Research on the relationship between teachers' and students' behavior and the measures to improve the teaching quality

• Published in: 2020 International Conference on Big Data and Informatization Education (ICBDIE) pp. 334 - 337
• Main Authors: Gong, Bing, Jing, Fan, Liu, Lili
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2020
• Subjects: Analytical models; behavior data of teachers and students; Big Data; component: classroom teaching; Data models; Education; prediction model; Predictive models; Psychology; real-time evaluation mechanism
• DOI: 10.1109/ICBDIE50010.2020.00084

With the approach of artificial intelligence to education, big data analysis has played a very important role in higher education and higher education management. However, due to the complex and changeable characteristics of teachers and students' classroom behavior, especially the interpretation of classroom behavior has obvious subjective color, so the use of big data behavior data analysis and AI assisted teaching behavior interpretation will become the only way for the development of education. This paper use a variety of technical means to collect the behavior data of teachers and students in classroom teaching, and cross judge the multi-source data, introduce complete random number algorithm and transformation regression model to regularize the classroom data and build a prediction model. The positive and negative feedback of teachers' teaching behavior in classroom teaching is carried out, and the mapping relationship between students' behavior data and teachers' behavior data in classroom teaching is used to further judge teachers' teaching behavior, form evaluation mechanism in real time, and establish quantitative evaluation basis for teachers' teaching ability improvement.