In the context of artificial intelligence, the rapid development of information technology and the importance of innovative talent training, in order to promote the scientific, precision and effectiveness of learning evaluation, this paper will explore the research progress of multi-modal learning evaluation in the background of artificial intelligence. First, we will define the core concepts in the research, namely artificial intelligence, multimodal, and learning evaluation, and analyze their functions and characteristics. Secondly, we will further summarize the research results of multimodal learning evaluation. These research results mainly focus on the aspects of multimodal accurate evaluation, diversified space, evaluation framework and evaluation model, etc., which promote the research of multimodal learning evaluation and make future teaching evaluation more scientific, more accurate and more effective. This paper will provide a useful reference for the future development of multimodal learning evaluation in the context of artificial intelligence.

Chuyi Chen, Ming Tang, Aobo Yang. Progress in a multimodal learning evaluation based on artificial intelligence. Frontiers in Educational Research (2024) Vol. 7, Issue 7: 22-27. https://doi.org/10.25236/FER.2024.070704.

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