Showing 1 - 4 of 4 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

Reporting Subscore Profiles Using Diagnostic Classification Models in Health Professions Education

Posted: | Y.S. Park, A. Morales, L. Ross, M. Paniagua

Evaluation & the Health Professions: Volume: 43 issue: 3, page(s): 149-158

 

This study examines the innovative and practical application of DCM framework to health professions educational assessments using retrospective large-scale assessment data from the basic and clinical sciences: National Board of Medical Examiners Subject Examinations in pathology (n = 2,006) and medicine (n = 2,351).

Category:Assessment-Oriented Research, Scoring, Product-Oriented Research, NBME

Detecting High-Functioning Autism In Adults Using Eye Tracking And Machine Learning

Posted: | V. Yaneva, L. A. Ha, S. Eraslan, Y. Yesilada, R. Mitkov

IEEE Transactions on Neural Systems and Rehabilitation Engineering

 

The purpose of this study is to test whether visual processing differences between adults with and without high-functioning autism captured through eye tracking can be used to detect autism.

Category:Assessment-Oriented Research, Applications of Technology

Conditional Subscore Reporting Using Iterated Discrete Convolutions

Posted: | R.A. Feinberg, M. von Davier

Journal of Educational and Behavioral Statistics: Vol 45, Issue 5, 2020

 

This article describes a method for identifying and reporting unexpectedly high or low subscores by comparing each examinee’s observed subscore with a discrete probability distribution of subscores conditional on the examinee’s overall ability.

Category:Assessment-Oriented Research, Scoring