
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Njål Foldnes; Jonas Moss; Steffen Grønneberg – Structural Equation Modeling: A Multidisciplinary Journal, 2025
We propose new ways of robustifying goodness-of-fit tests for structural equation modeling under non-normality. These test statistics have limit distributions characterized by eigenvalues whose estimates are highly unstable and biased in known directions. To take this into account, we design model-based trend predictions to approximate the…
Descriptors: Goodness of Fit, Structural Equation Models, Robustness (Statistics), Prediction
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Liqing Qiu; Lulu Wang – IEEE Transactions on Education, 2025
In recent years, knowledge tracing (KT) within intelligent tutoring systems (ITSs) has seen rapid development. KT aims to assess a student's knowledge state based on past performance and predict the correctness of the next question. Traditional KT often treats questions with different difficulty levels of the same concept as identical…
Descriptors: Intelligent Tutoring Systems, Technology Uses in Education, Questioning Techniques, Student Evaluation
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Peter Z. Schochet – Journal of Educational and Behavioral Statistics, 2025
Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
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Tian Li; Gaomin Sun; Xinlin Zhou; Tengfei Wang – Educational Psychology, 2023
The close relationship between working memory and maths problem solving is generally accepted, but the specifics of how working memory and its subcomponents contribute to maths problem solving remain poorly understood. Tests of working memory, maths problem problem solving, calculation, and intelligence were administered to 246 university…
Descriptors: Mathematics, Short Term Memory, Problem Solving, Computation
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Adams, William; Sonntag, Matthew D. – Journal of Chemical Education, 2022
Electrophilic aromatic substitution (EAS) represents an important class of reactions taught in the undergraduate organic chemistry curriculum. The EAS reaction of benzene and its substituted derivatives is generally described as proceeding through a carbocation (arenium cation) intermediate, and the regiochemistry of the product is heavily…
Descriptors: Undergraduate Students, Science Activities, Computation, Prediction
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Kun Sun; Rong Wang – Cognitive Science, 2025
The majority of research in computational psycholinguistics on sentence processing has focused on word-by-word incremental processing within sentences, rather than holistic sentence-level representations. This study introduces two novel computational approaches for quantifying sentence-level processing: sentence surprisal and sentence relevance.…
Descriptors: Reading Rate, Reading Comprehension, Sentences, Computation
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Tan, Hongye; Wang, Chong; Duan, Qinglong; Lu, Yu; Zhang, Hu; Li, Ru – Interactive Learning Environments, 2023
Automatic short answer grading (ASAG) is a challenging task that aims to predict a score for a given student response. Previous works on ASAG mainly use nonneural or neural methods. However, the former depends on handcrafted features and is limited by its inflexibility and high cost, and the latter ignores global word cooccurrence in a corpus and…
Descriptors: Automation, Grading, Computer Assisted Testing, Graphs
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Anzola, David; García-Díaz, César – International Journal of Social Research Methodology, 2023
Researchers have become increasingly interested in the potential use of agent-based modelling for the prediction of social phenomena, motivated by the desire, first, to further cement the method's scientific status and, second, to participate in other scenarios, particularly in the aid of decision-making. This article contributes to the current…
Descriptors: Prediction, Models, Computation, Social Sciences
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Albreiki, Balqis; Habuza, Tetiana; Zaki, Nazar – International Journal of Educational Technology in Higher Education, 2023
Technological advances have significantly affected education, leading to the creation of online learning platforms such as virtual learning environments and massive open online courses. While these platforms offer a variety of features, none of them incorporates a module that accurately predicts students' academic performance and commitment.…
Descriptors: Identification, At Risk Students, Artificial Intelligence, Academic Achievement
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Russo, James; MacDonald, Amy; Russo, Toby – International Journal of Science and Mathematics Education, 2022
Estimation supports the development of higher level mathematical thinking and reasoning; however, has received relatively little research attention. We examined whether making predictions influences the accuracy of numerosity estimates in elementary-aged children, and whether the amount of information available to the estimator determines the…
Descriptors: Elementary School Students, Grade 2, Grade 6, Prediction
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Peter Schochet – Society for Research on Educational Effectiveness, 2024
Random encouragement designs are randomized controlled trials (RCTs) that test interventions aimed at increasing participation in a program or activity whose take up is not universal. In these RCTs, instead of randomizing individuals or clusters directly into treatment and control groups to participate in a program or activity, the randomization…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
Yanli Xie – ProQuest LLC, 2022
The purpose of this dissertation is to develop principles and strategies for and identify limitations of multisite cluster randomized trials in the context of partially and fully nested designs. In the first study, I develop principles of estimation, sampling variability, and inference for studies that leverage multisite designs within the context…
Descriptors: Randomized Controlled Trials, Research Design, Computation, Sampling
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Brendan A. Schuetze – Educational Psychology Review, 2024
The computational model of school achievement represents a novel approach to theorizing school achievement, conceptualizing educational interventions as modifications to students' learning curves. By modeling the process and products of educational achievement simultaneously, this tool addresses several unresolved questions in educational…
Descriptors: Computation, Growth Models, Academic Achievement, Student Evaluation
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