Huan Kuang
Datos Biográficos
| ID | 9252718 |
|---|---|
| NOMBRE | Huan Kuang |
| NOMBRES | Huan |
| APELLIDO | Kuang |
| FIRMA | KUANG H |
| AFILIACIONES | University of Florida |
| ORCID | 0000-0003-2651-2867 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 6 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 6 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2021 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 0 |
Evaluating Neural Networks Architectures for Competency Prediction from Process Data Using Pisa Computer-Based Mathematics Assessment
Computer-based assessments generate rich process data that captures examinees’ interactions with test items. Using process data from the U.S. PISA 2012 computer-based mathematics assessment sample, this study applied recurrent neural networks to predict item-level correctness and assessment-level latent proficiency. The analysis also examines the impact of expert-engineered features, levels of architectural complexity, action variability, and sco…
Enhancing Effort-Moderated Item Response Theory Models by Evaluating a Two-Step Estimation Method and Multidimensional Variations on the Model
Rapid-guessing behavior in data can compromise our ability to estimate item and person parameters accurately. Consequently, it is crucial to model data with rapid-guessing patterns in a way that can produce unbiased ability estimates. This study proposes and evaluates three alternative modeling approaches that follow the logic of the effort-moderated item response theory model (EM-IRT) to analyze response data with rapid-guessing responses. One i…
Exploring the Evidence to Interpret Differential Item Functioning via Response Process Data
Evaluating differential item functioning (DIF) in assessments plays an important role in achieving measurement fairness across different subgroups, such as gender and native language. However, relying solely on the item response scores among traditional DIF techniques poses challenges for researchers and practitioners in interpreting DIF. Recently, response process data, which carry valuable information about examinees’ response behaviors, offer …
Model Specification Searches in Structural Equation Modeling with a Hybrid Ant Colony Optimization Algorithm
Model specification is a crucial aspect of structural equation modeling (SEM), since a misspecified model may lead to biased parameter estimation and result in inaccurate conclusions. We propose the Hybrid Ant Colony Optimization Algorithm (hACO), an improved metaheuristic algorithm to conduct model specification searches in SEM. This data mining algorithm combines aspects of the Ant Colony Optimization algorithm with the Tabu search algorithm to…
The relationship between self-regulated student use of a virtual learning environment for algebra and student achievement
Multilevel Mixture Modeling with Propensity Score Weights for Quasi-Experimental Evaluation of Virtual Learning Environments
With the growing use of virtual learning environments (VLE), innovative methods to evaluate their performance are increasingly needed. A key difficulty in evaluating VLE using system logs is the large heterogeneity of usage patterns. The current study demonstrates an approach to classify complex patterns of student-level and classroom-level usage with latent class analysis, then estimate average treatment effects (ATEs) of membership in student o…
Sin obras prominentes en esta página.
Multilevel Mixture Modeling with Propensity Score Weights for Quasi-Experimental Evaluation of Virtual Learning Environments
With the growing use of virtual learning environments (VLE), innovative methods to evaluate their performance are increasingly needed. A key difficulty in evaluating VLE using system logs is the large heterogeneity of usage patterns. The current study demonstrates an approach to classify complex patterns of student-level and classroom-level usage with latent class analysis, then estimate average treatment effects (ATEs) of membership in student o…
Model Specification Searches in Structural Equation Modeling with a Hybrid Ant Colony Optimization Algorithm
Model specification is a crucial aspect of structural equation modeling (SEM), since a misspecified model may lead to biased parameter estimation and result in inaccurate conclusions. We propose the Hybrid Ant Colony Optimization Algorithm (hACO), an improved metaheuristic algorithm to conduct model specification searches in SEM. This data mining algorithm combines aspects of the Ant Colony Optimization algorithm with the Tabu search algorithm to…
The relationship between self-regulated student use of a virtual learning environment for algebra and student achievement
Enhancing Effort-Moderated Item Response Theory Models by Evaluating a Two-Step Estimation Method and Multidimensional Variations on the Model
Rapid-guessing behavior in data can compromise our ability to estimate item and person parameters accurately. Consequently, it is crucial to model data with rapid-guessing patterns in a way that can produce unbiased ability estimates. This study proposes and evaluates three alternative modeling approaches that follow the logic of the effort-moderated item response theory model (EM-IRT) to analyze response data with rapid-guessing responses. One i…
Exploring the Evidence to Interpret Differential Item Functioning via Response Process Data
Evaluating differential item functioning (DIF) in assessments plays an important role in achieving measurement fairness across different subgroups, such as gender and native language. However, relying solely on the item response scores among traditional DIF techniques poses challenges for researchers and practitioners in interpreting DIF. Recently, response process data, which carry valuable information about examinees’ response behaviors, offer …
Evaluating Neural Networks Architectures for Competency Prediction from Process Data Using Pisa Computer-Based Mathematics Assessment
Computer-based assessments generate rich process data that captures examinees’ interactions with test items. Using process data from the U.S. PISA 2012 computer-based mathematics assessment sample, this study applied recurrent neural networks to predict item-level correctness and assessment-level latent proficiency. The analysis also examines the impact of expert-engineered features, levels of architectural complexity, action variability, and sco…
Computer Science (5 obras) · Mathematics (4 obras) · Machine learning (3 obras) · Psychometric Methodologies and Testing (3 obras) · Statistics (3 obras) · Advanced Statistical Modeling Techniques (2 obras) · Algorithm (2 obras) · Artificial Intelligence (2 obras) · Econometrics (2 obras) · Item response theory (2 obras)