to be held at the 16th International Learning Analytics and Knowledge Conference (LAK'26)
April 27, 2026
In-person Event: Bergen, Norway
Welcome to the third annual workshop on Generative AI and Learning Analytics (GenAI-LA) to be held during the LAK'26 conference!
The aim of this workshop is to advance interdisciplinary dialogue and collaboration around the evolving dynamics of human-AI partnerships in education. Building on the foundations established in previous GenAI-LA workshops, this year’s event focuses on understanding, measuring, and designing productive forms of human-AI collaboration through the lens of learning analytics. By bringing together researchers, practitioners, and designers from learning sciences, educational technology, and artificial intelligence, the workshop seeks to explore how learning analytics can illuminate and optimise the processes, affordances, and challenges of human-AI collaboration. Participants will collectively identify emerging frameworks, empirical methods, and ethical considerations that can guide the responsible and equitable integration of GenAI in learning environments.
Registration: To register for the workshop, please visit the registration website for the LAK conference and click on the register button.
Empirical Contributions:
Submissions showcasing empirical studies, methodological innovations, or case studies that explore the dynamics of human-AI collaboration in learning contexts. This includes work examining interaction patterns, trust and agency, division of labour, or the use of learning analytics to capture and analyse collaborative processes between humans and GenAI systems.
Conceptual Contributions:
Discussion papers or position pieces that challenge assumptions, raise critical questions, or propose new frameworks for understanding human-AI collaboration in education. These contributions are intended to provoke reflection on emerging opportunities, ethical dilemmas, and design principles guiding the responsible and equitable integration of GenAI in learning environments.
The paper submission deadline is on 04 Dec 2025, 11:59PM AOE.
Accepted workshop papers will be published in the CEUR Workshop Proceedings (CEUR-WS.org). Please note that accepted workshop papers will not be published in the LAK'26 companion proceeding.
Analysing Human–AI Collaborative Processes: Empirical or analytical studies examining interaction patterns, division of labour, trust calibration, and co-construction of knowledge between humans and GenAI systems.
Learning Analytics for Human–AI Interaction: Innovative methodologies and analytical frameworks that capture, model, or visualise the dynamics of collaboration between learners, educators, and AI agents.
Designing for Productive Human–AI Partnerships: Research or design case studies exploring how GenAI tools can be designed, implemented, or evaluated to support equitable, transparent, and effective collaboration in learning environments.
Agency, Ethics, and Accountability in Human–AI Collaboration: Conceptual or critical work examining issues of agency, authorship, responsibility, and ethical design in educational interactions with GenAI.
Measuring Learning and Collaboration Outcomes in Human–AI Teams: Studies that connect learning analytics indicators to outcomes such as engagement, creativity, metacognition, or collaborative problem-solving.
Equity and Inclusion in Human–AI Collaboration: Analyses of how GenAI-supported collaboration affects different learner groups, addressing accessibility, bias, and participation.
Emergent Literacies for Human–AI Collaboration: Exploration of the new skills, literacies, and competencies learners and educators need to collaborate effectively and critically with GenAI tools.
23 Oct 2025 Open Call for Submissions
04 Dec 2025 Deadline for Workshop Papers
19 Dec 2025 Notification of Acceptance for Papers
30 Jan 2026 Camera-Ready Deadline for Papers
27 April 2026 3rd GenAI-LA Workshop at LAK'26
Opening Keynote (30 minutes)
Workshop Paper Presentations (60 minutes)
Collaborative Design Sessions (90 minutes)
In this session, participants will join facilitated groups to tackle real-world learning scenarios involving human-AI collaboration. Using the learning analytics cycle as a guide, each group will design a research study or intervention aimed at unpacking and optimising human-AI collaborative processes. Each design will be shared with the wider group, generating immediate feedback and possible new partnerships.
Lixiang Yan (Tsinghua University)
Yueqiao Jin (Monash University)
Andy Nguyen (University of Oulu)
Wanruo Shi (Tsinghua University)
Ryan S. Baker (University of Pennsylvania)
Mutlu Cukurova (University College London)
Dragan Gašević (Monash University)
Nancy Law (University of Hong Kong)
Yuheng Li (The Hong Kong Polytechnic University)
For workshop-related questions, please contact Lixiang Yan at lixiangyan@mail.tsinghua.edu.cn or Yuheng Li at yu-heng.li@polyu.edu.hk