First International Workshop on
Advancing AI Literacy with Learning Analytics
@LAK'26
April 27 - May 1, 2026
Bergen, Norway
April 27 - May 1, 2026
Bergen, Norway
We are excited to announce the First International Workshop on Advancing AI Literacy with Learning Analytics, to be held at LAK'26.
As artificial intelligence (AI) continues to reshape education, there is an urgent need to understand how learners engage with AI systems and how educators can effectively foster AI literacy. This workshop seeks to bridge AI literacy research with learning analytics (LA) methods to explore how AI literacy can be defined, measured, and cultivated through data-informed approaches. Participants will exchange ideas, present frameworks and assessment strategies, and collaborate in design sessions that link AI literacy competencies with LA evidence and methodologies. The workshop aims to seed new partnerships, shared resources, and actionable models for integrating AI literacy into educational practice.
Registration: To register for the workshop, please visit the registration website for the LAK conference and click on the register button.
Empirical Contributions:
Studies presenting data-driven analyses, methodological innovations, or case studies related to AI literacy. Topics may include how learners engage with AI systems, how AI literacy can be measured or cultivated, or how learning analytics can inform evidence-based interventions and assessment.
Conceptual Contributions:
Position or discussion papers that propose new frameworks, theoretical perspectives, or critical reflections on AI literacy. These may examine its competencies, ethical dimensions, or implications for pedagogy, policy, and human–AI collaboration in education.
Tools and Demonstrations:
Papers or demos showcasing interactive tools, dashboards, prototypes, or analytics platforms designed to assess, visualise, or support AI literacy. Submissions may include working systems, design frameworks, or open-source resources that bridge AI literacy research and practice.
The paper submission deadline is on 04 Dec 2025, 11:59PM AOE.
Defining and Conceptualising AI Literacy: Conceptual or framework-oriented work clarifying the dimensions, competencies, and boundaries of AI literacy across educational contexts.
Measuring AI Literacy in Practice: Empirical or analytical studies using learning traces, performance data, or multimodal evidence to capture and assess AI literacy development.
Pedagogical Interventions for AI Literacy
Design-based or experimental work investigating instructional strategies, curricula, and scaffolds that foster critical and ethical engagement with AI systems.
Developing Tools and Frameworks for AI Literacy Assessment
Demonstrations or system papers presenting dashboards, analytics tools, or interactive environments for evaluating or supporting AI literacy.
Ethical and Responsible AI Literacy: Conceptual and empirical work exploring how learners understand, evaluate, and practise the ethical and responsible use of AI, with attention to fairness, transparency, accountability, and learner agency.
Policy and Institutional Frameworks for AI Literacy Development: Analyses and proposals addressing how institutional strategies, policies, and data governance frameworks can foster ethical, scalable, and equitable AI literacy initiatives.
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
27/28 Apr 2026 AI-LIT@LAK26 Workshop Day
Opening Keynote and Overview (45 mins)
Lightning Talks and Showcase (60 mins)
Collaborative Design Sessions (90 mins)
Further details will be provided closer to the workshop date.
Yueqiao Jin (Monash University)
Yizhou Fan (Peking University)
Yuan Shen (Zhejiang University of Technology)
Lixiang Yan (Tsinghua University)
Mohammad Khalil (University of Bergen)
Thomas K. F. Chiu (The Chinese University of Hong Kong)
Davy Tsz Kit Ng (Education University of Hong Kong)
Mutlu Cukurova (University College London)
For workshop-related questions, please contact Yueqiao Jin at ariel.jin@monash.edu or Yuan Shen at nicoleshen@zjut.edu.cn.