Grading Policy
The final grade consists of:
- Attendance & Participation 20%
The various in-class activities will include case discussion, class participation, and peer review. Students who are unable to attend class should please apply for a leave of absence in advance.
2. Course Reflection 20%
The class reflection should consist of the students’ takeaway, lesson learnt, or insights from the course. It should be a maximum of 2-pages, 12points Times New Roman/Arial, double-spaced.
3. Midterm Paper - A review of your country’s digital trade initiatives 30%
The midterm paper is an individual assignment to understand the students’ knowledge about digital trade. Each student shall write a short review paper about the digital trade initiatives of their respective countries. This assignment should include the concepts from previous lessons, including the challenges faced in the digital trade implementation, the implementation steps, the reengineered processes, the benefits of the digital trade projects and the students’ comments about the current status.
It should be a maximum of 5-pages, 12points Times New Roman/Arial, double- spaced.
4. Final Presentation – Best Practices of Cross Border Digital Trade 30%
The final project is a group project. More explanation on group sizes and how the assignment can be conducted will be provided in class.
Prior to the final presentation, students will be arranged a session to present their proposal about their final projects for obtaining feedback from the instructor and classmates.
Each team shall present a best practice or a new idea of cross border digital trade implementation for the final project. The final project includes an oral presentation and a 2-pages executive summary.
Class Contract
As the course instructor, I aim to help students develop their knowledge of cross border digital trade beyond the textbook. To facilitate an engaging learning environment, this class employs a range of activities that draw from the readings, in-class discussion, case studies and live system demonstration that help students understand the essence and application of the assigned materials.
In return, students are expected to attend and actively engage with their classmates in discussions and other class activities and to enable this by preparing in advance and avoiding academic dishonesty (including plagiarism). Students who are unable to attend class should please contact the course instructor in advance to apply for a leave of absence. For group activities, students should also inform their group members.
Note: Students must acknowledge all instances in which generative AI tools were used in an assignment (such as in ideation, research, analysis, editing, debugging, etc.).
|