Research on the Design and Application of Online Learning Activities for Chinese-foreign Cooperative Universities under the Perspective of Deep Learning

Abstract

After clarifying the development characteristics of Sino-foreign cooperative education in a depth perspective, this paper designs a framework of online learning activities for Sino-foreign cooperative education in combination with the components of online learning activities. Correlation analysis and cluster analysis are used to explore the learners’ knowledge preparation of online learning activities and learners’ behaviors are mined to explore the correlation between behavioral characteristics and learning effects. Regression analysis is conducted with the interactive learning dimension as the independent variable and the learning outcome as the dependent variable to construct a multiple regression model of students’ interactive learning on the learning outcome of online learning activities, and to analyze the influence of online learning autonomy and interactivity on the learning outcome. It also explores the relationship between online learning activity design, teaching quality, faculty, and student satisfaction during internship practice and overall satisfaction. The data show that personal background variables and online learning autonomy explain 0.408 of the variance in learning outcomes, which is an increase of 0.390 in the strength of explanation over that of only personal background factors. The substantial increase in the R-square of the model suggests that the level of autonomy of students in the online environment is an important factor influencing the variance in learning outcomes. The more autonomy the students have in their online learning, the more competent they become in the online learning activities of Sino-foreign cooperative universities.

Keywords

• correlation analysis
• cluster analysis
• multiple regression model
• online learning activities
• 01a25