ICCE 2026 Workshop · Half-day Mini-conference
📣 Call for Papers launched — submissions open until 11 August 2026.
Generative AI and multimodal educational data are reshaping how learning is supported, evaluated, and understood. Current AI-enhanced learning systems increasingly provide dashboards, feedback, recommendations, and automatically generated learning materials — but many still respond only after learners show difficulties or explicitly request help. More fundamentally, when AI can assist learners in searching, generating, analyzing, reflecting, receiving feedback, and adjusting strategies, we need to reconsider what "learning success" means in intelligent learning environments.
This workshop introduces Proactive Learning Success as an emerging paradigm for designing intelligent learning environments that diagnose learners' current states, model possible future learning needs, and provide timely, personalized, ethical, and pedagogically meaningful support (Zhao, Hwang, & Yin, 2027). It extends learning analytics, adaptive learning, and self-regulated learning by emphasizing forward-looking modelling, proactive intervention, human–AI collaboration, and evidence-based support for learners' cognitive, affective, behavioral, motivational, and social development.
Rather than treating learning success only as achievement, knowledge mastery, or final outcomes, the workshop views it as a dynamic and adaptive process involving engagement, motivation, strategy use, critical thinking, learner agency, deep understanding, and sustainable learning capacity.
We welcome theoretical, empirical, methodological, design-oriented, and practice-based submissions on topics including, but not limited to:
Proactive recommendation, scaffolding, prompting, feedback, and intervention systems; learner-state diagnosis and future-state modelling.
Multimodal evidence from behavioral, sensor, text, discourse, assessment, and classroom data; interpretation, validity, and explainability.
GenAI-based tutors, agents, copilots, and personalized material generation; human-AI collaboration in learning environments.
Learner agency, self-regulation, co-regulation, motivation, and engagement; critical thinking, creativity, and lifelong learning.
Teacher dashboards, human-in-the-loop orchestration, classroom implementation, pedagogical models, and learning design.
Privacy, fairness, accessibility, accountability, and responsible AI use; scaling up in authentic educational settings.
Submission Deadline
11 August 2026
23:59 GMT
Acceptance Notification
1 September 2026
Camera-Ready Due
15 September 2026
Workshop Day
30 Nov or 1 Dec 2026
Per ICCE 2026 schedule
The workshop follows a single-blind review process as ICCE conference: reviewers will know the authors' identities, but authors will not know the reviewers'. Anonymization is therefore not required.
Accepted papers will be presented at the workshop and published in the ICCE 2026 workshop proceedings with ISBN and will be indexed by Elsevier Bibliographic Database.
TBA
The workshop program will be announced after acceptance notifications.
Kyushu University, Japan
Kyushu University, Japan
Jilin University, China
National Chung Hsing University, Taiwan
National Taipei University of Education, Taiwan
Soochow University, Taiwan
East China Normal University, China