Wenchao Ma, Miguel A. Sorrel, Xiaoming Zhai, Yuan Ge
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A Dual-Purpose Model for Binary Data: Estimating Ability and Misconceptions
Most existing diagnostic models are developed to detect whether students have mastered a set of skills of interest, but few have focused on identifying what scientific misconceptions students possess. This article developed a general dual-purpose model for simultaneously estimating students' overall ability and the presence and absence of misconceptions. The expectation-maximization algorithm was developed to estimate the model parameters. A simulation study was conducted to evaluate to what extent the parameters can be accurately recovered under varied conditions. A set of real data in science education was also analyzed to examine the viability of the proposed model in practice.
期刊介绍:
The Journal of Educational Measurement (JEM) publishes original measurement research, provides reviews of measurement publications, and reports on innovative measurement applications. The topics addressed will interest those concerned with the practice of measurement in field settings, as well as be of interest to measurement theorists. In addition to presenting new contributions to measurement theory and practice, JEM also serves as a vehicle for improving educational measurement applications in a variety of settings.