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Data Analysis of Blended Learning in Python Programming

  • Qian Chu
  • Xiaomei Yu
  • Yuli Jiang
  • Hong Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11336)

Abstract

The rapid emergence of blended learning has sparked a great deal of research interest in the field of educational data mining. We apply the novel educational form of blended learning in the undergraduate curriculum of python programming. With the questionnaire before curriculum is obtained to capture the basic information of undergraduate students, we design educational resources and activities for online studying and face-to-face teaching. Since the learning process of each student is captured continuously, we make teaching and learning evaluations weekly to improve current teaching methods hence arouse students’ interest of continuous learning. With analyzing data and mining knowledge received in the process of blended learning, some beneficial results are gained to promote the quality of blended learning in the undergraduate curriculum of python programming, and benefit the undergraduate students as well as higher education in the long run.

Keywords

Blended learning Education Python Data analysis 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Qian Chu
    • 1
    • 2
  • Xiaomei Yu
    • 1
    • 2
  • Yuli Jiang
    • 1
    • 2
  • Hong Wang
    • 1
    • 2
  1. 1.Institute of Information and EngineerShandong Normal UniversityJinanChina
  2. 2.Shandong Provincial Key Laboratory for Distributed Computer Software Novel TechnologyJinanChina

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