Showing 1 - 4 of 4 Research Library Publications

Three Sources of Validation Evidence Needed to Evaluate the Quality of Generated Test Items for Medical Licensure

Posted: | Mark Gierl, Kimberly Swygert, Donna Matovinovic, Allison Kulesher, Hollis Lai

Teaching and Learning in Medicine: Volume 33 - Issue 4 - p 366-381

 

The purpose of this analysis is to describe these sources of evidence that can be used to evaluate the quality of generated items. The important role of medical expertise in the development and evaluation of the generated items is highlighted as a crucial requirement for producing validation evidence.

Category:Assessment-Oriented Research, Other

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

Palliative Care Competencies and Readiness for Independent Practice: A Report on the American Academy of Hospice and Palliative Medicine Review of the U.S. Medical Licensing Step Examinations

Posted: | E. C. Carey, M. Paniagua, L. J. Morrison, S. K. Levine, J. C. Klick, G. T. Buckholz, J. Rotella, J. Bruno, S. Liao, R. M. Arnold

Journal of Pain and Symptom Management: Volume 56, Issue 3, p371-378

 

This article reviews the USMLE step examinations to determine whether they test the palliative care (PC) knowledge necessary for graduating medical students and residents applying for licensure.

Category:Assessment-Oriented Research, Reliability/Validity, Product-Oriented Research, USMLE, Health Professions

Automated Item Generation with Recurrent Neural Networks

Posted: | M. von Davier

Psychometrika 83, 847–857 (2018)

 

Utilizing algorithms to generate items in educational and psychological testing is an active area of research for obvious reasons: Test items are predominantly written by humans, in most cases by content experts who represent a limited and potentially costly resource. Using algorithms instead has the appeal to provide an unlimited resource for this crucial part of assessment development.

Category:Assessment-Oriented Research, Applications of Technology