Abstract
Utilization of educational data is being increasingly demanded to enhance personalized and collaborative learning within schools. In particular, the effective use of educational data holds significant potential within university teacher training courses. This manuscript presents our experimental application of educational data-based instructions for student teachers during their teaching practices. The data were gathered using a sensor technology with artificial intelligence (AI), which could detect a speaker and trace individual positions, to improve classroom management skills. Two classes managed by a student teacher were analyzed as an initial case study. In the educational data collected by the sensor technology, various factors that could affect classroom dynamics, such as the change over time in the ratio of teacher to child speech, the teacher's standing position per second, and the change in the overall child downward rate were displayed. The analyzed data was then interpreted and instructional guidance was provided to the student teachers based on these insights. The results of this study indicated that the collected educational data could effectively track student teachers’ growth and identify the challenges faced by them during the teaching practice. In addition, the analyzed data could be used as instructional evidence.
