Showing 1 - 2 of 2 Research Library Publications

ACTA: Short-Answer Grading in High-Stakes Medical Exams

Posted: | King Yiu Suen, Victoria Yaneva, Le An Ha, Janet Mee, Yiyun Zhou, Polina Harik

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. 

Category:Assessment-Oriented Research, Scoring, General Measurement

The Optimal Number of Options for Multiple-Choice Questions on High-Stakes Tests: Application of a Revised Index for Detecting Nonfunctional Distractors

Posted: | M.R. Raymond, C. Stevens, S.D. Bucak

Adv in Health Sci Educ 24, 141–150 (2019)

 

Research suggests that the three-option format is optimal for multiple choice questions (MCQs). This conclusion is supported by numerous studies showing that most distractors (i.e., incorrect answers) are selected by so few examinees that they are essentially nonfunctional. However, nearly all studies have defined a distractor as nonfunctional if it is selected by fewer than 5% of examinees.

Category:Assessment-Oriented Research, General Measurement