Key research themes
1. How does Rasch analysis improve the validity and reliability of educational and psychological measurement instruments?
This research theme focuses on the application of Rasch measurement to develop, validate, and improve instruments used in education and psychology. It addresses how Rasch analysis enhances instrument quality by providing linear measurement, evaluating item fit and person fit, ensuring unidimensionality, and enabling meaningful interpretation of test scores. The theme also covers the validation of constructs (e.g., moral reasoning, classroom teaching quality) and the assessment of rater severity and expertise in scoring, with Rasch models providing more precise and invariant measurements compared to classical test theory approaches.
2. What advancements in Rasch model parameter estimation techniques enhance measurement accuracy, especially with small samples?
This theme examines methodological research comparing maximum likelihood estimation (MLE) approaches and Bayesian estimation (BE) techniques for estimating Rasch model parameters. It focuses on how BE provides improved accuracy and precision with small or limited data samples, overcoming limitations of traditional MLE methods. This research informs selection of estimation methods to achieve robust and reliable measurement outcomes in applied Rasch analyses.
3. How is scientometric and co-citation analysis used to map the evolution and influential trends within the Rasch measurement specialty?
This research converges on the scientometric investigation of the Rasch measurement field, utilizing author co-citation analysis, document co-citation analysis, journal co-citation analysis, and keyword mapping to delineate influential authors, seminal works, sub-specialties, and emerging research frontiers. Insights from this theme provide a meta-perspective on the intellectual structure, evolution, and interdisciplinary applications of Rasch measurement.