Submission Guidelines

We consider two types of submissions:

• Regular paper:  10-15 pages (including references)
• Short paper: 5-9 pages (including references)

The submission should be positioned within the current state of the field and articulate the contribution of the proposal within its specific application domain, even if preliminary results are presented. Detailed explanation of the methodology is expected, ensuring the replicability of experiments, and whenever feasible, a comparison with existing approaches in the literature should be provided. The short papers are primarily evaluated based on the novelty of their ideas and how well they position the innovation.

List of Topics

This workshop aims to unite a community of researchers interested in various aspects of lifelong learning, particularly in adaptation and personalization. We invite contributions covering all topics related to adaptive lifelong learning, from both technical and didactical perspectives, with a specific focus on, but not limited to, the following list:

• Tailoring lifelong learning to various factors, including knowledge, skills, motivation, engagement, and learning objectives
• Extending the range of adaptation criteria beyond mere relevance, incorporating factors such as fairness, diversity, bias, and pedagogical aspects
• Group-aware and context-aware adaptations in lifelong learning
• Lifelong learning adaptation involving multiple stakeholders, including learners, trainers, and EdTech companies
• Adaptive learning in Massive Open Online Courses (MOOCs)
• Quantifying learner’s engagement and dropout risk
• Adaptive or personalized nudging strategies within lifelong learning
• Multi-modal adaptive lifelong learning
• Adaptive educational games for enhancing lifelong learning
• Adaptive computer-assisted language learning
• Adaptive communication with learners (e.g. feedback, dashboard, etc)
• Chatbots for lifelong learning
• Adaptive simulations in work stations
• Explainable adaptations in lifelong learning
• Generating/composing adaptive learning trajectories

Please feel free to contact us to check whether your paper idea matches our call for papers.

Committees

Program Committee

• Judy Kay, Professor, Computer Science, University of Sydney
• Bita Akram, Assistant Professor, Computer Science, North Carolina State University
• Diego Zapata-Rivera, Distinguished Presidential Appointee, Educational Testing Service, Princeton NJ
• Anaïs Tack, Postdoctoral Researcher, Language Technology, KU Leuven and uclouvain
• Ifeoma Adaji, Assistant Professor, Computer Science, The University of British Columbia
• Chen Sun, Research Associate, School of Environment, Education and Development, The University of Manchester
• Yang Shi, Assistant Professor, Computer Science, Utah State University
• Wim van den Noortgate, Full Professor, Psychology and Educational Sciences, KU Leuven
• Sameh Metwaly, Postdoctoral Researcher, Psychology and Educational Sciences, Itec, imec research group
• Ishari Amarasinghe, Postdoctoral Researcher, Artificial Intelligence, NOLAI 
• Celine Vens, Professor, Machine learning and AI, KU Leuven, campus Kulak
• Felipe Kenji Nakano, Postdoctoral Researcher, Machine learning and AI, KU Leuven

Organizing committee

• Alireza Gharahighehi
• Rani Van Schoors
• Jeroen Ooge
• Paraskevi Topali

Venue

The workshop is co-located with LAK 2025 in Dublin, Ireland

Contact

All questions about submissions should be emailed to alireza[dot]gharahighehi[at]kuleuven[dot]be