Educational Assessment, Measurement and Intelligent Analysis

Educational assessment and measurement are undergoing a paradigm shift driven by Big Data and Artificial Intelligence. This session, “Educational Assessment, Measurement and Intelligent Analysis,” explores how Big Data and AI are transforming educational assessment from traditional, single-indicator testing toward continuous, diagnostic, fair, and interpretable intelligent evaluation. We invite submissions that integrate multi-source evidence—such as learning process data, teaching behavior data, and learning outcomes—to improve measurement precision and equity, generate actionable insights through interpretable analytics, and enable timely feedback and personalized interventions in authentic educational settings. We especially welcome work on multimodal learning analytics, cognitive diagnosis and learner profiling, automated scoring and writing assessment, formative and adaptive assessment, large language models for assessment, and issues of fairness, privacy, and data-driven decision support for educational quality assurance and governance.

Session Chairs

Prof. Dr. Piero Dominici, University of Perugia, Italy

Dr. Zhe Chen, Central China Normal University, Wuhan

Dr. Liujian Gu, Fudan University, Shanghai