RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
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.
Advances in Health Sciences Education: Volume 27, p 1401–1422
After collecting eye-tracking data from 26 students responding to clinical MCQs, analysis is performed by providing 119 eye-tracking features as input for a machine-learning model aiming to classify correct and incorrect responses. The predictive power of various combinations of features within the model is evaluated to understand how different feature interactions contribute to the predictions.
JMIR Medical Education: Volume 8 - Issue 2 - e30988
This article aims to compare the reliability of two assessment groups (crowdsourced laypeople and patient advocates) in rating physician error disclosure communication skills using the Video-Based Communication Assessment app.
JMIR Medical Education: Volume 8 , Issue 4
The Video-based Communication Assessment (VCA) app is a novel tool for simulating communication scenarios for practice and obtaining crowdsourced assessments and feedback on physicians’ communication skills. This article aims to evaluate the efficacy of using VCA practice and feedback as a stand-alone intervention for the development of residents’ error disclosure skills.
ACM SIGACCESS Accessibility and Computing
In this article, we first summarise STA (Scanpath Trend Analysis) with its application in autism detection, and then discuss future directions for this research.
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 8 - p 838-841
Adaptive learning requires frequent and valid assessments for learners to track progress against their goals. This study determined if multiple-choice questions (MCQs) “crowdsourced” from medical learners could meet the standards of many large-scale testing programs.