The widespread integration of Artificial Intelligence (AI), especially generative AI, into learning and teaching has sparked a growing interest in Hybrid Intelligence—systems in which humans and AI collaborate to achieve joint cognitive and learning goals (Dellermann et al., 2019; Järvelä et al., 2025). This concept moves beyond automation and augmentation toward a synergistic co-performance model in which both human and machine intelligences adapt and improve over time through interaction (Nguyen, 2025). In the context of education, Hybrid Intelligence is gaining traction as a promising direction for enhancing teaching, learning, and educational decision-making (Cukurova, 2024; Giannakos et al., 2024). Recent developments in learning analytics have further amplified the potential of Hybrid Intelligence. Learning analytics not only enables the collection and interpretation of data from complex learning environments but also plays a critical role in facilitating adaptive support, reflection, and pedagogical decision-making (Cukurova, 2024; Jung & Wise, 2025). As learning environments become increasingly multimodal and AI-mediated, the need to reconceptualize analytics systems as collaborative, human-centered, and co-regulated with intelligent systems becomes urgent (Dang et al., 2025).

Following the success of the inaugural workshop, this second iteration continues to serve as a forum for advancing dialogue and fostering collaborations among researchers and practitioners interested in learning analytics for Hybrid Intelligence. The inaugural workshop brought together 39 participants and resulted in the publication of seven peer-reviewed workshop papers. Over the past year, notable advancements have been achieved, and the concept of Hybrid Intelligence, referring to the integration of human and artificial intelligence, has attracted growing interest across various disciplines, particularly within learning sciences, learning analytics, and human-computer interaction. The workshop will explore the mutual shaping of human-AI collaboration and learning, with a particular emphasis on how learning analytics can inform and enhance hybrid intelligence systems, and conversely, how hybrid intelligence can enrich the scope and impact of learning analytics. The workshop aims to advance the conceptual, methodological, and design foundations of Hybrid Intelligence by bringing together a transdisciplinary community of learning scientists, learning analytics researchers, software engineers, and AI experts. Participants will engage in critical discussions, share emerging work, and identify future directions for research and development at the intersection of human learning and intelligent systems. 

20 Oct 2025: Call for Submissions

4 Dec 2025: Submission Deadline for Workshop Papers

19 Dec 2025: Notifications of Acceptance

15 Jan 2026: Camera-Ready Deadline for Workshop Papers

April 2026: the 2nd Hybrid Intelligence: Human-AI Collaboration and Learning Workshop, taking place during the LAK'2026 conference!