Training Methods of Computational Thinking for Medical Students in Big Data Age
Jiarui Si, Huan Feng, Zikun Niu, Yizhou Bian, Yu Fu, Hong Wei Guo, SU Zhen-xing, Weimin Deng, Xiaoxia Li · 2021
The era of big data witnesses that ‘computing’ has become an indispensable tool for medical development in many aspects of medicine domain. The ability of computational thinking is of great significance to medical students engaging in basic research and clinical diagnosis and treatment in the future. However, medical students are lack of this strategy in dealing with problems at present. Meanwhile, there is also a problem of ‘insufficient skills and no training’ in computer learning. In this article, we recommend training students’ computational thinking from three aspects. First, students can learn the basic concepts of computational thinking and different thinking modes of computer scientists through computer courses in both theory and practice in order to train their computational thinking. Second, in the process of thinking, students can directly carry out divergent thinking, logical integration, and practice the thinking methods of scientists such as abstraction and simplification through the mind maps produced by IMindMap software. Third, during the practice of modeling and programming, after using mind maps to make the problem abstract and sort out the content of the creation to draw a flowchart, students start modeling and systematic design through Scratch software. At last, under the help of MATLAB, some specific medical cases enable students to apply computational thinking to practice comprehensively. Our practice in class shows that these training methods has positive influence in improving students computational thinking.