Research on the Teaching Reform of Capital Operation Course: Digitally-enabled Innovation
Under the wave of the age of digital intelligence, the teaching of the course "Capital Operation" ushers in the opportunity of change and many challenges. This study takes digital intelligence as the core and explores the teaching reform practice of the course in depth. On the one hand, Course team fully integrate big data, artificial intelligence and other cutting-edge digital technologies to create a rich and diversified teaching resource library and platform, which provides a large amount of accurate and practical teaching materials and cases for the course, and helps students understand the theoretical essence and practical points of capital operation in depth and intuitively. On the other hand, with the help of digitalized teaching tools, the teaching methodology has been innovated to stimulate students' enthusiasm and participation. In addition, Course team emphasize the organic integration of ethical and moral education and professional education in the course teaching, and in the process of teaching professional knowledge and skills of capital operation, Course team guide students to think deeply about the ethical and moral norms and social responsibilities in capital operation activities, and cultivate their professional ethics of adhering to the moral bottom line and following the legal norms in the complex business environment. Practice has proved that Digital Intelligence EmpoCourse teamrment has not only promoted the innovation of the teaching mode and the improvement of the teaching quality of the Capital Operation course, but also facilitated the synergistic development of students' professionalism in capital operation, their ability to apply digital intelligence and their ethical and moral qualities.
Authors
- Yue Xiao (ORCID: https://orcid.org/0000-0001-5158-3267)
- Yan Chen (ORCID: https://orcid.org/0000-0003-0371-5776)
- Yinlei Tang
Publication Details
- Journal
- Journal of Educational Research and Policies
- Published
- 2024-12-30
- DOI
- https://doi.org/10.53469/jerp.2024.06(12).23
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00