Application Of Blended Teaching In "Network Data Analysis Based On Python"

The novel teaching form of blended learning has opened up a new era of education by pushing the so-called "forced-feeding method of teaching" to the end.With both online video learning and flipped classroom,blended learning makes it possible for the teachers to spend more time interacting with students in class.Moreover,the flipped classroom teaching actually enhances the interests of students to participate in class.Therefore,we introduce blended learning into the undergraduate curriculum of "python for network data analysis".As an elective course,the purpose of the course is to introduce the programming language of python and show common data analysis methods as well as some machine learning libraries in python.The basics of programming and engineering problem-solving methodology are also introduced in the course.The study combines the constructivism and other educational theoriesand constructs a hybrid teaching model in the course of "python for network data analysis ",which is based on the teaching platform of super-star network in Shandong Normal University.The main work in the paper is outlined as follows.1?In the first semester of 2017,the basic informationof undergraduatesenrolled in this courseis collected through the survey questionnaire.With statistical analysis and data mining,we obtain the characters and personality of the undergraduate,so as to design content of teaching in this paper.2?Educational resources and activities are designed and exerted in this course.As each student's learning process is captured,we conduct weekly appraisals to improve current teaching methods and thereby motivate students to learn.3?By analyzing the data collected in the blended learningprocess,effective teaching feedback can be obtained to promote the quality of blended learning in undergraduate courses,which will benefit the learning in the following week.