Advancing AI Literacy with Learning Analytics 

CALL FOR WORKSHOP PAPERS

We invite researchers, educators, and practitioners to contribute to this workshop. Submissions should present original work that advances the understanding, measurement, or cultivation of AI literacy through empirical, conceptual, or tool-based approaches. Participants may submit either a Workshop Paper (4–10 pages) or an Extended Abstract (2–4 pages) using the designated template. We will welcome three types of contributions:

• 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.

All submissions will be peer-reviewed by the organising committee. Accepted papers will be published in the CEUR Workshop Proceedings (CEUR-WS.org). Please note: accepted papers will not appear in the LAK’26 Companion Proceedings.

Suggested topics

Submissions may address, but are not limited to, the following areas:

• 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.

Workshop Schedule (Half-day Interactive Session)

• 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.

CONTACT

For workshop-related questions, please contact Yueqiao Jin at ariel.jin@monash.edu or Yuan Shen at nicoleshen@zjut.edu.cn.