Call for Papers

UPDATED 20th March 2026

Finnish Learning Analytics and Artificial Intelligence in Education Conference 2026

Focus & Scope
The Finnish Learning Analytics and Artificial Intelligence in Education conference (FLAIEC) explores the intersection of Learning Analytics (LA) and Artificial Intelligence (AI) to support teaching and learning across all educational contexts.

In FLAIEC, we are bringing together a global community of educators, researchers, policymakers, and developers to explore how AI and data-driven insights are transforming education and how smart systems can genuinely support learners and teachers across all environments. The topic is highly timely and generates both discussion and questions: How different learning theories can inform the design, analysis, and interpretation of learning and teaching processes involving LA and AI? What underlying assumptions about learning and agency are embedded in LA and AI educational practices, and how do these assumptions align with or challenge established learning theories? How are questions of trust, accountability, and responsibility conceptualized and enacted in LA- and AI-mediated educational practices?

Participants are encouraged to present their latest research, methodological advances, empirical findings, and theoretical insights, and discuss the broader role of educational science in shaping the future of LA and AI. We welcome junior and senior scholars, teachers, practitioners, and all interested stakeholders.

Call for Contributions
We invite empirical, theoretical, and review contributions on the role of LA and AI in education. Submissions may engage with (but are not limited to) the following themes:

  1. Pedagogy, Curriculum & Learning Design: LA- and AI-supported approaches to teaching and learning, including personalization, assessment and feedback, curriculum design, and AI literacy, as well as the use of learning data to inform and improve instructional decisions and learning experiences.
  2. LA and AI Technologies & Methodologies: Technical and methodological advances in LA and AI, such as NLP, multimodal learning analytics, adaptive systems, and gamified learning, alongside data integration, modeling, and evaluation approaches for understanding and supporting learning processes.
  3. Ethics, Policy & Governance: Ethical and regulatory dimensions of LA and AI, including data privacy, fairness, transparency, and accountability, as well as institutional practices, policy development, and teacher professional development for responsible use.
  4. AI-Augmented Learning Support: Digital assistants, virtual tutors, and AI agents informed by LA that scaffold learning, provide timely feedback, support self-regulation, and facilitate individual and collaborative learning processes.
  5. Generative AI and LA in Practice: Everyday uses of generative AI alongside LA by students and educators for writing, content creation, feedback, and instructional design, and how these practices reshape learning, assessment, and academic work.
  6. Human–AI–LA Interaction & Collaboration: Evolving relationships between humans, AI systems, and learning data, including trust, agency, interpretability of analytics, and the changing roles of teachers and learners in data-informed educational environments.
  7. Underlying Assumptions & Untapped Theories: Theoretical approaches to learning, LA and AI, critical societal insights and conceptualizations of LA and AI in education.

Different types of contributions

1. Journal Special Issue Papers 

A selection of submissions will be invited for potential publication in a special issue associated with the conference. Papers will undergo a rolling editorial board assessment to identify contributions of journal quality. Selected papers will then enter a formal peer-review process managed by the conference’s editorial board, in line with the standards of the hosting journal. We encourage authors to submit to this category; editors will provide feedback on papers that are not selected to help authors get the paper ready for the SI track.

2. Conference Abstract (Presentation Only)

Authors may submit an abstract (maximum 500 words) outlining their research, work in progress, or conceptual contribution. Accepted abstracts will be included in the conference program and presented, but will not be formally published.

3. Short Conference Papers (CEUR Proceedings)

Authors may submit short papers describing completed or ongoing research. Accepted papers will be peer-reviewed and published in the CEUR Workshop Proceedings, providing an accessible and citable record of the work presented at the conference.

LINK TO THE SUBMITTING SYSTEM WILL BE ADDED SOON.

AUTHOR GUIDELINES WILL BE UPDATED SOON.