Construction and Analysis of Evaluation Index System of College Students' Online Learning Based on Analytic Hierarchy Processes

Introduction

Constructing a complete evaluation index system of college students' online learning is a crucial measure for online education, and has important practical significance for promoting the development of online learning and personalized learning. Using AHP and experimental analysis of online learning evaluation index, an online learning evaluation system for college students is established and applied to each learning stage. According to the relevant theory of chromatographic analysis, the experiment constructs the learning index, and constructs the related model, and analyzes the learning efficiency with the model to get the evaluation results, which makes the relevant experimental basis for the later online learning adjustment. This paper explores how to overcome the temptation of environment in mobile learning environment, and proposes to increase online monitoring and feedback mechanism (Ma et al. 2018). A survey of online learning procrastination of college students by means of online questionnaire shows that self-efficacy has reverse predictive ability to online learning procrastination (Shi 2016). This paper puts forward the influence and mechanism of learning input in e-learning environment, and shows that e-learners' self-efficacy can positively predict learning input (Lei et al. 2017). Through the study of professional courses based on Moodle platform, this paper investigates and analyzes the factors affecting students' online learning motivation (Zhang et al. 2013). The impact of feedback types on college students' learning motivation and academic performance shows that task feedback has a positive impact on academic performance (Yang et al. 2015). From the development of flipped classroom, the connotation of learning ability, and the needs of different learning ability elements for flipped classroom instructional design, this paper discusses the flipped classroom instructional design and the connotation of learning ability based on the concept of learning ability (Lv 2015). In-depth analysis of the essential factors leading to the lack of learning ability of college students in the information-based environment of college education, and put forward the training strategies of learning ability of college students in the information-based environment of college education (Tang 2015) . Based on the research of online learning activities, an instructional design model led by online learning activities is designed (Liu 2013). This paper discusses the influence of modern network environment on college students' learning state, and puts forward effective measures for the influence of network environment on learning state (Ma et al. 2019). On the basis of fully drawing lessons from relevant research results at home and abroad, this paper defines the concept of online learning ability of distance learners and constructs a theoretical model (Ding et al. 2015). This paper probes into the gender and grade differences of students' learning ability in private colleges and universities in China, and presents the grade norm of students' learning ability in private colleges and universities (Yan 2017). Embodying students as the main body and students' learning as the center, its key focus is to pay attention to and cultivate learning ability (He 2013). Taking the online learning activity of a hybrid course in Moodle platform as an example, this paper summarizes some characteristics and laws of online learning (Zhang et al. 2016). By combing the related research of learning analysis and combining with the actual needs of teaching administrators, the effectiveness of online teaching performance evaluation mode is verified (Wei 2014). This paper investigates the changing mechanism and influencing factors of college students' English learning motivation by using trajectory equivalent modeling method, which shows that teachers should pay attention to individual differences of learners (Chang 2018). The experiment is based on the analysis of students' online learning, and the corresponding optimization method and the construction of evaluation index are obtained. Firstly, the online learning situation of students is obtained by AHP, and the comparative experiment on weight is made according to relevant theories. Next, the positive and negative matrices are constructed according to the learning subjects and correlation indicators, so as to improve the learning scale. Aiming at the ambiguity of online learning, the construction route analysis of learning index matrix is obtained by means of eigenroot, deviation and mean square error. According to the learning situation, the fuzzy matrix is constructed, and the weights of system indexes are obtained and the consistency is tested at the same time to ensure the adaptability and standard of the system. Finally, the good construction of the online evaluation system will be beneficial to analyze the application situation. Since then, the online education evaluation system will be fully oriented to educational institutions.