The 25th International Conference on Artificial Intelligence in Education (AIED) will take place between 8-12 July, 2024 in Recife, Brazil. Its theme is: AI in Education for a World in Transition. 

The AIED Doctoral Consortium is an interactive event to support doctoral students working in domains relevant to the interdisciplinary research areas of AIED. In the Doctoral Consortium, the students will share and discuss their research ideas and plans with more experienced colleagues, i.e., mentors, who will provide feedback on various aspects of the student's work including the theoretical framing and the methodological approaches. Doctoral Consortium participants will also have the opportunity to informally introduce themselves to the larger AIED community. 

We invite all doctoral students for submissions. However, the candidates selected will be those who are at a stage in their research for which feedback from the AIED community will be of most value. That is, the students who have a clear topic and research approach, and have made some progress, but who are not so far along in their work that they can no longer benefit from feedback received during the conference. It is possible to participate in the Doctoral Consortium if the candidate is in a doctoral program, and also if the individual has graduated within the year. Paper submissions must be primarily authored by the students with advisors and collaborators listed as co-authors. The topics of interest are related to the main conference topics. 

Though the main objective of the Doctoral Consortium is to provide an opportunity for feedback on students’ current research, we also seek to continue to build interdisciplinary research ideas, theoretical frameworks, and methodological approaches because these intersections are critical to AIED as an area of scholarship. We recognize that a supportive and trans-disciplinary research community can only be possible with opportunities for healthy dialogic exchange between members of the AIED community. Therefore, it is of utmost importance that the Doctoral Consortium fosters such collaborative interactions among the participants of the conference in order to enhance the experience of all participants and build capacity in the field.

Submission due: February 6, 2024

Notification of acceptance to authors: March 25th, 2024

Camera-ready paper due: April 29th, 2024

Conference: July 8 - 12, 2024

Note: the submission deadlines are at 11:59 pm AoE (Anywhere on Earth) time. Please adhere to these deadlines as there will NOT be any extensions to the above dates for DC track submissions.

The AIED Society values diversity, equity, and inclusion (and related principles under this broad umbrella) as essential and fundamental values for the AIED community to uphold. Thus, in AIED 2024, we incentivize authors to carefully consider diversity, equity, and inclusion when reporting on your work. 

When preparing your paper, please consider the following: 

• Authors should write with care toward inclusive language. This includes understanding identify-first vs. person-first language, gender neutral language, appropriate demographic categories and terminology, and avoiding the conflation of distinct dimensions such as race and ethnicity, or sex and gender. 

• Authors are encouraged to consider how their theoretical frameworks and findings are related to diversity, equity, and inclusion. For example, authors may discuss how these issues influence key assumptions, hypotheses, and methods. Likewise, authors might address implications or appropriate interpretations of their findings with respect to diversity, inclusion and equity. 

Please consider the following criteria when reporting samples: 

• Authors should be clear and specific about the composition of human-sourced data. Who were the participants? What was the distribution of gender, race, ethnicity, or related variables? If corpus data or training data were sourced from humans, a similar description could be offered. 

• Skewed or non-representative samples would not necessarily trigger a "reject" decision, but authors should acknowledge the demographic imbalances and discuss the potential impact on data, results, or conclusions. A more compelling paper would describe barriers to inclusive and representative sampling and the steps taken to generate an inclusive and representative sample (this is basic science, but often overlooked for convenience). 

• Authors should demonstrate some awareness of how equity, inclusion, accessibility issues impact their data, methods, products, or findings. How are different demographic groups or communities differentially connected to the work? People who are developing educational technologies need to think about access and use, for example. Corpus analyses need to address the impact of skewed/exclusive datasets and potential outcomes (e.g., algorithmic bias). It is also important to use strategies to control or reduce bias against populations of any kind (e.g., benefit or bring prejudice to a particular gender, race, or people with different economic status) when collecting, using, or aggregating data. 

• Authors are encouraged to discuss/justify how demographic variables are included in the analyses. If they are not included or "covaried out" please justify. If they are included, what are the assumptions? Are there "categorical effects"? Are the effects of different demographic variables independent, interdependent, or intersectional? What valid conclusions can be drawn? What erroneous conclusions need to be avoided or tempered?

Accepted candidates will participate in 1-on-1 talks with senior researchers and other students during the conference in which they will present their work and receive feedback on their research. 

In addition, prior to the conference, each student with an accepted paper will be assigned a mentor with specialized background on the student’s research topic or methodological approach so that more detailed and specific feedback can be provided to each student. As part of the application, students will list names of potential mentors in the AIED community they want to meet, and we will do our best to connect each student with those individuals. 

The submission has two equally important parts: 

1. A 6-page paper to be published in the conference proceedings. Important: If you wish to also submit your paper, or a close version, to the main conference (full or short paper track) and it is accepted under one of those tracks, then you will instead be invited to provide a one-page abstract for the camera-ready copy of the Doctoral Consortium proceedings. That way your paper will not be published twice yet your participation in the DC will be recorded in the proceedings. However, it is crucial to emphasize that these abstracts will be included in the front matter and will not undergo indexing. 

2. A presentation letter with additional information about the student and the research carried out to date. 

The paper should follow the format template linked below and describe, in a logical and coherent manner, the aims and objectives of the proposed research by clearly illustrating the following: 

1. The problem(s) addressed and the fit with the state of the art, including any previous work the student has done. 

2. The theoretical framing and proposed solution(s), as well as the methodology adopted to achieve it. Include the progress made to date on the work. 

3. The expected contribution(s) and impact of the research to the AIED community being mindful of both the Learning Sciences and Computer Science. 

The presentation letter should include all of the following information: 

1. Paper Title 

2. Name of the student and supervisor(s) 

3. Student’s title and university affiliation 

4. Short description of the study where the research is carried out. 

5. A paragraph describing the student’s contribution to the work, the stage of the studies, with a brief description of the student’s background. 

6. The type of feedback sought by the student from the Doctoral Consortium. 

7. List of other contributions submitted to the AIED 2024 conference, including the list order of authors, and status of the submission. 

8. Three names of AIED researcher-mentors the student would like to meet and why. 

9. Just for U.S. citizens: U.S. Citizenship and/or Green Card Status for funding consideration by the NSF. 

10. Link to your research webpage and/or CV.

All submissions must be in Springer format and follow Springer policies on publication (including policies on the use of AI in the authoring process):  https://tinyurl.com/3rk3zj3v. 

Papers that do not use the required format may be rejected without review. Authors should consult Springer’s authors’ guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. 

Instructions

• The papers can be co-authored by the student and supervisor(s), but the student should be the first author. 

• Papers should be 6 pages long, including references using the format used for the conference, i.e. Springer’s authors’ guidelines should be followed and an appropriate template, either for LaTeX or for Word, should be used for the preparation of the papers. 

• The paper and the presentation letter should be bound in a single PDF and uploaded to EasyChair.

Submissions will be handled via EasyChair: https://easychair.org/conferences/?conf=aied2024

Each accepted paper within the Doctoral Consortium track must be accompanied by a unique author registration (i.e., one registration per paper), completed by the early registration date cut-off. Please note that presenters of papers accepted to the Doctoral Consortium track are expected to be on-site to give their presentations and interact with the audience, to have the paper included in the proceedings. An online streaming option will be set-up for remote observers. Scholarships are available for researchers who lack funding to present at the conference, see website for more information.

If you have any further questions, please, contact the DC Chairs: 

• Yu Lu , Beijing Normal University, China (luyu@bnu.edu.cn)

• Elaine Harada Teixeira de Oliveira, Universidade Federal do Amazonas, Brazil (elaine@icomp.ufam.edu.br) 

• Vanda Luengo, Sorbonne Université, France (vanda.luengo@lip6.fr)