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Direct linkAlexander 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
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
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
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
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
Fangli Xia; Mitchell J. Nathan; Kelsey E. Schenck; Michael I. Swart – Cognitive Science, 2025
Task-relevant actions can facilitate mathematical thinking, even for complex topics, such as mathematical proof. We investigated whether such cognitive benefits also occur for action predictions. The action-cognition transduction (ACT) model posits a reciprocal relationship between movements and reasoning. Movements--imagined as well as real ones…
Descriptors: Undergraduate Students, Geometry, Mathematical Concepts, Mathematics Instruction
