Research On Modeling And Application Of College Students' Online Learning Behavior Evaluation

With the rapid development of online education,online learning has become an indispensable learning method,which has been accepted and adopted by more and more people.While online learning is booming,some challenges have also been encountered,such as high drop-out rate of online learning and low completion rate of courses.In order to find out the reasons for this situation,many researchers have invested in online learning behavior analysis research,trying to solve the problems faced by online learning by analyzing learning behavior data of learners online learning process.Based on the question of how to motivate learners' online learning behaviors,this paper attempts to inspire online learners' effective learning behaviors in a data-driven way through the learning performance of online learners.Firstly,this paper summarizes the research status of online learning behavior evaluation at home and abroad through literature review,defines the relevant concepts of online learning behavior evaluation,summarizes the characteristics of online learning,and analyzes the characteristics of online learners.Based on the above analysis,the constituent elements and evaluation process of online learning behavior evaluation were summarized.Based on education theory and the existing online learning behavior evaluation dimensions,the online learning behavior evaluation was divided into three categories: knowledge acquisition,collaborative communication,and learning attitude.Dimensions and determine the evaluation indicators for each dimension.According to the online learning behavior evaluation process,evaluation dimensions and evaluation indicators,a theoretical model of online learning behavior evaluation was concluded.Then,in order to achieve the theoretical model,this study collected data from 3146 learners(20 general education courses)on the "Erya Online Classroom" learning platform of Yunnan Normal University,and used SPSS 22.0 to analyze the correlation between each evaluation index and the final exam results.Sex,with reference to the correlation coefficient,uses the analytic hierarchy process to determine the weights for the evaluation indicators at all levels.Due to the low relevance of communication content,the author deliberately collected the statistical analysis of the communication content and used text analysis tools for analysis.Then two online learning behavior evaluation models are constructed,one is a linear weighted comprehensive evaluation model and the other is a nonlinear fuzzy comprehensive evaluation model.In the process of constructing the mathematical model of fuzzy comprehensive evaluation,the author proposes a method to determine the degree of membership compared with the average value.Finally,in order to verify the validity of the model,the author took 3146 online learners' learning behavior data into two models,and compared the final evaluation results with the learner's final exam results to verify the validity of the model.During the verification process,the fuzzy comprehensive evaluation method needs to evaluate a student's fuzzy matrix multiple times.The author proposes a simple and easy-to-use method for batch data processing.This paper provides two implementation models for the evaluation of online learning behaviors and suggests the application of the model.A reference program is provided to stimulate the study of online learners' learning behavior.