Diagnostic Questions: Predicting Student Responses and Measuring Question Quality

Important Dates:
July 15, 2020: Tasks released
October 23, 2020: Final submission deadline for all tasks
November 15, 2020: Final competition results announced

Contact: edu_competition@outlook.com

Digital technologies are becoming increasingly prevalent in education, enabling personalized, high quality education resources to be accessible by students across the world. Importantly, among these resources are diagnostic questions: the answers that the students give to these questions reveal key information about the specific nature of misconceptions that the students may hold.

Analyzing the massive quantities of data stemming from students’ interactions with these diagnostic questions can help us more accurately understand the students’ learning status and thus allow us to automate learning curriculum recommendations. In this competition, participants will focus on the students’ answer records to these multiple-choice diagnostic questions, with the aim of 1) accurately predicting which answers the students provide; 2) accurately predict which questions have high quality; and 3) determine a personalized sequence of questions for each student that best predicts the student’s answers. These tasks closely mimic the goals of a real-world educational platform and are highly representative of the educational challenges faced today. We provide data from the last school year (2018-2019) of students’ answers to mathematics questions from Eedi, a leading educational platform which millions of students interact with daily around the globe. Successful competition entrants have the potential to make a lasting, real-world impact on the quality of personalized education for millions of students across the world.

Calls

The competition is now open on CodaLab!