Development Of In-class Attention Assessment Tool Used Internet Of Things

Establishing students’ learning database and behavior database,storing the process of students’ interaction with learning content,user behavior and personal characteristic information are the prerequisites for carrying out learning analysis.To improve the question that the previous study whose date was analyzed on a single line and to rich the learning dimension analysis data,this study was based on Internet of things technology,combined with the related theory and cognition,per the attention to sitting posture data,applying Wemos development board,OneNET data cloud and HTML 5 technology for the classroom attention condition,data acquisition,storage,and analysis of classroom assessment tools.To test and verify the reliability of equipment data at the same time,the research was carried out in the real classroom to test the whole system.The system collected data was compared with the records of real classroom video in multidimensional data such as attention distribution data,the teachers assess of the attention,the score of traditional attention tests and so on.The purpose of this test was to use individually multidimensional data to certificate the effectiveness of the assessment tool.The experimental data analysis results show a significant correlation in the instrumental classroom attention data and the real classroom video data,and the learners focus attention data determined by the classroom assessment tool possesses certain accuracy.In this way,the assessment tool can partly replace artificial observation attention;However,the results of traditional attention test are different from that of teachers,and the results of classroom attention assessment tools are closer to the daily observation results of teachers,and the data analysis dimension is more comprehensive.