【摘要】 随着人工智能、物联网、大数据等技术的快速发展及其在教育领域的深度应用，教学过程逐渐走向智能化、精准化和个性化。学习状态人机协同监控指教师和智能机器分工协同，共同完成学习状态多模态数据的采集与处理，精准识别学生的个性化学习需求，为教师精准教学与学生个性化学习提供数据支持。通过构建由4个一级指标、11个二级指标和42个三级指标构成的大学生学习状态监控指标体系，并结合该指标体系提出了人机协同监控策略，可以有效解决大学生学习状态监控什么与如何监控的问题。更多还原

【Abstract】 Teaching has been getting more intelligent, precious, and personalized, as a result of rapid development and application of such technologies as artificial intelligence, the Internet of Things, and big data, etc. Teachers and intelligent machines are capable of collaborating in collecting, processing students’ multimodal data generated in their learning, and identifying accurately their needs, facilitating data-driven support in teaching and learning. Thus human-machine collaborative monitoring system is constructed serving this end. The present study constructs an index system, consisting respectively of 4 primary, 11 secondary, and 42 tertiary indexes. The study then proposes strategies for human-machine collaboration in monitoring college students’ learning.更多还原