Blended Teaching Research and Practice Combining Ideological Political Instruction and Data-Driven Method

Abstract

In order to alleviate poor course learning effect caused by learning goal confusion and the lack of learning motivation in big data major courses instruction, this paper proposed a blended teaching solution combining ideological political education and data-driven method. Firstly, with the help of smart teaching platform, main instruction process, including pre-class, in-class, after-class and practice, has been restructured and condensed, and teaching materials on ideological and political education towards data science major has also been designed which can enrich in-class interaction and inspire learning interest, and firmly established the professional learning objectives. Secondly, the learning behavior data derived from logs of smart teaching platform is used for analyzing, feedback and early warning, which can help students track their learning status and knowledge mastery, and thus drive them to adjust their learning plans and cultivate active learning habits. Finally, our blended teaching program has been carried out in the course of Principles and Technology of Big Data with 4 teaching classes. The statistics from teaching practice and research show that our solution can greatly improve in-class participation, interest and initiative in learning. Moreover, profiting from learning behavior data analysis and feedback, learning progress can be more accurately mastered, which can supervise students to perform courses learning, and consequently are conducive to the improvement and optimization of the teaching process and significantly improve the quality of course learning.