RESEARCH LIBRARY

Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), Pages 443-447

This paper presents the ACTA system, which performs automated short-answer grading in the domain of high-stakes medical exams. The system builds upon previous work on neural similarity-based grading approaches by applying these to the medical domain and utilizing contrastive learning as a means to optimize the similarity metric. 

Integrating Timing Considerations to Improve Testing Practices

This chapter addresses timing considerations in the context of other types of performance assessments and reports on a previously unpublished experiment examining timing with respect to performance on computer-based case simulations that are used in physician licensure.