AIAI (Artificial Intelligence for Advancing Instruction) Challenge - Phase 1

Classify instructional activities using multimodal classroom data. #education

$70,000 in prizes
5 days left
25 joined

Overview

Welcome to the Artificial Intelligence for Advancing Instruction (AIAI) Data Science Challenge! In this challenge, you will build models that classify instructional activities using multimodal classroom data.

Classroom observation videos provide valuable insights into a teacher's instruction, student interactions, and classroom dynamics. Over the past 15 years, their use in teacher preparation and the study of teacher quality has increased significantly. Classroom videos are also a common source of data for educational researchers studying classroom interactions as well as a resource for professional development. Despite this growth, using video at scale remains challenging due to the time and resources required for processing and analysis. In this challenge, you will build models to help automate classroom observation so that it can be offered at scale and inform future teaching.


Phases

There are two phases to this challenge:

  • Phase 1: Model Development (June 9th, 2025 – August 5th, 2025) ← you are here
    Participants develop and refine their models using the training dataset, then generate predictions for the Phase 1 test set. Submissions are evaluated against the test set labels and ranked on the Phase 1 leaderboard. These scores contribute 25% to final prize rankings.

  • Phase 2: Final Scoring (August 7th, 2025 – August 11th, 2025)
    Participants make one submission against a new, unseen test set. Submissions are evaluated against the Phase 2 test set labels and ranked on the Phase 2 leaderboard. These scores contribute 75% to final prize rankings.

Prizes

Phase 1 End Date:

Aug. 5, 2025, 11:59 p.m. UTC

Place Prize Amount (Phase 2)
1st $40,000
2nd $20,000
3rd $10,000

How to compete (Phase 1)

  1. Get permission to access the data and participate in the competition by requesting, completing, and submitting a data use agreement.
  2. Click the "Compete!" button in the sidebar to enroll in the competition.
  3. Get familiar with the problem through the overview and problem description. You might also want to reference additional resources available on the about page.
  4. Access the Training and Phase 1 competition data via Globus to train your own model.
  5. Use your model to generate predictions that match the submission format.
  6. Click “Submit” in the sidebar, and then “Make new submission”. You’re in!

Challenge rules

In addition to abiding to the terms of the data use agreement required to participate in this competition, participants must also adhere to the challenge rules. The challenge rules are in place to promote fair competition and useful solutions. If you are ever unsure whether your solution meets the challenge rules, ask the challenge organizers in the competition forum or send an email to info@drivendata.org.

Use of pre-trained models

Updated on July 1st, 2025 in response to a question on the forum

Participants may use pre-trained models provided that the models were publicly available under a free and open source license at the beginning of the competition. If you want to use a tool that is not clearly designated as open source, you must reach out to competition organizers for approval at info@drivendata.org.

This rule exists to ensure that participants have all rights, licenses, and permissions to include the tool as part of their submission as stated in the Competition Rules.


Challenge sponsor

Prize generously supplied by our friends from the Artificial Intelligence for Advancing Instruction (AIAI) project at the University of Virginia.

University of Virginia Logo UVA AIAI Logo

Images courtesy of the University of Virginia.