GA 407.1-2003
Active
T/XZBX 0092-2025
Active
Group standards
T/XZBX 0092-2025 Multimodal artificial intelligence education dynamic evaluation system construction guidance
T/XZBX 0092-2025 Multimodal artificial intelligence education dynamic evaluation system construction guidance
Price:
$ 20.00
Basic Information
Standard Code:
T/XZBX 0092-2025
Standard Type:
Group standards
Standard Status:
Active
is_force_gb:
no
CCS Name:
-
ICS Name:
The application of information technology in other fields
Publish Date:
2025-10-10
Implement Date:
2025-11-01
Scope
With the widespread application of artificial intelligence technology in the field of education, the traditional static assessment model centered on exams has become difficult to comprehensively reflect the true level and development potential of learners. The multi-modal artificial intelligence education dynamic assessment system integrates various information sources such as text, voice, images, videos, and behavioral data, enabling real-time perception, dynamic tracking, and intelligent analysis of the learning process. This assessment system not only reveals learners' cognitive abilities, emotional states, and behavioral habits in a more comprehensive manner, but also provides immediate feedback and scientific decision-making basis for personalized teaching. At present, domestic and international explorations in the field of artificial intelligence education assessment continue to deepen, but there is still a lack of unified norms and guidance in aspects such as data collection, model construction, indicator system design, privacy protection, and adaptation to educational scenarios, resulting in inconsistent assessment results, incomparable data, and difficulty in sharing among different platforms and institutions. Therefore, it is urgent to establish a scientific, standardized, and actionable guide for the construction of a multi-modal artificial intelligence education dynamic assessment system. The purpose of formulating this document is to standardize the collection and processing of multi-modal data, clarify the principles and methods of dynamic assessment, propose ideas for building technical frameworks and application scenarios, and provide reference for education managers, teachers, scientific research institutions, and related enterprises, so as to promote the transition of education assessment from static to dynamic, from single to multiple, and to enhance educational fairness and quality improvement.
Development Information
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