In-Depth Integration and Exploration Practice of “Rain Classroom” in the Teaching of Big Data Courses for Medical Colleges and Universities

Abstract

AbstractPurpose: Proposed a big data course teaching reform plan to improve the teaching effect, strengthen the interaction between students and teacher, So as to build a Multidimensional teaching atmosphere, through the implementation of a new type of big data course experiment plan, ultimately strengthen students’ hands-on practice ability, and cultivate a group of cross-integrated big data talents who can understand the professional terminology of doctors and medical experts. Method: Taking medical information engineering and data science and big data majors in medical schools as examples, It introduced “Rain Classroom” technology into the teaching environment, and carrying out online and offline integrated teaching innovation, It can pushing teaching content to students before class, so students can be preview it in advance; This reform could carry out better interactive teaching atmosphere during class, and increase student participation, teacher could respond to students doubts and difficulties in real time; After class, teacher could summarize students learning, and then distinguish students at different levels, conduct differentiated guidance; It could manage all students through diversified assessment schemes; The learning process truly and objectively reflects the student’s learning situation. Conclusion: The teaching reform plan is applied to actual teaching work. Through questionnaire surveys, interviews and other evaluation methods, it is found that the teaching reform plan can significantly improve the teaching effect; it also improved students’ independent learning ability, and promoted the cultivation of interdisciplinary professional talents. It is conducive to promoting the education and teaching reform of big data subjects in medical schools.KeywordsInter disciplinaryBig data course teachingOnline and offline teaching integration“Rain Classroom” technologyVirtual laboratoryMedical big data