L@S | AIED | EDM
June 27 – July 28 | Seoul, Republic of Korea
Background & Motivation
Generative AI (GenAI) is reshaping Multimodal Learning Analytics (MMLA) — yet its use in collaborative learning remains largely overlooked. This half-day workshop invites researchers to explore how Large Language Models (LLMs) and multimodal architectures can act as semantic sensors: decoding meaning, motivation, and coherence in group learning settings. Rather than simply tracking behaviour, we aim to envision tools that foster meaningful human-GenAI interaction and support higher-order thinking skills without falling into cognitive over-reliance.
Learning Analytics has historically focused on observable signals — gaze, gesture, activity logs. Paired with speech-to-text models like Whisper, LLMs can now extract rich semantic representations from classroom dialogue in real time. Advances in multimodal LLMs further enable the analysis of nonverbal cues, such as facial expressions and physical interactions. Treating LLMs as semantic sensors opens one of the most exciting frontiers of MMLA: understanding meaning in collaborative learning.Learning Analytics has historically focused on observable signals — gaze, gesture, activity logs. Paired with speech-to-text models like Whisper, LLMs can now extract rich semantic representations from classroom dialogue in real time. Advances in multimodal LLMs further enable the analysis of nonverbal cues, such as facial expressions and physical interactions. Treating LLMs as semantic sensors opens one of the most exciting frontiers of MMLA: understanding meaning in collaborative learning.
The CROSSMMLA series has advanced MMLA research across LAK, ICLS, and AIED for over a decade. This edition focuses the community on harnessing GenAI to advance the semantic frontier.
Participation & Format
This half-day symposium brings together researchers, developers, and practitioners advancing the semantic frontiers with Generative AI.
Expected Outcomes & Community Relevance
The workshop will produce and disseminate:
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Collaborative Research Agenda — Priorities and open challenges for GenAI as semantic sensors in collaborative learning
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Special Issue Proposal — A call for papers in the Behaviour & Information Technology (planned 2027)
These outputs aim to strengthen community partnerships and support long-term scientific impact.
Organizers
Daniel Spikol — University of Copenhagen
Andy Nguyen — University of Oulu
Olga Viberg — KTH Royal Institute of Technology
Namrata Srivastava — Vanderbilt University
Roberto Martinez-Maldonado — Monash University
Qi Zhou — University College London
Kester Wong — University College London
Richard Lee Davis — KTH Royal Institute of Technology
Sa’ar Karp Gershon — IT University of Copenhagen
Marcelo Worsley — Northwestern University