{"id":102,"date":"2024-11-15T11:20:04","date_gmt":"2024-11-15T11:20:04","guid":{"rendered":"https:\/\/educationaldatamining.org\/edm2025\/?page_id=102"},"modified":"2025-02-09T14:54:47","modified_gmt":"2025-02-09T14:54:47","slug":"call-for-papers","status":"publish","type":"page","link":"https:\/\/educationaldatamining.org\/edm2025\/call-for-papers\/","title":{"rendered":"Call For Papers"},"content":{"rendered":"<style>.kadence-column102_2fe6fa-de > .kt-inside-inner-col,.kadence-column102_2fe6fa-de > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column102_2fe6fa-de > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column102_2fe6fa-de > .kt-inside-inner-col{flex-direction:column;}.kadence-column102_2fe6fa-de > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column102_2fe6fa-de > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column102_2fe6fa-de{position:relative;}@media all and (max-width: 1024px){.kadence-column102_2fe6fa-de > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column102_2fe6fa-de > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column102_2fe6fa-de\"><div class=\"kt-inside-inner-col\">\n<style>.kadence-column102_57cbee-fa > .kt-inside-inner-col,.kadence-column102_57cbee-fa > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column102_57cbee-fa > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column102_57cbee-fa > .kt-inside-inner-col{flex-direction:column;}.kadence-column102_57cbee-fa > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column102_57cbee-fa > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column102_57cbee-fa{position:relative;}@media all and (max-width: 1024px){.kadence-column102_57cbee-fa > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column102_57cbee-fa > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column102_57cbee-fa\"><div class=\"kt-inside-inner-col\">\n\n<p><strong>Theme:<br>New Goals, New Measurements, New Incentives to Learn:<\/strong><br>In a world where AI can excel and outperform humans in many cognitive tasks, educational<br>systems need to reconsider their goals from the ground up. As AI is expected to reshape the<br>labor market, the social mechanisms that have shaped students\u2019 incentives to learn may<br>diminish or, at the very least, change. This presents an opportunity, and perhaps even a<br>necessity, for communities like EDM to help learners of all ages find their own voices and take<br>greater responsibility for their learning journey. Reshaping goals and priorities would also<br>require developing new ways to measure learning gains and processes to include more<br>complex constructs, like critical thinking, creativity, and ability to evaluate and incorporate new<br>information. The educational data mining community, with its expertise in both AI and education,<br>and its commitment to harnessing AI for the benefit of future generations, is in an ideal position<br>to lead the way in this brave new world<\/p>\n\n<\/div><\/div>\n\n<\/div><\/div>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-102_cfc50c-33 .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-102_cfc50c-33 .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-102_cfc50c-33\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\" \/><\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-column kadence-column102_4ce036-1c\"><div class=\"kt-inside-inner-col\">\n<p><strong>Topics of Interests<\/strong>:<br>Topics of interest to the conference include but are not limited to:<\/p>\n<ul>\n<li>Developing new techniques for mining educational data<\/li>\n<li>Bridging EDM research and learning sciences\n<ul>\n<li>Informing data mining research with educational and\/or motivational theories<\/li>\n<li>Actionable advice rooted in educational data mining research, experiments, and outcomes<\/li>\n<li>Evaluating the efficacy of curriculum and interventions<\/li>\n<\/ul>\n<\/li>\n<li>Domain Knowledge Modeling\n<ul>\n<li> Deriving representations of domain knowledge from data<\/li>\n<li> Algorithms for discovering relationships, associations, and prerequisite structures between learning resources<\/li>\n<li> Algorithms to improve existing domain models<\/li>\n<li> Human-in-the-loop methods to collect domain knowledge models, including crowd-sourcing and expert tagging<\/li>\n<\/ul>\n<\/li>\n<li>Educational Recommenders, Instructional Sequencing, and Personalized Learning\n<ul>\n<li>Learning resource recommendation algorithms, remedial recommendations, and learner<\/li>\n<li>choice in selecting the next activity<\/li>\n<li>Goal-oriented instructional sequencing<\/li>\n<li>Personalized course recommendations<\/li>\n<li>Peer recommendation for collaborative learning<\/li>\n<li>Methodologies for evaluating educational recommender systems and sequencing algorithms<\/li>\n<\/ul>\n<\/li>\n<li>Equity, Privacy, Transparency, and Fairness\n<ul>\n<li>Ethical considerations in EDM<\/li>\n<li>Legal and social policies to govern EDM<\/li>\n<li>Developing privacy-protecting EDM algorithms and detecting learner privacy violations in<\/li>\n<li>existing methods<\/li>\n<li>Developing and applying fairer learning algorithms, and detecting and correcting instances of algorithmic unfairness in existing methods<\/li>\n<\/ul>\n<\/li>\n<li>Human Factors, Transparency, and Explainability\n<ul>\n<li>Developing, improving, and evaluating explainable schemes for EDM systems<\/li>\n<li>Human factors that shape educational users\u2019 acceptance of EDM-based<\/li>\n<li>recommendations<\/li>\n<li>Educational users\u2019 trust and attitudes towards EDM technologies<\/li>\n<\/ul>\n<\/li>\n<li>Learner Cognitive and Behavior Modeling and its association with performance\n<ul>\n<li>Modeling and detecting students\u2019 affective and cognitive states (e.g., engagement, confusion) with multimodal data<\/li>\n<li>Temporal patterns in student behavior including gaming the system, procrastination, and<\/li>\n<li>sequence modeling<\/li>\n<li>Data mining to understand how learners interact with various pedagogical environments such as educational games and exploratory learning environments<\/li>\n<\/ul>\n<\/li>\n<li>Learner Knowledge and Performance Modeling\n<ul>\n<li>Automatically assessing student knowledge<\/li>\n<li>Learner knowledge gain and forgetting models in domains with complex concept structures<\/li>\n<li>Modeling real-world problem-solving in open-ended domains<\/li>\n<li>Causal inference of students\u2019 learning<\/li>\n<li>Predicting students\u2019 future performance<\/li>\n<li>Detecting cheating and academic dishonesty<\/li>\n<\/ul>\n<\/li>\n<li>Comparing Human and Artificial Intelligence\n<ul>\n<li>Analyzing generative AI\u2019s capabilities to perform complex learning tasks<\/li>\n<li>Developing methods to identify the use of generative AI in learning environments (e.g., for cheating)<\/li>\n<\/ul>\n<\/li>\n<li>Learning Analytics\n<ul>\n<li>Institutional analytics<\/li>\n<li>Learner profiling<\/li>\n<li>Multimodal analytics<\/li>\n<\/ul>\n<\/li>\n<li>Social and Collaborative Learning\n<ul>\n<li>Modeling student and group verbal and non-verbal interactions for collaborative and\/or competitive problem-solving<\/li>\n<li>Social network analysis of student and teacher interactions<\/li>\n<li>Data mining to understand how learners interact in formal and informal educational contexts<\/li>\n<li>Peer-assessment modeling<\/li>\n<li>Social learner modeling<\/li>\n<\/ul>\n<\/li>\n<li>Reproducibility\n<ul>\n<li>Replicating previous studies with larger sample sizes, in different domains, and\/or in more diverse contexts<\/li>\n<li>Facilitating accessible benchmarking systems and publishing educational datasets that are useful for the community<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/div><\/div>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-102_7df28e-0f .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-102_7df28e-0f .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-102_7df28e-0f\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\" \/><\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-column kadence-column102_4ed555-65\"><div class=\"kt-inside-inner-col\">\n<p><strong>Submission Types:<\/strong><br>For all tracks, the acknowledgements and references sections at the end of the paper do not<br>count towards the listed page limits. Note that long papers with borderline scores will not be<br>accepted as short papers. It is the authors\u2019 responsibility to consider the best fit for their<br>submission in terms of length.<\/p>\n<ul>\n<li>Full Papers \u2014 10 pages. Should describe original, substantive, mature, and unpublished<br>work.<\/li>\n<li>Short Papers \u2014 6 pages. Should describe original, unpublished work. This includes early<br>stage, less developed works in progress.<\/li>\n<li>JEDM Journal Track Papers \u2014 Papers submitted to the Journal of Educational Data Mining<br>track in the section \u201cEDM 2025 Journal Track\u201d (and accepted before May 31, 2025) will be<br>published in JEDM and presented during the JEDM track of the conference.<\/li>\n<li>Industry Papers \u2014 6 pages. Should describe innovative uses of EDM techniques in a<br>commercial setting.<\/li>\n<li>Doctoral Consortium \u2014 2-4 pages. Should describe the graduate\/postgraduate student\u2019s<br>research topic, proposed contributions, and results so far. See below for details.<\/li>\n<li>Posters\/Demos \u2014 2-4 pages. Posters should describe original unpublished work in progress<br>or last-minute results. Demos should describe EDM tools and systems, or educational<br>systems that use EDM techniques.<\/li>\n<li>Workshop proposals \u2014 2-4 pages. Should describe the organizers\u2019 plan both to conduct the<br>workshop (e.g., format, rough schedule, proposed list of speakers) and to stimulate growth in<br>the workshop\u2019s area of focus.<\/li>\n<li>Tutorial proposals \u2014 2-4 pages. Should motivate and describe succinctly the field or tool that will be presented, as well as a plan for attendees to learn it in a hands-on way.<\/li>\n<\/ul>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-102_82c650-12\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\" \/><\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-column kadence-column102_8644d0-b4\"><div class=\"kt-inside-inner-col\">\n<p><strong>Submission<\/strong><\/p>\n<ul>\n<li>All accepted papers will be published in the proceedings of the conference, except for the Journal track as stated above. Workshop papers will be published based on the decision and under the responsibility of the workshop organizers.<\/li>\n<li>All paper submissions must be submitted for double-blind reviewing.<\/li>\n<li>All papers must not have been submitted for publication at other venues.<\/li>\n<li>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).<\/li>\n<li>All papers &#8211; except the papers submitted to the JEDM Journal Track, see below &#8211; should be formatted according to the EDM template:\n<ul>\n<li>Word: <br><a href=\"https:\/\/educationaldatamining.org\/wp-content\/uploads\/2024\/edm_word_template2024.docx\">https:\/\/educationaldatamining.org\/wp-content\/uploads\/2024\/edm_word_template2024.docx<\/a><\/li>\n<li>LaTex:<br><a href=\"https:\/\/educationaldatamining.org\/wp-content\/uploads\/2024\/EDM-template2024.zip\">https:\/\/educationaldatamining.org\/wp-content\/uploads\/2024\/EDM-template2024.zip<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Papers not adhering to the provided templates, not respecting the page limits associated to the respective track, making unauthorized changes (e.g., decreasing font sizes, altering the position of captions in figures and tables, changing margins of columns or between sections, or allowing text, figures and\/or tables to extend beyond the column margins), or failing to comply with accessibility guidelines (e.g., not providing alt text for figures) may be rejected without review.<\/li>\n<li>Accepted papers will be subject to the EDM publication agreement, available at <a href=\"https:\/\/educationaldatamining.org\/EDM_ORG\/wp-content\/uploads\/2022\/02\/IEDMS-publishing-agreement.docx\">https:\/\/educationaldatamining.org\/EDM_ORG\/wp-content\/uploads\/2022\/02\/IEDMS-publishing-agreement.docx<\/a>, which is based on Creative Commons 4.0. DOIs will be assigned to all the accepted papers via Zenodo, and an ISBN will be included in the proceedings. The papers will also be submitted for indexing consideration by DBLP, Google Scholar, and Scopus.<\/li>\n<\/ul>\n<p>Papers can be submitted through the Easychair platform: <a href=\"https:\/\/easychair.org\/conferences\/?conf=edm2025\">https:\/\/easychair.org\/conferences\/?conf=edm2025<\/a><\/p>\n<\/div><\/div>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-102_be91f2-2d .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-102_be91f2-2d .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-102_be91f2-2d\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\" \/><\/div><\/div>\n\n\n<style>.kadence-column102_4660ed-02 > .kt-inside-inner-col,.kadence-column102_4660ed-02 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column102_4660ed-02 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column102_4660ed-02 > .kt-inside-inner-col{flex-direction:column;}.kadence-column102_4660ed-02 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column102_4660ed-02 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column102_4660ed-02{position:relative;}@media all and (max-width: 1024px){.kadence-column102_4660ed-02 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column102_4660ed-02 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column102_4660ed-02\"><div class=\"kt-inside-inner-col\">\n\n<p><strong>JEDM Journal Track Papers<\/strong><br>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 \u201cEDM 2025 Journal Track\u201d in the corresponding Section box.<\/p>\n\n<\/div><\/div>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-102_2b3de4-4e .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-102_2b3de4-4e .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-102_2b3de4-4e\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\" \/><\/div><\/div>\n\n\n<style>.kadence-column102_ec099b-60 > .kt-inside-inner-col,.kadence-column102_ec099b-60 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column102_ec099b-60 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column102_ec099b-60 > .kt-inside-inner-col{flex-direction:column;}.kadence-column102_ec099b-60 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column102_ec099b-60 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column102_ec099b-60{position:relative;}@media all and (max-width: 1024px){.kadence-column102_ec099b-60 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column102_ec099b-60 > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column102_ec099b-60\"><div class=\"kt-inside-inner-col\">\n\n<p><strong>Important Dates<\/strong><br>All dates refer to 23:59 (11:59 pm) <a href=\"https:\/\/www.timeanddate.com\/time\/zones\/aoe\">anywhere on Earth<\/a>. All deadlines are firm. No extension will<br>be granted.<br><\/p>\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td>JEDM track papers [three cut-off dates]<br>cut-off deadline 1<\/td><td>October 13, 2024<\/td><\/tr><tr><td>cut-off deadline 2<\/td><td>December 2, 2024<\/td><\/tr><tr><td>cut-off deadline 3<\/td><td>January 26, 2025<\/td><\/tr><tr><td>Abstracts for full and short papers<\/td><td>February 13, 2025<\/td><\/tr><tr><td>Full papers and short papers<\/td><td>February 20, 2025<\/td><\/tr><tr><td>Industry papers<\/td><td>February 20, 2025<\/td><\/tr><tr><td>Workshop and Tutorial proposals<\/td><td>March 1st, 2025<\/td><\/tr><tr><td>Doctoral consortium papers<\/td><td>March 11, 2025<\/td><\/tr><tr><td>Posters and demos<\/td><td>March 18, 2025<\/td><\/tr><tr><td>Acceptance notifications for workshop and tutorial submissions<\/td><td>March 22, 2025<\/td><\/tr><tr><td>Acceptance notifications for full, short, and industry papers<\/td><td>April 10, 2025<\/td><\/tr><tr><td>Acceptance notifications for posters, demos, and doctoral<br>consortium papers<\/td><td>April 25, 2025<\/td><\/tr><tr><td>Application deadline for student volunteers<\/td><td>April 20, 2025<\/td><\/tr><tr><td>Revisions due for submissions with conditional accept decisions<\/td><td>April 30, 2025<\/td><\/tr><tr><td>Camera-ready copy due<\/td><td>May 10, 2025<\/td><\/tr><tr><td>Conference Workshop Day<\/td><td>July 20, 2025<\/td><\/tr><tr><td>EDM<\/td><td>July 21-23, 2025<\/td><\/tr><\/tbody><\/table><\/figure>\n\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Theme:New Goals, New Measurements, New Incentives to Learn:In a world where AI can excel and outperform humans in many cognitive tasks, educationalsystems need to reconsider their goals from the ground up. As AI is expected to reshape thelabor market, the social mechanisms that have shaped students\u2019 incentives to learn maydiminish or, at the very least, [&hellip;]<\/p>\n","protected":false},"author":26,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"categories":[],"tags":[],"class_list":["post-102","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/pages\/102","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/users\/26"}],"replies":[{"embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/comments?post=102"}],"version-history":[{"count":13,"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/pages\/102\/revisions"}],"predecessor-version":[{"id":355,"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/pages\/102\/revisions\/355"}],"wp:attachment":[{"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/media?parent=102"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/categories?post=102"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2025\/wp-json\/wp\/v2\/tags?post=102"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}