Research on the construction and optimization of students’ metacognition under intelligent education management

With the acceleration of the process of education informatization and the continuous emergence of technological innovation, intelligent education is ushering in unprecedented development opportunities. Based on metacognition, this paper proposes a model of student metacognition and affective regulation in intelligent education system. First of all, this paper reviews the current research status of metacognition and emotion in the intelligent education system, and clarifies its important functional positioning in the system. This paper focuses on the measurement method, implementation process and data analysis strategy of emotion regulation in intelligent education system, which lays a solid foundation for the construction of the subsequent model. In terms of theoretical framework, this paper proposes a comprehensive model of metacognitive perception and emotion regulation in intelligent education system. The model not only considers the sequence data of learners' classroom behavior, but also fully integrates the learners' current cognitive level, and combines the classroom interactive text data for fine design. In order to verify the validity of the proposed model, rigorous experimental tests are carried out on real data sets. Specifically, the mean metacognitive post-test level of the experimental group was 91.795, and the standard deviation was 2.691. The mean metacognitive posttest level of the control group was 79.957, and the standard deviation was 2.610. Through covariance analysis, we found that F value was 9.968 and P value was 0.004 < 0.05. The experimental results show that when the initial metacognitive level is the same, the experimental group of learners who receive metacognitive affective regulation training in the intelligent education system have significantly improved their metacognitive post-test level compared with the control group.