Showing 1 - 2 of 2 Research Library Publications

The Role of Data Science and Machine Learning in Health Professions Education: Practical Applications, Theoretical Contributions, and Epistemic Beliefs

Posted: | Martin G. Tolsgaard, Christy K. Boscardin, Yoon Soo Park, Monica M. Cuddy, Stefanie S. Sebok-Syer

Advances in Health Sciences Education: Volume 25, p 1057–1086 (2020)

 

This critical review explores: (1) published applications of data science and ML in HPE literature and (2) the potential role of data science and ML in shifting theoretical and epistemological perspectives in HPE research and practice.

Category:Assessment-Oriented Research, General Measurement, Health Professions

Examining the Precision of Cut Scores Within a Generalizability Theory Framework: A Closer Look at the Item Effect

Posted: | B. E. Clauser, M. Kane, J. C. Clauser

Journal of Educational Measurement: Volume 57, Issue 2, Pages 216-229

 

This article presents two generalizability-theory–based analyses of the proportion of the item variance that contributes to error in the cut score. For one approach, variance components are estimated on the probability (or proportion-correct) scale of the Angoff judgments, and for the other, the judgments are transferred to the theta scale of an item response theory model before estimating the variance components.

Category:Assessment-Oriented Research, Reliability/Validity