Instituto de Investigaciones en Inteligencia Artificial, Universidad Veracruzana, Xalapa, Veracruz 91097, Mexico.
Division of Research and Postgraduate Studies, CONACYT-Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 852 Col. Emiliano Zapata, Orizaba, Veracruz 94320, Mexico.
Biosensors (Basel). 2022 Jul 11;12(7):509. doi: 10.3390/bios12070509.
Appropriate teaching-learning strategies lead to student engagement during learning activities. Scientific progress and modern technology have made it possible to measure engagement in educational settings by reading and analyzing student physiological signals through sensors attached to wearables. This work is a review of current student engagement detection initiatives in the educational domain. The review highlights existing commercial and non-commercial wearables for student engagement monitoring and identifies key physiological signals involved in engagement detection. Our findings reveal that common physiological signals used to measure student engagement include heart rate, skin temperature, respiratory rate, oxygen saturation, blood pressure, and electrocardiogram (ECG) data. Similarly, stress and surprise are key features of student engagement.
适当的教学策略可以使学生在学习活动中投入其中。科学的进步和现代技术使我们可以通过读取和分析附在可穿戴设备上的传感器的学生生理信号,在教育环境中衡量学生的参与度。这项工作是对当前教育领域学生参与度检测计划的综述。该综述突出了现有的用于监测学生参与度的商业和非商业可穿戴设备,并确定了参与度检测所涉及的关键生理信号。我们的研究结果表明,用于衡量学生参与度的常见生理信号包括心率、皮肤温度、呼吸率、血氧饱和度、血压和心电图(ECG)数据。同样,压力和惊喜也是学生参与度的关键特征。