Application of Big Data Technology in Blended Teaching of College Students: A Case Study on Rain Classroom

Cuibi Yang, Shuliang Huan, Yong Yang

Abstract


Rain classroom is a big data tool that effectively connects the teacher with students throughout the teaching process. This paper mainly applies rain classroom in blended teaching of college students, and evaluates the application effect. Firstly, the authors set up a model of rain classroom, covering all three phases of the teaching process: before-class (B), in-class (I) and after-class (A). Next, the BIA model was applied to the course Film and Television Appreciation, and the key issues in each phase were explained. To evaluate the effect of the BIA model, two questionnaire surveys were carried out among engineering students in Chongqing Three Gorges University. The results show that rain classroom can greatly improve the learning effect of the target course in various aspects: the teacher could arouse the students’ learning interest by sending red packets, make students more attentive through limited-time quiz, and reduce the absence through random roll call; the students were actively involved in group activities and confident in presenting their findings; however, many students most students switched to other apps in the class. The research results provide new insights to the application of big data technology in college education.

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Copyright (c) 2020 Cuibi Yang, Shuliang Huan, Yong Yang


International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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