Modeling and Analysis of Classroom Teaching Evaluation Platform Based on Colored Petri Nets

摘要

The accurate evaluation of classroom quality can quantify the teaching effect of teachers and reflect the learning effect of students at the same time. Traditional questionnaire survey and observation evaluation cannot evaluate classroom quality objectively for a long time, and cannot get clear and definite evaluation results. Therefore, It is necessary to establish an intelligent evaluation method for recording students' classroom behavior. In this paper, the intelligent campus classroom quality evaluation platform is proposed, and the overall framework and module components of the platform are described in detail. The platform considers the sensor information, flow information, and electricity information of the mobile device during the classroom, and trains the classification model through the neural network to give the fine-grained classroom quality assessment scores, so that the school can grasp the overall classroom quality of the students, and the teacher makes appropriate teaching reforms. Students view and improve their own classroom quality. In order to simulate the execution process of the platform, colored Petri net (CPN) is used to model the platform, and the functions, boundedness, reachability and liveness of the platform are analyzed. The analysis results show that the platform can be carried out correctly and reliably, and the development cost can be saved.