Medical Teacher: Volume 45 - Issue 6, Pages 565-573
This guide aims aim to describe practical considerations involved in reading and conducting studies in medical education using Artificial Intelligence (AI), define basic terminology and identify which medical education problems and data are ideally-suited for using AI.
Neural Engineering Techniques for Autism Spectrum Disorder: Volume 2, Pages 63-79
Automated detection of high-functioning autism in adults is a highly challenging and understudied problem. In search of a way to automatically detect the condition, this chapter explores how eye-tracking data from reading tasks can be used.
Academic Medicine: Volume 98 - Issue 2 - Pages 162-170
The US medical education transition from school to residency is resource-intensive. The Coalition for Physician Accountability aims to improve it, emphasizing learner support, diversity, and minimizing conflicts. This study explores key tensions and offers strategies to align the transition with ideal goals, aiding educators and organizations in implementing recommendations.
Behavior & Information Technology
This study builds upon prior work in this area that focused on developing a machine-learning classifier trained on gaze data from web-related tasks to detect ASD in adults. Using the same data, we show that a new data pre-processing approach, combined with an exploration of the performance of different classification algorithms, leads to an increased classification accuracy compared to prior work.
Journal of Applied Technology: Volume 23 - Special Issue 1 - Pages 30-40
The interpretations of test scores in secure, high-stakes environments are dependent on several assumptions, one of which is that examinee responses to items are independent and no enemy items are included on the same forms. This paper documents the development and implementation of a C#-based application that uses Natural Language Processing (NLP) and Machine Learning (ML) techniques to produce prioritized predictions of item enemy statuses within a large item bank.
Journal of Educational Measurement: Volume 58, Issue 4, Pages 515-537
In this paper, the NBME team reports the results an eye-tracking study designed to evaluate how the presence of the options in multiple-choice questions impacts the way medical students responded to questions designed to evaluate clinical reasoning. Examples of the types of data that can be extracted are presented. We then discuss the implications of these results for evaluating the validity of inferences made based on the type of items used in this study.
Academic Medicine: Volume 96 - Issue 9 - Pages 1324-1331
This study examines associations between USMLE Step 1 and Step 2 Clinical Knowledge (CK) scores and ACGME emergency medicine (EM) milestone ratings.
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.
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.
Medical Teacher: Volume 40 - Issue 11 - p 1143-1150
This study explores a novel milestone-based workplace assessment system that was implemented in 15 pediatrics residency programs. The system provided: web-based multisource feedback and structured clinical observation instruments that could be completed on any computer or mobile device; and monthly feedback reports that included competency-level scores and recommendations for improvement.