Value Assessment for a Theory-Oriented Flipped Classroom of Physical Education Based on Multi-Source Data Analysis

Abstract

In order to overcome the problem of students’ boredom in physical education theory classes in general, and to give full play to the role of assessment in guiding, diagnosing, motivating and proving, this paper analyses the multi-source data generated during the teaching process, which can predict students’ subsequent learning status. Based on the collection and processing of data from multiple sources, this study takes the PE course as an example and predicts the course performance based on multiple dimensions; and carries out empirical analysis with the actual course performance through numerical correlation, ranking correlation and the bottom band. The analysis was compared with actual course grades through numerical correlation, ranking correlation and bottom band warning coverage of students. The results of the study show that the earliest grade prediction using taught courses has the highest student warning coverage; the highest grade prediction based on unit tests has the highest numerical relevance and ranking relevance; and the highest grade prediction based on unit tests has the highest student warning coverage.