Call for Participation

We are announcing the first BEA (2024) shared-task on automated prediction of 
Difficulty And Response Time for Multiple Choice Questions (DART-MCQ).

Motivation

For standardized exams to be fair and valid, test questions, otherwise known as 
items, must meet certain criteria. One important criterion is that the items 
should cover a wide range of difficulty levels to gather information about the 
abilities of test takers effectively. Additionally, it is essential to allocate 
an appropriate amount of time for each item: too little time can make the exam 
speeded, while too much time can make it inefficient.

There is growing interest in predicting item characteristics such as difficulty 
and response time based on the item text. However, due to difficulties with 
sharing exam data, efforts to advance the state-of-the-art in item parameter 
prediction have been fragmented and conducted in individual institutions, with 
no transparent evaluation on a publicly available dataset. In this Shared Task, 
we bridge this gap by sharing practice item content and characteristics from a 
high-stakes medical exam called the United States Medical Licensing 
Examination® (USMLE®) for the exploration of two topics: predicting item 
difficulty (Track 1) and item response time (Track 2) based on item text.

Participation

The shared-task has two separate tracks as follows:

• Track 1: Given the item text and metadata, predict the item difficulty 
variable.
• Track 2: Given the item text and metadata, predict the time intensity 
variable.

Important Dates

Training data release: January 15
Test data release: February 10
Results due: February 16
Announcement of winners: February 21
Paper submissions due: March 10
Camera-ready papers due: April 22

Links

For more information about the shared task, see: 
https://sig-edu.org/sharedtask/2024

Organizers

Victoria Yaneva, National Board of Medical Examiners
Peter Baldwin, National Board of Medical Examiners
Kai North, George Mason University
Brian Clauser, National Board of Medical Examiners
Saed Rezayi, National Board of Medical Examiners
Yiyun Zhou, National Board of Medical Examiners
Le An Ha, Ho Chi Minh City University of Foreign Languages - Information 
Technology (HUFLIT)
Polina Harik, National Board of Medical Examiners
_______________________________________________
Corpora mailing list -- [email protected]
https://list.elra.info/mailman3/postorius/lists/corpora.list.elra.info/
To unsubscribe send an email to [email protected]

Reply via email to