Research Area
Table of Contents
- Psychometrics & Educational Measurement
- Latent Variable Modeling
- Sequential Analysis
- Additional Information
My work centers on Psychometrics, Latent Variable Modeling, Educational/Psychological Measurement, and Sequential Analysis. Of particular interest is the development and application of advanced statistical methods to improve our understanding of high-dimensional data, refine measurement tools, and promote more effective learning.
Psychometrics & Educational Measurement
Instrument/Test Development & Validation
Emphasizes the creation and rigorous evaluation of educational tests and surveys, ensuring reliability and validity across diverse populations. This includes deploying evidence-based quality metrics and harnessing innovative psychometric methods to refine measurement instruments.Cognitive Diagnosis Modeling (CDM)
Explores cutting-edge CDMs for adaptive assessment and real-time item selection, enabling more precise diagnostic feedback that supports targeted learning interventions. Research also examines procedures for aligning multiple test forms, setting performance standards, and maintaining rigor over time.Item Response Theory (IRT)
Leverages a spectrum of IRT-based models to optimize test scoring, build robust item banks, and power computerized adaptive testing. Current efforts focus on addressing multidimensional traits and incorporating novel item types, ultimately refining the accuracy and efficiency of educational and psychological measurement.
Latent Variable Modeling
Structural Equation Modeling (SEM)
Examines relationships among latent constructs to provide nuanced insights into factors such as motivation, engagement, and academic performance. Integrating theoretical frameworks with empirical data allows for evidence-based recommendations in both research and applied settings.Multilevel Modeling
Employs hierarchical and multilevel approaches to capture the complexity of nested data structures (e.g., student–classroom–school). These models reveal contextual effects that might otherwise remain hidden, offering a deeper understanding of learning processes and outcomes.Bayesian Approaches
Capitalizes on Bayesian inference for flexible model specification and robust parameter estimation, particularly when classical methods prove restrictive. This work addresses unique data challenges and uncertainty, fostering innovation in theory building and applied analysis.
Sequential Analysis
Sequential Hypothesis Testing
Applies sequential procedures to monitor incoming data, enabling faster and more efficient decisions in research and educational contexts. By continuously assessing evidence, resources can be conserved without sacrificing statistical integrity.Adaptive Designs
Develops adaptive sampling and experimental designs that respond in real-time to emerging data trends. These methodologies can boost power, reduce costs, and refine study direction as new insights surface.Real-Time Intervention Tracking
Advances methodologies for continuous observation and adjustment of interventions, allowing immediate responses that improve outcomes in both educational and psychological studies. This proactive approach bridges the gap between data collection and real-world impact.
Additional Information
Curriculum Vitae
A comprehensive record of publications, conference presentations, and teaching experiences is available in my CV.Contact
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Thank you for visiting my research page. New insights and developments will be added here as my work progresses!