Course Policies

Attendance and Participation

A great deal of success is measured just in showing up where one needs to be at the right time. A next important measure of success is being prepared for meetings and sharing one’s perspective.

Grading for Attendance and Participation:

1 point per class: Attending AND actively participating with clear preparation
0 points: Any of the following:
- Attending but not participating
- Attending but clearly unprepared
- Not attending class

Absence Policy:
You may miss up to two classes without losing points, provided you have justified your absence in advance or in cases of medical or family emergencies. In case of emergency, you must notify the professor by email as soon as possible.

Late Assignment Policy

You may submit up to two assignments late without affecting your grade, provided you have previously agreed with the course professor to submit late, or in cases of emergency.

Late Submission Guidelines:

Assignments submitted late must be submitted within five business days from the original due date to receive full or partial credit
If late submission has not been previously agreed upon:
- General assignments: Lose 1 point from the total available points every two days
- Partial exams: Lose 20% of total available points per day

Group Work Policy

Group work is an essential component of this course, particularly for the final project and various collaborative assignments throughout the semester.

Group Work Expectations:

Attend all group meetings and contribute meaningfully to your team’s work
Contribute equitably to all group assignments and deliverables
Communicate actively with your team members about progress and challenges

Consequences for Non-Participation:

Taking credit for work you did not contribute to is not tolerated in this class
Should you fail to contribute to a group assignment, you will receive 0 points for that assignment
Repeated offenses may result in you being removed from a group and failing the class
Repeatedly missing group meetings without valid justification will be treated as non-participation

AI Usage Policy

This course encourages the thoughtful integration of AI tools as part of your learning process, particularly for enhancing your understanding of course materials and practicing business English concepts.

Approved AI Usage:

First, develop your own thoughts: Draft your initial responses and form your own opinions before consulting AI tools
Then enhance with AI: Use AI to refine, expand, or strengthen your work after you have established your own foundation
Cite AI usage: When AI tools are used for assignments, clearly cite the technology used and explain your modifications

Important Principle:
Being able to form your own opinion without AI influence and then strengthen it through AI assistance is a crucial professional skill. Avoid early AI influence that might prevent you from developing independent analytical thinking.

For Assignment Work:

Complete your initial draft and thinking independently
Use AI as a revision and enhancement tool, not as a starting point
Always maintain your authentic voice and perspective in final submissions

Extra Credit Policy

Extra credit is designed to reward exceptional effort and consistency, not to replace missed regular coursework. Students who consistently attend and complete assignments should not need extra credit to succeed.

Perfect Attendance Extra Credit (2 points):

Attendance tracking begins Week 2 (32 total class meetings)
Students can miss up to 2 classes without losing points, since we have 32 classes and attendance is worth 30 total points
Students who attend all 32 remaining classes earn 2 extra credit points

Custom Assignment Extra Credit (3 points):

Students may design their own course assignment equivalent in scope to regular assignments
Assignment must connect to course content and include clear deliverables
Must be submitted for approval by Week 10
Must be completed by Week 15 (no extra credit during final project weeks)
Student provides self-assessment rubric to minimize professor workload

Extra Credit Limitations:

Maximum 5 points total (5% of final grade)
Cannot exceed 100% in the course
No extra credit available during Weeks 16-17 (final project period)

For detailed information about custom assignment options, see the Extra Credit Assignment page.

Academic Integrity

In this course you must submit original work. This means that, while you can and should cite your sources, the work must reflect your own analysis and perspective. For many assignments, the use of generative AI is permitted following the AI usage guidelines above.

Regarding Team Work:
All members must contribute equitably to group assignments. If you take credit for group work to which you have not contributed, you may lose between 10 and 20 percent or more of your final grade, in addition to facing more serious consequences depending on the nature of the infraction.

Plagiarism Consequences:
Plagiarism of work from other students or online resources, as well as submission of non-original work, will result in a zero grade on the assignment and will be reported to the program director, with potential additional consequences.

Success Tips

The course requires 6-8 hours of weekly work outside of class. Generally you will have one assignment per week.
Review materials before Tuesday classes to participate effectively.
Start assignments early to have time to resolve questions.
30-minute rule: First research independently, then consult with classmates, and if after 30 minutes you don’t find a solution, contact the professor.
The professor responds to messages during business days via Teams or email.

📥 Download Course Policies

Find this file on our repo and download it!

🤖 AI Study Prompts

Copy the downloaded policies and try these prompts:

“Explain the difference between appropriate and inappropriate AI usage for this course”
“What strategies can I use to be better prepared for class participation?”
“How should I organize my group work to ensure equal contribution from all members?”

Next: Explore the Bibliography for course resources and recommended readings.