Overview
The final grade consists of the following components:
| Component | Weight |
|---|---|
| Class Engagement | 40% |
| Take-home Assignment | 20% |
| Final Project | 40% |
Class Engagement
Your class engagement score is based on the total credits you earn from class participation. This includes both passive engagement (e.g., being cold-called, assigned tasks like mini-lectures) and active engagement (e.g., answering in-class questions, summarizing group findings).
Activities That Earn Credits
| Activity | Credits |
|---|---|
| Summarizing a paper before the discussion session | 2 |
| Answering in-class questions | 1 |
| Asking questions or providing opinions during lecture | 1 (max 3 per week) |
| Summarizing group synthesis | 2 |
| Presenting a mini-lecture | 4 |
| Submitting in-class assignments | 1 |
| Attending other students’ user studies | 1 |
| TBA |
Note: The credits one student can earn are capped at 8 per week.
How Your Grade Is Calculated
We use a dynamic credit system to calculate your class engagement grade. To ensure fairness, the grading benchmark is set by the 5th highest credit earner (the “Anchor”).
- Threshold: You only need 90% of the Anchor’s credits to receive a perfect 100% Class Engagement grade.
- Below Threshold: If you have less than 90% of the Anchor’s credits, your grade equals your percentage of the Anchor’s credits plus 10%. For example, if you have 85% of the Anchor’s credits, your score is 95%.
- Top Performers: The top 4 students receive fixed bonus scores of 110%, 106%, 104%, and 102% respectively.
Take-home Assignment
| Assignment | Points |
|---|---|
| CITI IRB Training | 5 |
| HW1 | 7 |
| HW2 | 8 |
Grading details for each assignment will be available in the individual handout.
Final Project
You will be expected to conduct original research in the HCI field.
Project Timeline
- Proposal Submission: At week X, you will submit a project idea proposal.
- Topic Selection: We will select the best 6 student proposals (student with selected proposal will get 5 point bonus on final project score), combined with 4 instructor-curated projects, to form the pool of available topics.
- Team Formation: You will choose which project to work on and form teams of 1–3 people.
- Implementation: The second half of the semester will focus on implementing your project collaboratively, incorporating the research methods learned in class.
Grading Criteria
The project will be graded based on:
- Final presentation
- Written report
- Individual workload contribution
More details will be provided during the semester.
Policy
Academic Integrity
All students are expected to uphold the highest standards of academic integrity. Plagiarism, cheating, and other forms of academic dishonesty are strictly prohibited. You must not submit work that is not your own or misrepresent others’ ideas as your own. Proper citation and attribution are required when referencing external sources. Violations of academic integrity will be handled in accordance with university policy and may result in disciplinary action.
AI Usage Policy
In general, we permit the use of AI tools (e.g., for proofreading, writing code, or QA).
However, there is one strict prohibition:
Under no circumstances should you use AI to generate data that is supposed to be collected from human participants or other measurement (unless the study itself is designed to evaluate AI-generated data).
Discouraged (but not forbidden):
While not prohibited, we discourage using AI to generate reflections or ideas that you should develop yourself. Offloading cognitive work to AI often backfires: you learn less, and the quality of your thinking suffers. Instead, we encourage an AI-collaborative approach—use AI as a partner to iteratively refine your documents, not as a replacement for your own reasoning.
Your responsibility:
You are fully responsible for all content you submit, regardless of how much was generated by AI. Any material you submit will be treated as your own work and graded accordingly. “It was generated by AI” is not a valid excuse for errors, inaccuracies, or integrity issues. You must verify the correctness, validity, and integrity of all AI-assisted content before submission.
Attendance
Regular attendance is expected. We do not take attendance and will not directly penalize absences. However, class engagement credits are closely tied to attendance and participation, so missing class will likely affect your credit accumulation.
Late Submissions
Late submissions may be subject to grade penalties unless prior arrangements have been made with the instructor.