Evaluating the Quality of Internet-Based Education in Colleges Using the Regression Algorithm

Abstract

An efficient and effective mechanism is required for quality education in schools, colleges, and universities. After the pandemic worldwide, every organization worked online from home instead of on the site. The educational institutes started online classes using various platforms. The quality of education using online classes is affected by numerous factors, including hardware, software, and the internet. Therefore, in this paper, the quality evaluation of internet education using a regression algorithm is proposed. The proposed system optimizes the hardware design and functions of the client end of the internet education of colleges and universities. It determines the time response data sequence of the grey prediction model and ensures that the proposed scheme's prediction accuracy is high. By adopting the logistic regression, the rules for the overall evaluation of the education quality are formulated. The database of the rules for the overall evaluation of the education quality of the internet of colleges and universities is generated. Experimental results show that the response time of the education quality evaluation system is about 1.3 sec. The probability of failure is very low than the existing literature.