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    脑机接口技术支持学习情感识别的 应用框架及反思

    Application Framework of Brain-Computer Interface Technology to Support Learning Emotion Recognition and Its Reflection

    [浏览次数:16399]

【作      者】:

赵 丽, 李苏琦, 王淑文


【关 键 词 】:

脑机接口; 情感识别; 人工智能; 学习情感; 教学调控


【栏      目】:

学习环境与资源


【中文摘要】:

人工智能技术支持下的学习情感识别在教育教学研究中至关重要,能够促进教育教学策略的改进。脑机接口技术作为人工智能技术的一项重要应用,已成为情感识别领域研究热点之一。文章分析了脑机接口技术支持学习情感识别的发展动因,进而构建包括数据处理、情感表达与教学调控三个过程的脑机接口技术支持学习情感识别的应用框架,探讨了脑机接口技术在学习情感识别领域仍面临的技术鸿沟、伦理挑战与学习者的主观偏见等局限。最后提出未来脑机接口支持下的学习情感识别可从强化技术融合、发展以人为本为导向的设计,以及尊重学习者的主观需求等方面进行改进,从而保证脑机接口技术支持学习情感识别应用的可行性,并综合衡量学习状态,拓展其在教育领域的应用与创新。


【英文摘要】:

Learning emotion recognition supported by artificial intelligence technology is crucial in education and can facilitate the improvement of teaching strategies. Brain-computer interface technology (BCI), as an important application of artificial intelligence, has become a hot issue in the field of emotion recognition. This paper analyses the motivation for the development of BCI technology to support learning emotion recognition, then constructs a framework for the application of BCI-supported learning emotion recognition that includes three stages: data processing, emotion expression and teaching moderation, and explores the limitations of BCI technology in learning emotion recognition, such as the technical gap, ethical challenges and learners' subjective bias. Finally, it is proposed that future BCI-supported learning emotion recognition can be improved by enhancing technology integration, developing human-centered design and respecting learners' subjective needs, which will ensure the feasibility of BCI-supported learning emotion recognition applications, and expand its applications and innovations in education by comprehensively measuring the state of learning.

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