AAAI2024 Workshop on AI for Education - Bridging Innovation and Responsibility

AAAI2024 Workshop on AI for Education - Bridging Innovation and Responsibility

Workshop Overview

This two-day in-person workshop explores the innovations in artificial intelligence (AI), specifically generative-AI (GenAI), in educational applications, and discusses the related ethical implications of responsible-AI (RAI). Over two days, attendees will examine GenAI technologies, potential vulnerabilities, and the development of RAI standards in an educational context. Through a variety of formats like papers, demonstrations, posters, a global competition on Math reasoning, and opportunities to hear experts and representatives from various communities, participants will explore AI’s impact on instruction quality, learner outcomes, and ethics. This workshop ultimately aims to inspire novel ideas, foster partnerships, and navigate the ethical complexities of AI in education.

Date: February 26-27, 2024
Location: Vancouver Convention Center, Vancouver, Canada

Topics of interest

Day 1. Cognitive and learning science principles for improving genAI-based learning frameworks and tutoring systems; Mitigating “hallucinations” in large language models (LLMs) and improving factual validity for education; Improving mathematical and scientific reasoning capabilities of LLMs; Methods and metrics for evaluating GenAI content; AI-based methods to evaluate students, monitor their progress and personalize their education; Analyses, studies, and solutions for preserving academic integrity in the abundance of GenAI models and generated educational content; Benchmark datasets for genAI applications in education; Next generation infrastructure to support research on GenAI for education

Day 2. Responsible AI (RAI; e.g., Fairness, Accountability, Interpretability, and Transparency) for consequential decision-making in education (e.g. admissions, early warning systems, grading); Methodological contributions and impact of responsible AI in education, including and not restricted to generative modeling, predictive modeling, causal inference, reinforcement learning, and data collection; AI for better student outcomes: applications that use AI to enhance educational interventions under resource constraints and inequity; Privacy, security, and AI Regulation in education equity, pipelines, and representation; surveillance; platform governance; regulating large/foundation models in education settings; Social and cultural impacts of AI in education; historical perspectives and critical theory

Format of Workshop

We have a two-day workshop with distinct themes and events on each day. Day 1 will focus on innovations in AI for education specifically highlighting GenAI and a variety of different events including keynotes, invited presentations/posters/demos, a debate all with representation from research and allied communities, and finally, a global challenge on math reasoning. Day 2 will highlight topics on responsibility in AI for education with a keynote, a stellar lineup of invited speakers, a moderated discussion session, expert panels highlighting critical issues in responsible AI, spotlight talks, and a poster session to highlight accepted papers. Participants will be encouraged to think critically, ask questions, identify edge cases for demos, and come together to brainstorm solutions.

Call for Submissions

We welcome different kinds of submissions:

  • Short papers (2 pages + references). Demo papers, Work-in-progress papers. These submissions will be exhibited as posters or demonstrations.

  • Full papers (up to 6 pages + references). Novel research papers, Appraisal papers of existing methods and tools (e.g., lessons learned), Benchmark datasets highlighting the application of GenAI, Evaluatory papers that revisit the validity of domain assumptions

Full paper submissions must follow the PMLR style template. Update: Short paper submissions should follow the AAAI style template.

Accepted full papers will be invited to submit an extended version, addressing the remarks of the reviewers, to PMLR ( to be published as part of the Workshop Proceedings.

Important Dates

  • Submission opens: September 29, 2023
  • Submission due: November 27, 2023, by 23:59 PM Eastern Time
  • Final paper decision: December 11, 2023
  • Camera-ready: February 15, 2024
  • Workshop Dates: February 26-27, 2024
  • Travel Scholarship applications due: November 23, 2023
  • Travel scholarship announcements: December 15, 2023

Submission Process

All submissions must be made through the OpenReview portal for the workshop. Authors must have an OpenReview account in order to make submissions. Full paper submissions must follow the PMLR style template. Short paper submissions should follow the AAAI style template.

Submission Guidelines

Workshop submissions are anonymous and must conform to the instructions (detailed below) for double-blind review. The authors must remove all author and affiliation information from their submission for review and may replace it with other information, such as paper number and keywords. Submissions may consist of up to 6 pages of technical content plus additional pages solely for references; acknowledgments should be omitted from papers submitted for review. Only PDF files are required at the time of submission for review; authors will additionally need to submit paper source files if their paper is accepted for publication.

> Access the OpenReview Submission Portal

Submission Limit per Author

Each individual author is limited to no more than a combined limit of 5 submissions to the AI4ED-AAAI24 workshop (including papers in the Innovation and Responsible AI tracks) and authors may not be added to papers following submission (see below for policies about author changes).

Guidelines for Changes to Titles/Authors after Submissions

MODIFICATIONS TO SUBMISSIONS ARE ONLY ALLOWED UNTIL SUBMISSION DEADLINE (November 23, 2023). No exceptions will be granted. Please see the full policy on Paper Modification Guidelines.

Policy Concerning Multiple Submissions to Conferences or Journals

This workshop will not consider any paper that, at the time of submission, is under review or has already been published or accepted for publication in any archival venue such as a journal or a conference (workshops and preprint servers such as arXiv are acceptable). Authors are free to retract a submission from a venue with a concurrent review process (e.g., from NeurIPS-23) and submit the same work to the AI4ED-AAAI24 workshop as a full paper, provided that this retraction occurs before the AI4ED-AAAI-24 submission. Authors must confirm at the time of submission that the paper is not under review at another archival conference or journal. Once they have made a submission to the workshop, authors may not submit the same paper to another archival conference or journal until they receive an accept/reject decision from AI4ED-AAAI24 or they withdraw their submission from AI4ED-AAAI-24. In some cases, it may require a judgment call to determine whether two concurrent submissions constitute a violation of AAAI’s multiple submission policy. If a concern is raised about the similarity of two non-identical submissions, at least three people will inspect whatever information is available about both submissions. If they all agree that the simultaneous submission has excessive technical overlap, the paper will be summarily rejected and the organizers of the other conference will be informed about AAAI’s decision. As with all summary rejects, such decisions are final.

Citation and Comparison

Papers are expected to cite those refereed publications most relevant to their content, but authors are excused for not knowing about all non-refereed work (e.g, appearing on arXiv). Nevertheless, in cases where such prior work is widely known in the field, its existence may be considered by reviewers in assessing a submission’s novelty. Papers published less than two months before the regular paper submission deadline (November 23, 2023) are considered contemporaneous to all AAAI-24 submissions; authors are not obliged to address such papers (though, especially for the camera-ready versions of accepted papers, authors are encouraged to do so).

Reproducibility Guidelines

Authors must complete a reproducibility checklist at the time of paper submission, which outlines how to reproduce the results of the submission. These responses will become part of each paper submission and will be shared with reviewers. Information related to reproducing experimental results described in the submission may be included in the main paper or the Code and Data Appendix, as appropriate. Further technical details (proofs, descriptions of assumptions, algorithm pseudocode) may be included in the Technical Appendix. When appropriate, authors are encouraged to include detailed information about each reproducibility criterion as part of their Technical Appendix. Reviewers will be asked to assess the degree to which the results reported in a paper are reproducible, and this assessment will be weighed when making final decisions about each paper.

Ethics Policy

All AAAI authors and reviewers are required to honor the AAAI Publications Ethics and Malpractice Statement, as well as the AAAI Code of Professional Conduct. A paper may be rejected if an author is found to violate the AAAI Publications Ethics and Malpractice Statement or the AAAI Code of Professional Conduct. Demonstrations During paper submission, authors will be able to express interest in giving a public demo of the systems described in the paper. Based on these expressions of interest and reviews, papers will be selected to participate in a demonstration session, which will happen in addition to technical talks and posters.

Global Challenge on Math Problem Solving and Reasoning

We invite researchers and practitioners worldwide to investigate the opportunities of automatically solving math problems via LLM approaches. More details about this competition can be found at

Invited Speakers and Panelists

NYU Prof. Emeritus,

Geometric Intelligence - Founder

Assistant Professor of Computer Science, University of British Columbia

Director-Center for Technology Innovation, Brookings Institute

Hortenius I. Chenault Endowed Associate Professor & Director, Culturally Relevant Computer Lab, Morehouse College

Executive Director, Digital Promise

Associate Professor of Computer Science, Stanford University.

Professor in Responsible AI and the Scientific Director of WASP-HS (Humanities and Society), Umea University

Will Belzak

Senior Assessment Scientist, Duolingo

Professor of Computer Science,

University of British Columbia

Assistant Professor of Computing Science,

University of Alberta

Assistant Professor in Education Data Science,

Stanford Graduate School of Education

Principal Research Director in Foundational Psychometrics and Statistics Research Center,


Chief Scientist,

Cambium Assessment

Research Scientist,

Google Research

Manager NLP Research

National Board of Medical Examiners (NBME)

Assistant Professor of Learning Analytics and Educational Data Mining,

Columbia University

AJ Alvero

Assistant Professor of Sociology and Data Science,

University of Florida

Program Lead,


Technical Director,


Graduate Student,

Stanford University


Our 2-day workshop will focus on both AI Innovation (day 1) and Responsible AI (day 2). The detailed workshop schedule can be found at:

Travel Scholarship

We are pleased to announce travel scholarships to the AAAI 2024 conference and attendance at the AI in Education: Bridging Innovation and Responsibility workshop. These scholarships are intended to broaden participation in the conference and the workshop, with a focus on reaching underserved and underrepresented undergraduate and graduate students as well as postdocs in the machine learning and AI domain. Each award is valued at $2000 CAD and is intended to cover travel, accommodation, and registration fees. We look forward to your applications and hope to see you in Vancouver, Canada, in February 2024.

Application Deadline: 11/23/2023 Recipient announcement: 12/15/2023

Workshop Steering Committee

Director of Engineering

Google Learning Platform

Director of Research

OpenStax, Rice University

Principal Assessment Scientist,


Assistant Professor of Computer Science (2024),

Princeton University

Dean of Guangdong Institute of Smart Education,

Jinan University, Guangzhou, China

Staff AI Research Scientist, Duolingo

Adjunct Associate Professor, UC Davis

Research Scientist


PhD Candidate

UC Berkeley

Subcommittee Leads

Program Committee and Proceedings

Director of Research

Google Brain

Assistant Professor

University of Massachusetts at Amherst

Staff AI Research Scientist, Duolingo

Adjunct Associate Professor, UC Davis

Mathematical Reasoning Competition

Liang Xu

Staff Machine Learning Engineer

TAL Education Group, China

Jiong Zhao

Staff Machine Learning Engineer

TAL Education Group, China

Staff Machine Learning Engineer

TAL Education Group, China

Dean of Guangdong Institute of Smart Education,

Jinan University, Guangzhou, China

Director of Research

Google Brain

Director of Engineering

Google Learning Platform

Chief Data Scientist and Co-Founder


Machine Learning Research Engineer



Associate Professor, Computer Science

University of British Columbia, Canada

Travel Scholarship

Director of Engineering

Google Learning Platform

Chief Data Scientist and Co-Founder


Collaborating Organizations

Collaborating Organizations