ALL25

ALL25: 2nd International Workshop on Adaptive Lifelong Learning

Co-located with LAK 2025

March 3rd
Dublin, Ireland

This half-day interactive workshop emphasizes the role of adaptive lifelong learning in the dynamic landscape of learning analytics (LA). When learners, trainees, teachers and trainers are confronted with AI in an educational context, they often face challenges such as information overload or the necessity to exhibit high degrees of flexibility to adapt to the rapid changes and continuous evolution of learning tools. By highlighting the virtues of AI for adaptive learning, the workshop examines the impact of AI as a source of support for bridging learning gaps and differences, to streamline automation and so on. Furthermore, the workshop emphasizes the critical necessity for multidisciplinary expertise in the evolving LA domain, moving beyond its roots in computer science (technical knowledge) to encompass a broader educational perspective (didactical knowledge). With a specific focus on multi-criteria adaptive learning, the workshop advocates for collaboration among learners, educators, policymakers, researchers, and EdTech companies. The ultimate goal is to facilitate the development of relevant and evidence-based adaptive learning tools that significantly enhance and support lifelong learning.

Topics of Interest

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.

Types of submissions

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.

Important dates

  • Paper submission deadline: December 4th, December 16th, 2024

  • Author notification: December 20th, January 13th, 2024

  • Camera-ready version deadline: January 20th, 2025

Deadlines refer to 23:59 in the AoE (Anywhere on Earth) time zone.

Paper format

All submissions should be in English and are required to adhere to the the 1-column CEUR-ART style: Word template or Overleaf (LaTeX). Failure to comply with the formatting guidelines may result in rejection prior to review.

Submissions must be anonymous, as we adhere to the double-masked review process. Depending on the number of accepted papers, we will determine whether short papers should be presented through oral presentations or at a poster session. Submissions will be reviewed by the organizing committee.

Submission will be accepted through Easychair.

Publications

All accepted papers will be included in the workshop proceedings published on the workshop website and shall be submitted to CEUR-WS.org for online publication. Authors of selected papers will be invited to extend their submissions by up to 30% for potential inclusion in a special issue of a journal (name of the journal and special issue will be announced soon).

General introduction (9:00-9:10)

Part 1: Adaptive learning from learners’ perspective (9:10-10:30)

  • Papers (50 min):
    • Does Personalised Learning Influence Students’ Self-Evaluation of Learning in Digital Learning Environments?

      Presenting author: Stefanie Vanbecelaere

    • Integrating Expert Knowledge in Matrix Factorization

      Presenting author: Changsheng Chen

  • Group discussions (30 mins)

Break (10:30-11:00)

Part 2: Adaptive learning from educators’ perspective (11:00-12:20) 

  • Papers (50 min):
    • Feedback Focus: A Tool for Evaluating and Reflecting on Instructor to Student Feedback Communication

      Presenting author: Derek Maki

    • Artificial intelligence in education: teachers’ trust, self-efficacy, anxiety and task value

      Presenting author: Rani Van Schoors

  • Group discussions (30 mins)

Overall conclusion and wrap-up (12:20-12:30)

Organizing Committee

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

Proceedings of the First Workshop on Adaptive Lifelong Learning (ALL 2024)

co-located with the 25th International Conference on Artificial Intelligence in Education (AIED 2024)

For any questions regarding the workshop, please feel free to contact: alireza[dot]gharahighehi[at]kuleuven[dot]be

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