Data analysis of blended learning in python programming. Chu, Q., Yu, X., Jiang, Y., & Wang, H. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 11336 LNCS, pages 209-217, 2018. Springer Verlag. abstract bibtex 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.
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title = {Data analysis of blended learning in python programming},
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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.},
bibtype = {inProceedings},
author = {Chu, Qian and Yu, Xiaomei and Jiang, Yuli and Wang, Hong},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
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