Theme: Educational data mining for amplifying human potential

Educational Data Mining is a leading international forum for high-quality research that mines datasets to answer educational research questions, including exploring how people learn and how they teach. These data may originate from a variety of learning contexts, including learning and information management systems, interactive learning environments, intelligent tutoring systems, educational games, and data-rich learning activities. Educational data mining considers a wide variety of types of data, including but not limited to log files, student-produced artifacts, discourse, learning content and context, sensor data, and multi-resource and multimodal streams. The overarching goal of the Educational Data Mining research community is to support learners and teachers more effectively, by developing data-driven understandings of the learning and teaching processes in a wide variety of contexts and for diverse learners.

The 16th iteration of the conference, EDM 2023, will take place in the Indian Institute of Science Campus, Bengaluru, India, during July 11-14, 2023.

The theme of this year’s conference is “Educational data mining for amplifying human potential”. Not all students receive the education necessary to help them express their full potential be it due to a lack of resources or access to high quality teaching. The lack of high-quality educational material and teaching aids and methodologies and non-availability of objective feedback on how they can become even better teachers, deprive our teachers from achieving their full potential. The administrators and policy makers lack tools for making optimal decisions such as optimal class sizes and composition and course sequencing. These in turn handicap the nations, particularly the economically emergent ones, who recognize the centrality of education for their growth. Thus, EDM-2023 particularly welcomes papers focusing on concepts, principles, and techniques mined from educational data for enhancing the potential of all the stakeholders in the education system. Papers describing applications and case studies are especially welcome.
Topics of Interest

Topics of interest to the conference include but are not limited to:

Models and new techniques for mining educational data.
Closing the loop between EDM research and learning sciences
Informing data mining research with educational and/or motivational theories
Actionable advice rooted in educational data mining research, experiments, and outcomes
Domain Knowledge Modeling
Deriving representations of domain knowledge from data
Algorithms for discovering relationships, associations, and prerequisite structures between learning resources with different formats, including programming practices, essays, and videos
Algorithms to improve existing domain models
Novel methods to collect domain knowledge models, including crowd-sourcing and expert tagging
Educational Recommenders, Instructional Sequencing, and Personalized Learning
Learning resource recommendation algorithms, remedial recommendations, and learner choice in selecting the next activity
Goal-oriented instructional sequencing
Personalized course recommendations
Peer recommendation for collaborative learning
Offline and online evaluation methods for educational recommender systems and sequencing algorithms
Learner Cognitive and Behavior Modeling and its association with performance
Modeling and detecting students’ affective and cognitive states (e.g., engagement, confusion) with multimodal data
Temporal patterns in student behavior including gaming the system, procrastination, and sequence modeling
Data mining to understand how learners interact with various pedagogical environments such as educational games and exploratory learning environments
Multimodal analytics
Learner Knowledge and Performance Modeling
Automatically assessing student knowledge
Learner knowledge gain and forgetting models in domains with complex concept structures
Modeling real-world problem-solving in open-ended domains
Causal inference of students’ learning
Predicting students’ future performance
Social and Collaborative Learning
Modeling student and group verbal and non-verbal interactions for collaborative and/or competitive problem-solving
Social network analysis of student and teacher interactions
Data mining to understand how learners interact in formal and informal educational contexts
Peer-assessment modeling
Social learner modeling
Reproducibility
Replicating previous studies with larger sample sizes, in different domains, and/or in more diverse contexts
Facilitating accessible benchmarking systems and publishing educational datasets that are useful for the community
EDM in life and the practical influence of EDM on learning and teaching
Equity, Privacy, Transparency, and Fairness
Ethical considerations in EDM
Legal and social policies to govern EDM
Developing privacy-protecting EDM algorithms and detecting learner privacy violations in existing methods
Developing and applying fairer learning algorithms, and detecting and correcting instances of algorithmic unfairness in existing methods
Developing, improving, and evaluating explainable EDM algorithms

Submission Types

For all tracks, the references section at the end of the paper does not count towards the listed page limits.

Full Papers — 10 pages. Should describe original, substantive, mature, and unpublished work.
Short Papers — 6 pages. Should describe original, unpublished work. This includes early stage, less developed works in progress.
JEDM Journal Track Papers — Papers submitted to the Journal of Educational Data Mining track (and accepted before 2023-05-31) will be published in the June issue of JEDM and presented during the JEDM track of the conference. Papers accepted later will be automatically considered for the next iteration of the conference.
Industry Papers — 6 pages. Should describe innovative use and deployment of EDM techniques in schools, formal and informal learning settings, ed-tech products, etc.
Posters — 2-4 pages. Should describe original unpublished work in progress or last-minute results.
Demos — 2-4 pages. Description of the proposed demonstration at the conference of the EDM tools and systems, or educational systems that use EDM techniques.
Doctoral Consortium — 2-4 pages. Should describe the graduate/postgraduate student’s research topic, proposed contributions, results so far, and aspects of the research on which advice is sought.
Workshop proposals — 2-4 pages. Should describe the organizers’ plan both to conduct the workshop (e.g., format, rough schedule, proposed list of speakers) and to stimulate growth in the workshop’s area of focus.
Tutorial proposals — 2-4 pages. Should motivate and describe succinctly the field or tool that will be presented, and a plan for attendees to learn it in a hands-on way.

All paper submissions must be submitted for double-blind reviewing. All papers must haven’t been submitted for publication at other venues.

All accepted papers will be published in the open-access proceedings of the conference, except for the Journal track as stated above. Papers submitted to workshops will be published separately in the workshop proceedings.

Links to existing source code are encouraged, however to keep the double-blind reviewing, we suggest using a service such as Anonymous GitHub (https://anonymous.4open.science).
Submission

All papers – except the papers submitted to the JEDM Journal Track, see below – should be formatted according to the EDM template:

Word: https://educationaldatamining.org/edm2020/wp-content/uploads/sites/4/2019/09/edm_word_template2020.doc
LaTeX: https://educationaldatamining.org/edm2020/wp-content/uploads/sites/4/2019/09/edm_submission2020.zip

Submission link will be made available soon.
Special Instructions
Workshop and Tutorial proposals

Workshop and Tutorial proposals should use the EDM proceedings template (LaTeX or Word) and include at least the following elements:

Title.
Length of workshop/tutorial: full or half-day.
Proposed format of the workshop/tutorial (e.g., approximate timeline) and type of activities (e.g., paper presentations, discussions, demos, etc.).
Description of the workshop/tutorial content and themes.
Names, short biographies, and contact information of workshop/tutorial chair(s). For tutorials, this biography must include detailed information about the qualifications of the proposer to conduct the tutorial on the proposed topic. For workshops, include a list of organizing/program committee members, who should be from multiple universities.

Submission link will be made available soon.
JEDM Journal Track Papers

JEDM track papers should be formatted according to the JEDM guidelines and should be submitted to the journal directly at: https://jedm.educationaldatamining.org/index.php/JEDM/about/submissions.

Select the option “EDM 2023 Journal Track” in the corresponding Section box when filling the form to submit your paper.
Important Dates

All dates refer to 23:59 (11:59 pm) anywhere on Earth. All dates refer to the year 2023. All deadlines are firm. No extension will be granted.

Please note: Compared to previous years, EDM 2023 will have an earlier submission deadline on Jan 20, 2023 (with Jan 13, 2023 as abstract submission deadline)
JEDM track papers Three cut-off dates:September 30, 2022 November 30, 2022January 30, 2023
Workshop and Tutorial proposals December 5, 2022
Acceptance notifications for workshops and tutorials January 9, 2023
Abstracts for full and short papers January 13, 2023
Full papers and short papers, Industry papers, Posters and demos, Doctoral consortium papers January 20, 2023
Acceptance notifications for full and short papers, posters, demos, and doctoral consortium papers April 10, 2023
Camera-ready copy due May 1, 2023
Due dates and acceptance notifications for workshop papers Set by workshop organizers

Looking forward to seeing you at EDM 2023 in Bangalore!