OPEA Worshop 2025 - Call for Papers

Scope

We invite submissions of original, unpublished research on topics related to AI-driven personalization in education. We anticipate relevant works on a range of topics, including but not limited to:

Automated test assembly and parallel form construction (e.g., using evolutionary algorithms, integer programming)
Machine learning models for understanding academic motivation, attribution, and engagement
Affective computing, student emotion detection, and their roles in feedback
Cognitive diagnosis models and their practical applications
Algorithms and systems for adaptive testing and intelligent item selection
Automated scoring and feedback generation for complex tasks
Optimization of learning pathways and curricula for individuals or groups
Reinforcement learning for optimizing pedagogical policies and adaptive interventions
Resource allocation and scheduling in educational systems
Educational data mining and learning analytics for personalization
Generative AI for creating educational content and interactive learning scenarios
Explainable AI for educational decision-making and recommendations
Development and case studies of AI-powered tutoring systems
Ethical considerations, fairness, and bias in educational AI systems

Submission Instructions for Authors

Authors should follow Springer LNCS Authors Guidelines: Information for Authors to prepare their papers. Formats for the submissions are limited within a maximal length of 8 pages for main content and 4 pages for references. All accepted papers by a registered author will be published as a volume in the Springer series Lecture Notes in Computer Science (LNCS). Authors should consult Springer's authors' guidelines and use the proceedings templates there linked. There are both LaTeX and Word formats: the authors make their choice. Also, authors should comply with Springer's authors' code of-conduct. Among the papers accepted at the conference, some will be selected to be extended and submitted to a planned Special Issue of the Journal IEEE Transactions on Learning Technologies.

Each submission will be reviewed by at least two PC members. Acceptance will be based on originality, technical quality, relevance to the workshop theme, and clarity of presentation. Some Accepted Papers will be further voted by program commitee member and recommended to be presented at the Workshop (Nov. 30th, 2025).