Simulation of University Teaching Achievement Evaluation Based on Deep Learning and Improved Vector Machine Algorithm

• Published in: Applied artificial intelligence Vol. 37; no. 1
• Main Author: Chen, Li
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 31.12.2023; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Accuracy; Algorithms; Applications programs; Colleges & universities; Computer simulation; Data mining; Deep learning; Internet; Mobile computing; Quality assessment; Simulation; Students; System effectiveness
• ISSN: 0883-9514; 1087-6545
• DOI: 10.1080/08839514.2023.2195221

In recent years, the rapid progress of mobile internet technology has revolutionized how data is transmitted and shared wirelessly, making it possible to deliver information in real-time to users anywhere. This technological advancement has created new research opportunities, particularly in teaching quality evaluation in colleges and universities using mobile applications. Teaching quality is a crucial evaluation index at the university level, and accurately assessing it is a complex task due to numerous influencing factors. Therefore, there is a need to develop a model that can effectively evaluate the teaching quality to address this challenge. To this end, this paper proposes a teaching quality evaluation model based on data mining algorithms that consist of four parts: evaluation model, evaluation method, evaluation procedure, and practice optimization. This model aims to improve the accuracy of teaching quality evaluation in colleges and universities. Moreover, this study suggests that virtual simulation experiment systems can positively affect the effectiveness of teaching environmental courses. The paper recommends incorporating virtual simulation experiments into the curriculum to enhance students' learning experience. In conclusion, the progress in mobile internet technology has opened up new research opportunities, and data mining algorithms can improve the accuracy of teaching quality evaluation. Additionally, integrating virtual simulation experiments in environmental course teaching can enhance students' learning experience.