[CogSci] AIED2023 Call for Late-Breaking Results

[Andrew McGregor Olney (aolney)]

AIED2023 Call for Late-Breaking Results

We are pleased to invite you to contribute to the program of AIED2023 
by submitting your late breaking results. The late-breaking results 
track offers an opportunity for presenting compelling, preliminary 
results and innovative work in progress. The goal is to give new, but 
not necessarily mature work a chance to be seen by other researchers and 
practitioners and to be discussed at the conference. Accepted 
submissions will be presented during the conference as posters.

The 24th international conference on Artificial Intelligence in 
Education (AIED) will take place between 3-7 July, 2023 in Tokyo, Japan 
and virtually. Its theme will be: AI in Education for Sustainable 
Society<https://www.aied2023.org/theme.html>

The conference will be the latest of a longstanding series of 
international conferences, known for high quality and innovative 
research on intelligent systems and cognitive science approaches for 
educational computing applications. To celebrate the 30th anniversary of 
the AIED Society, we invite papers exploring how researchers envision 
the way AIED can shape the future of education in the next 30 years. 
AIED 2023 solicits empirical and theoretical papers particularly (but 
not exclusively) in the following lines of research and application:

   *   AI-assisted and Interactive Technologies in an Educational Context;

   *   Modelling and Representation;

   *   Models of Teaching and Learning;

   *   Learning Contexts and Informal Learning;

   *   Evaluation;

   *   Innovative Applications;

   *   Equity and Inclusion in Education;

   *   Ethics and AI in Education;

   *   Explore Design, Use, and Evaluation of Human-AI Hybrid Systems 
for Learning; and

   *   Online Learning Spaces.

Please see the main call for details about each of these topics

<https://www.aied2023.org/cfp.html>

DIVERSITY, EQUITY, AND INCLUSION

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 2023, we 
incentivize authors to carefully consider diversity, equity, and 
inclusion when reporting on your work. Please see the submission 
instructions for specific considerations.


SUBMISSION INSTRUCTIONS

All submissions must be in Springer format. Papers that do not use the 
required format may be rejected without review. Authors should consult 
Springer’s<https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines> 
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<https://goo.gl/hbsa4D> in 
their papers. Submissions are handled via 
EasyChair<https://easychair.org/conferences/?conf=aied23>:

https://easychair.org/conferences/?conf=aied23

Accepted AIED 2023 papers for the late-breaking results track will be 
published by Springer Lecture Notes in Artificial Intelligence (LNAI), a 
subseries of Lectures Notes in Computer Science (LNCS).

Maximum paper length is as follows:

   *   Late-breaking results papers (4 pages including references; will 
be presented as a poster)



Following the successful presentation format in AIED 2022, giving 
opportunities for synchronous, remote presentations, during AIED 2023 we 
will allow synchronous participation for researchers who cannot attend 
in person. Each accepted paper will be expected to have at least one 
author registered to attend in-person who will present the paper at the 
conference.

All submissions will be reviewed by the program committee to meet 
rigorous academic standards of publication. The review process will be 
double-masked, meaning that both the authors and reviewers will remain 
anonymous. To this end, authors should: (a) eliminate all information 
that could lead to their identification (names, contact information, 
affiliations, patents, names of approaches, frameworks, projects and/or 
systems); (b) cite own prior work (if needed) in the third person; and 
(c) eliminate acknowledgments and references to funding sources. Papers 
will be reviewed for relevance, novelty, technical soundness, 
significance and clarity of presentation. It is important to note that 
the work presented should not have been published previously or be under 
consideration in other conferences of journals. Any paper caught in 
double submission will be rejected without review.



IMPORTANT DATES

   *   Late-breaking results submission: March 6, 2023

   *   Notification of decisions: April 10, 2023

   *   Camera-ready version: May 1, 2023



AUTHOR GUIDELINES

When preparing your paper, please consider the following:

(1) 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.

(2) 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:

(1) 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.

(2) 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).

(3) 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.

(4) 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?




ORGANIZING COMMITTEE

General Chairs

   *   Noboru Matsuda, North Carolina State University, USA

   *   Vania Dimitrova, University of Leeds, UK

   *   Olga C. Santos, UNED, Spain



Program Co-chairs

   *   Ning Wang, University of Southern California, USA

   *   Genaro Rebolledo-Mendez, The University of British Columbia


Local Chair

   *   Maomi Ueno, University of Electro-Communications, Japan


Posters and Late-Breaking Results Co-chairs

   *   Carrie Demmans Epp, University of Alberta, Canada

   *   Marie-Luce Bourguet, Queen Mary University of London, UK

   *   Andrew M. Olney, University of Memphis, USA