Big-data-based Learning Intervention and Learning Analysis
More and more colleges and universities adopt the hybrid education method as the main teaching method.Blended learning combines traditional face-to-face and online teaching for students,increasing the interactivity of the course content and the diversity of teaching.However,how to provide students with effective course resources and effective interaction methods,is more targeted.It requires the usage of big data analysis to find a solution.Through my empirical study of 363 sophomore accounting students in my Tax-law course,finding shows two evidences; one is that key factor which has a direct impact on student learning mood; the other is without adequate supervision,students will still try to cheat on the LMS.My conclusion includes three points; at first,we can use a big data mining to create a multidimensional analysis of the stereoscopic analysis including background factors; secondly,we should increase the cost of cheating by improving the LMS and a reasonable evaluation system; lastly,under collaborative learning,in order to improve learning quality we need to increase effective team integration to fulfill some task and internal assessment and interaction.
Blended learning LMS Interaction Impact factor Multi-dimensional analysis Prediction Collaboration
Tao WU
Z.J.College of SCAU University Guangzhou,China
国际会议
深圳
英文
412-421
2019-07-23（万方平台首次上网日期，不代表论文的发表时间）