Students' Online Learning Behavior And Its Relationship With Learning Effect Based On Cloud Classroom

Online learning has gradually become more and more popular worldwide.The huge number of users has spawned massive learning data,online learners' clickstream data and interactive forum text data can be used to investigate the online learning behaviors in depth.In this paper,the author takes the undergraduate students in Central China Normal University as research subjects,based on the learning data and curriculum achievement data recorded by StarC which is developed by Central Normal China University.By dividing them into different groups according to grades,this paper investigates the relationship between undergraduate students' online learning behavior and learning outcome from two aspects:the explicit behavior and the implicit behavior.Which could provide theoretical support for the design and optimization of the online learning platform,and guidance for the improvement of the online teaching methods,the main work of this paper is as follows:1.The data of the questionnaire survey and the course achievement data of Central Normal China University were collected.According to academic achievement,the students are divided into three groups,and the corresponding online learning records were sorted out and analyzed.2.Using the sequence analysis method,the explicit learning behavior patterns and click patterns of students with high,medium and low learning outcomes were explored.Then the differences of such patterns between the three groups were analyzed.3.In this part,the author introduced Chinese word segmentation technology for extracting keywords in forum text data,and implying statistics analysis of high frequency vocabulary in different learning effectiveness groups' forum interactive discourses.On the basis of in-depth understanding of all the types of posts the students post in the forum,the author summarizes six interactive discourse models,and deeply analyzes different discourse patterns on the impact of learning effects.4.Based on the four parts of the study above and module settings StarC platform,this paper defined and collected a series of online learning behavior properties.The author introduces the hierarchy analytic method and the Yaahp tool,which divides the online learning behavior into three levels:operational interaction,information interaction and cognitive interaction,and constructs a set of evaluation index system for learners' behavior measurement and monitoring for small-scale private online learning platform.In order to verify the credibility and usefulness of the evaluation index system,a questionnaire survey was also conducted to empirical test this model,and makes the corresponding adjustment based on the results.The innovation of this article is that using the real data explores the relationship between learning interactions incorporating explicit and implicit behaviors and final performances of online college students,and a set of evaluation index system of online learning behavior is constructed.Now,the study of the combination of explicit and implicit behaviors at home is still weak,and there are few studies building the evaluation system of online learning behaviors.This study makes some contributions to inspire the new views of network learning behavior researches and improve platform innovation and teaching method.