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.
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.
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.