The 38th Annual AAAI Conference on Artificial Intelligence
February 20-27, 2024 | Vancouver, Canada
Important Dates for Authors
Note: all deadlines are “anywhere on earth” (UTC-12)
Abstract deadline: August 31, 2023 at 11:59 PM UTC-12 (anywhere on earth)
Paper deadline: September 10, 2023 at 11:59 PM UTC-12 (anywhere on earth)
Notification date: December 9, 2023
Camera Ready deadline: December 19, 2023
Symposium dates: February 24-25, 2024 (co-located with AAAI-24)
EAAI-24 Call for Participation
EAAI-24: The 14th Symposium on Educational Advances in Artificial Intelligence invites AI educators and researchers to share and discuss advances in AI education.
EAAI website: https://eaai-conf.github.io
Submission types
EAAI-24 has a main track and four special tracks. All submissions are subject to double-blind review. All accepted submissions are to be presented at the symposium.
Main Track
Chair: Fred Martin (UT San Antonio), Narges Norouzi (University of California Berkeley), Stephanie Rosenthal (Carnegie Mellon University)
The main track invites a broad range of papers on teaching AI and teaching with AI. Submissions may be framed as research papers or as experience reports. Potential topics include:
- The design of an AI curriculum, course, or module.
- The development or use of a tool or resource to teach AI.
- The impact of a pedagogical or mentoring technique on AI students.
Special Track: AI for Education
Chairs: Collin F. Lynch (North Carolina State University), Effat Farhana (Vanderbilt University)
Educational domains provide unique task areas and challenges for AI, and they provide unique opportunities for positive impacts. This special track invites research on advances in AI applied to educational tasks and domains including novel student models, intelligent learning environments, automated assistants, and instructional support.
Submissions should be framed as research publications consistent with the general call.
Special Track: Resources for Teaching AI in K-12
Chairs: Dave Touretzky (Carnegie Mellon), Christina Gardner-McCune (University of Florida)
This special track invites papers on the development and use of resources to support K-12 AI education. Examples include online demos, software tools, and structured activities. Submissions should follow the standard EAAI format for an academic paper and include the following: description of the resource; target age group; setup and resources needed; AI concepts addressed; expected learning outcomes; and (if possible) implementation results. Online demos and software tools should be accompanied by brief video walk-throughs.
Special Track: Mentored Undergraduate Research Challenge: AI for Accessibility in Communication
Chair: Rick Freedman (SIFT)
This special track invites papers addressing the AI for Accessibility in Communication Mentored Undergraduate Research Challenge (https://www.yetanotherfreedman.com/resources/challenge_ai4aic.html). The objective of this year’s challenge is to perform and publish research on the development or application of AI that makes sharing information more approachable and inclusive. The broader purpose of EAAI mentored undergraduate research challenges is to encourage undergraduate students to experience the full life-cycle of AI research through the guidance of a mentor familiar with the research life-cycle.
Submissions should be framed as research papers, with at least one undergraduate (including community college) student author and at least one mentor (faculty or Ph.D.-holding) author.
Special Track: Model AI Assignments
Chair: Todd Neller (Gettysburg College)
This special track invites assignments for AI classes. Good assignments take a lot of work to design. If an assignment you have developed may be useful to other AI educators, this track provides an opportunity to share it. Model AI Assignments are kept in a public online archive.
This track has special submission instructions (http://modelai.gettysburg.edu).
Review criteria
Submissions will be reviewed for:
- Relevance to the track
- Significance to the intended audience
- Engagement with prior work
- Novelty of contributions
- Technical soundness
- Clarity of presentation
- Evaluation of claims/results (as applicable)
- Engagement with questions of ethics/inclusivity (as applicable)
For empirical studies, we suggest that authors consider making use of one of the reporting standards in the SIGSOFT Empirical Standards document (https://acmsigsoft.github.io/EmpiricalStandards/docs). Submissions not making use of the reporting standards will not be penalized. Although we always aim for high standards in empirical research, specifically making use of the SIGSOFT Empirical Standards criteria is not in any way mandatory. Every paper is considered on its own merits; deviation from the guidelines may sometimes be desirable. Authors may indicate in their submission the category that they have chosen as most appropriate for their work and follow the respective checklist to ensure that their submission fulfills the required standard. The standards will also be suggested to reviewers as a basis for their decision.
Submission Instructions
All submissions (including supplementary materials) must be anonymous for double-blind review.
Instructions for paper submissions (all tracks except Model AI Assignments, which have their own format):
- Papers should be up to 7 pages long, plus up to 2 pages of references.
- Use the AAAI-24 Author Kit
- For supplementary material follow the AAAI-24 Supplementary Material Guide.
- Submit papers via EasyChair (https://easychair.org/conferences/?conf=eaai24).
EAAI-24 will not consider any paper that, at the time of submission, is under review for or has already been published or accepted for publication in a refereed journal or conference. Once submitted to EAAI-24, papers may not be submitted to another refereed journal or conference during the review period. These restrictions do not apply to unrefereed forums or workshops without archival proceedings.
Organization
Correspondence may be sent to EAAI at eaai24@aaai.org.
EAAI-24 chairs
Marion Neumann (Washington University in St. Louis, USA)
Stephanie Rosenthal (Carnegie Mellon University, Pittsburgh, USA)