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

A Comparison of Strategies for Smoothing Parameter Selection for Mixed-Format Tests Under the Random Groups Design

Posted: | C. Liu, M. J. Kolen

Journal of Educational Measurement: Volume 55, Issue 4, Pages 564-581

 

Smoothing techniques are designed to improve the accuracy of equating functions. The main purpose of this study is to compare seven model selection strategies for choosing the smoothing parameter (C) for polynomial loglinear presmoothing and one procedure for model selection in cubic spline postsmoothing for mixed‐format pseudo tests under the random groups design.

Category:Assessment-Oriented Research, Reliability/Validity, Scoring