肖婉,季一木.传感数据:智能时代学习分析的新视角[J].南京邮电大学学报(社会科学版),2024,(02):56~64 |
传感数据:智能时代学习分析的新视角 |
Sensor data: A new perspective on learning analysis in the intelligent era |
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中文关键词: 传感数据 学习分析 教育大数据 智能化 教育信息化 |
英文关键词:sensor data learning analysis educational big data intelligentize educational informationization |
基金项目:教育部人文社会科学研究青年项目“基于多模态数据的学习者情感分析及应用研究”(20YJC880104);江苏省社会科学基金青年项目“江苏高校大学生网络欺凌现象的话语分析与防治对策研究”(19JYC002);江苏高校哲学社会科学研究基金项目“‘双一流’背景下江苏高校海归教师逆文化冲击及对策研究”(2018SJA0079) |
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中文摘要: |
智能时代,各种智慧教育场所、移动智能终端和可穿戴设备中应用的传感技术可以对学习者的生理特征、行为动作及学习场所等相关数据进行捕捉,使学习者“身体”重新回归到教育者视野,并通过低倾入性的方式采集真实情境中的序列数据,为实现全方位、情境性和过程性的学习分析提供条件。当前,在教育实践中,传感数据已逐步应用于认知监测、行为分析、情感识别以及自适应情境学习等方面,为智能化学习分析与评价提供了良好支持。随着技术与实践的发展,学习分析中的传感技术将从“有感”走向“无感”,传感设备将从单一设备转变为集成系统,应用目的将从对学习过程的合理解释走向精准干预,并从实验研究走向多样化实践。在传感数据应用于学习分析的实践中,教育部门、研究机构和企业应共同努力,以应对理论基础、技术成本和伦理隐私等方面的挑战。 |
英文摘要: |
In the era of intelligence, the sensing technology applied in various smart education venues, mobile intelligent terminals, and wearable devices can capture related data of physiological characteristics, behavioral actions, and environment of learners, allowing learners to return to the perspective of educators and collect sequence data in real situations through low immersion, providing conditions for achieving comprehensive, situational, and procedural learning analysis. Currently, in the context of educational practice, sensor data has gradually been applied in cognitive monitoring, behavioral analysis, emotion recognition, and adaptive situational learning, providing good support for intelligent learning analysis and evaluation. With the development of technology and practice, sensing technology in learning analysis will move from “sensing” to “non sensing”, sensing devices will move from single device to integrated system, application purpose will shift from reasonable explanation of the learning process to precise intervention, and from experimental research to diversified practice. In the application of sensor data in learning and analysis practice, education departments, research institutions, and enterprises should work together to address challenges in theoretical foundations, technological costs, and ethical privacy. |
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