This (half-day) workshop emphasizes the role of adaptive lifelong learning in the dynamic landscape of Artificial Intelligence in Education (AIED). The pervasive influence of digitization mandates continuous learning, responding to the challenges of automation and skill gaps. Learners and trainees play a pivotal role in the frontline of implementing AI in lifelong learning education. They grapple with significant demands, confronting information overload and the necessity to exhibit a high degree of flexibility in order to effectively adapt to the rapid changes and continuous evolution of new AI tools. By highlighting the virtues of adaptive lifelong learning, the workshop examines the impact of AI on a diverse spectrum of learners. Adaptive AI tools emerge as a source of support for bridging learning gaps, particularly in the post-pandemic landscape, offering essential support to learners through streamlined automation. Furthermore, the workshop emphasizes the critical necessity for adaptation in the evolving AIED domain, moving beyond its roots in computer science to encompass a more expansive educational perspective. With a specific focus on multi-criteria adaptive lifelong 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 AI tools that significantly enhance lifelong learning.

The aim of this workshop is to unite a community of AIED researchers interested in various aspects of lifelong learning, particularly in adaptation and personalization in lifelong learning. We invite contributions covering all topics related to adaptive lifelong learning, 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

We consider two types of submissions:

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

𝗙𝗼𝗿 𝗺𝗼𝗿𝗲 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻, 𝗽𝗹𝗲𝗮𝘀𝗲 𝘃𝗶𝘀𝗶𝘁 𝗼𝘂𝗿 𝘄𝗲𝗯𝘀𝗶𝘁𝗲:
https://itec.kuleuven-kulak.be/workshops-all24/