RKDE 2023 : CFP - The 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education (RKDE 2023)

RKDE 2023 - Call for Papers
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1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education
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to be held as part of the ECML PKDD 2023

Workshop: September 18, 2023 - Torino, Italy (with support for remote attendance)
Website: http://rkde2023.isti.cnr.it/


CONTEXT & OBJECTIVES
By offering a large number of highly diverse resources, learning platforms have been attracting lots of participants, and the interactions with these systems have generated a vast amount of learning-related data. Their collection, processing and analysis have promoted a significant growth of machine learning and knowledge discovery approaches and have opened up new opportunities for supporting and assessing educational experiences in a data-driven fashion. Being able to understand students' behavior and devise models able to provide data-driven decisions pertaining to the learning domain is a primary property of learning platforms, aiming at maximizing learning outcomes.

However, the use of knowledge discovery in education also raises a range of ethical challenges including transparency, reliability, fairness, and inclusiveness. The purpose of RKDE, Responsible Knowledge Discovery in Education, is to encourage principled research that will lead to the advancement of explainable, transparent, ethical and fair data mining and machine learning in the context of educational data. RKDE is an event organized into two moments: a tutorial to introduce the audience to the topic, and a workshop to discuss recent advances in the research field. The tutorial will provide a broad overview of the state of the art on the major applications for responsible approaches and their relationship with the educational context. Moreover, it will present hands-on case studies that practically shows how knowledge discovery tasks can be responsibly addressed in education. The workshop will seek top-quality submissions addressing uncovered important issues related to ethical, fair, explainable and transparent data mining and machine learning in education. Papers should present research results in any of the topics of interest for the workshop as well as application experiences, tools and promising preliminary ideas. RKDE asks for contributions from researchers, academia and industries, working on topics addressing these challenges primarily from a technical point of view, but also from a legal, ethical or sociological perspective.

Topics of interest include, but are not limited to:

TOPICS
* Dataset Collection and Preparation:
- New tools and systems for capturing educational data;
- Modeling representations of learners from data;
- Building representations of domain knowledge from data;
- Integrating data from multiple (and diverse) data sources;
- Creating datasets that allow to explore ethical dimensions;
- Designing collection protocols tailored to responsible knowledge discovery.

* Techniques and Models:
- Multimodal / semantic approaches for learners' behavior modeling or personalization;
- Adaptive question-answering and dialogue or automatically generating test questions;
- Personalized support tools and systems for communities of learners;
- Natural language processing applied on exam data in order to assign a grade to them.
- Temporal, behavioral, and physiological analysis of learners' behavior;
- Student engagement assessment via machine-learning techniques;
- Systems that detect and/or adapt the platform to emotional states of learners;
- Techniques to provide automated proctoring support during online examinations;
- Tools able to predict the learner's success or failure along the educational path;
- Developing fair and explainable models for different kinds of stakeholders;
- Developing privacy-protecting algorithms for learners' data processing.

* Evaluation Protocol and Metric Formulation:
- Performing auditing studies with respect to bias and fairness;
- Defining objective metrics for knowledge discovery in education;
- Formulating bias-aware protocols to evaluate existing algorithms;
- Evaluating existing mitigation strategies in unexplored domains;
- Comparative studies of existing evaluation protocols and strategies;
- Analyzing efficiency and scalability issues of debiasing methods;
- Replicating previous studies with different samples, domains and/or contexts.

* Case Study Exploration:
- Educational games;
- Learning management systems;
- Interactive simulations;
- Intelligent tutoring;
- Language assessment


SUBMISSION & PUBLICATION
All contributions will be reviewed by at least three members of the Program Committee. All papers should be anonymized (double-blind review process). We strongly encourage making code and data available anonymously (e.g., in an anonymous GitHub repository via Anonymous GitHub (https://anonymous.4open.science/). Moreover they should be written in English and be in LNCS format. Author instructions, style files, and the copyright form can be downloaded here:
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines


The following kinds of submissions will be considered:
- Full papers between 12 and 16 pages;
- Reproducibility papers between 12 and 16 pages;
- Short papers between 6 and 11 pages;
- Position papers between 4 and 5 pages.

It is planned that accepted papers will be published after the workshop by Springer in a volume of Lecture Notes in Computer Science (LNCS). Conditions for inclusion in the post-proceedings are that at least one of the co-authors has presented in person the paper at the workshop and the overall length of the paper should be no less than 4 pages. Pre-proceedings will be available online before the workshop. We also allow accepted papers to be presented without publication in the conference proceedings, if the authors choose to do so. Some of the full paper submissions may be accepted as short papers after review by the Program Committee. A special issue of a relevant international journal with extended versions of selected papers is under consideration.

The submission link is:
https://cmt3.research.microsoft.com/ECMLPKDDworkshop2023/Submission/Index

IMPORTANT DATES
Paper Submission deadline: June 20, 2023
Accept/Reject Notification: July 17, 2023
Camera-ready deadline: July 31, 2023
Workshop: September 18 or 22, 2023 (TBD)


PROGRAM CO-CHAIRS
* Mirko Marras, University of Cagliari, Italy
* Paola Mejia, EPFL, Switzerland
* Agathe Merceron, Berliner Hochschule für Technik, Germany
* Anna Monreale, University of Pisa, Italy
* Daniela Rotelli, University of Pisa, Italy


CONTACT
All inquiries should be sent to [email protected]