Analysis and Satisfaction Evaluation of Online Learning Based on Artificial Intelligence

Introduction

With the rapid development of artificial intelligence, the large-scale popularization of portable devices such as computers, mobile phones, and tablets that can use the Internet, the form of distance education has undergone great changes. As one of the most widely used forms, online learning is widely used in current learning. In order to understand the quality of online learning and people's satisfaction with it, this paper uses the rough set algorithm to construct an online learning quality evaluation index system, and evaluates and analyzes the online learning quality and satisfaction based on artificial intelligence. Artificial intelligence technology is one of the most advanced technologies in the world, and its rapid development has caused changes in all aspects. Artificial intelligence + education embodies the deep integration of artificial intelligence and education. In the process of solving educational problems, adaptive system with artificial intelligence is an important application form (Jing Leng et al., 2021). Traditional teaching methods have been difficult to adapt to the changes of music education. With the continuous expansion of the application scope of multimedia technology, music education in colleges and universities also applies multimedia technology to music teaching classroom practice. The definition of artificial intelligence can be divided into two parts, namely “artificial” and “intelligent”(Lv Yinghua .,2022). It is the study of making computers to simulate certain thinking processes and intelligent behaviors of human beings (Hutson M,2018). It introduces the theoretical basis of the construction of all-media teaching resources in China-Taiwan system, introduces the integrated docking scheme and components of China-Taiwan system, discusses the practical results of promoting online and offline synchronous teaching in Peking University, and finds that China-Taiwan system is innovative in construction concept, application logic and development mode(Zeng Teng.,2022). In view of the existing research model can not systematically solve the e-government online learning behavior and computational action between the relationship and interaction. By integrating the triple attributes of availability opportunity, individual technical ability and social network isolation contained in the intersection of information communication and computing action into the online learning behavior model of e-government, From the perspective of relational attributes, this paper explores the behavior modeling method of e-government online learning, which includes the influencing factors of behavioral relationships and the interaction of relational attributes such as availability opportunities, individual technical capabilities and social network isolation(Sun Jie, 2021). Rough sets are a mathematical tool for dealing with uncertainty (Kieslinger B et al.,2018). Online learning is the most impactful of all learning modes (Nihuka K A & Voogt J,2018). From the perspective of media richness theory, we can put forward corresponding solutions, including effective and smooth communication channels, popularization and use of natural language, extensive publicity of advantages and characteristics, continuous improvement of policies and regulations, and optimization and promotion of learning resources(Qian Xiaolong et al.,2022). It fully respects the individuality of students and stimulates the motivation of learning (Rajab, Khairan D, 2018). Online learning is not limited by time, place and space (Tojo T et al.,2018). Online education, as the research background, attempts to explore the connotation of the effectiveness of innovation and entrepreneurship education, excavate its functional value, and try to explain the countermeasures and measures of the effectiveness research of college students' innovation and entrepreneurship education under the background of online education, which enriches the theory of college students' innovation and Entrepreneurship Education, and further integrates employment and entrepreneurship into the theoretical system of ideological and political education (Wang Ying, 2021). Quality evaluation is the basis for improving product quality (Lalilta R,2018).. The trend of macro quality level development can be predicted (QSE Hammouri,2018). Online education industry status data, through the collection of Hebei Province population education status, information and communication status and other data, combined with the current national, provincial government and other departments of the relevant policy guidance, analogized the status of online education in Hebei Province, analyzed the development prospects of online education in Hebei Province and put forward suggestions(Dong Kunjing ., 2021). Satisfaction is obtained by weighted calculation of evaluation scores (Klasnja-Milicevic A et al.,2018). With the development of Internet technology, regional differences and other issues lead to great differences in education levels in different regions. The existing literature is applied to online education, which is generally applied to curriculum learning in the education system, but there are poor teaching effect, large system delay and low student satisfaction. Using artificial intelligence algorithm can effectively improve students' learning efficiency and satisfaction, and the optimization of algorithm performance can improve response time.