Policies

Policies Overview

Attendance: See Class Meetings (attendance policy). You are required to attend class. If you miss an in-class-experience, you cannot make it up. If you miss class, please fill out the Missed Class Form. Bring drawing supplies.
Parts of Class: See Parts of Class. The class consists of in class meetings (traditional lectures, group discussions, in-class-exercises), online discussions (weekly topics and seek-and-finds), surveys, and design exercises.
Weekly Rhythm: See Weekly Rhythm. The class follows the same pattern each week.
Grading: See Grading and Late Policy (late policy). Most aspects of class are graded “check/no check.” We grade design exercises. We track “kudos” for good work, and penalize missing assignments.
Late Policy: See Grading and Late Policy. Each assignment has a due date and a hard cutoff.
Use of Generative AI: See Course Policy on the use of Generative AI Tools (s). Use generative tools appropriately: do not claim credit for their work, always cite them appropriately, and do not use them for discussions or surveys.
Recording / Lecture Capture: See Lecture Capture Policy. I may record classes. Even if these recordings exist, they do not take the place of attending class.

I intend to use lecture capture to record class meetings.

I say “intend” - I plan to try to capture all lectures using the technology provided by the University. I may not successully capture all (or any) of the lectures.

Students should be aware that classes may be recorded. While the technology is focused on the instructor (I will wear a directional microphone, and the camera points at the front of the room), I cannot guarantee that others in the room will not be recorded.

In this class you are expected to uphold standards of professional conduct and academic integrity. The University policies on academic misconduct apply to this class.

Proper academic conduct means being honest about your work and being respectful in your communications with staff and other students.

We will have in-person class meetings (in Room 1221 Computer Sciences); we will use Canvas for announcements, discussions, and hand-ins; and we will use this course web to distribute information (we will announce new information on Canvas).

Your grade will depend on all aspects of class.

Canvas will not show your final grade. It will not even estimate it.

Grading in this class is challenging. The quality of a project/assignment may depend on factors beyond class topics (e.g., a student’s implementation skills), and project evaluation can be quite subjective. We do not want to assess your artistic skill or your programming abilities (from before the class).

As such, this class is designed to have a large number of small activities which, if you really do them and take them seriously, will lead to you meeting the learning objectives for the class. See the Parts of Class. If you actively participate consistently, I believe you will learn the lessons.

I am quite aware that most LLM chat tools (ChatGPT, Co-Pilot, etc.) can write completely reasonable responses to the prompts. They tend to be a bit generic and wordy, which means that reading them uses up the time.

It is a waste of a grader’s time (or your discussion partners’ time) to read a GenAI response to a discussion prompt. We all know that the tools can generate reasonable responses without very much prompt engineering work (even I was able to get Co-Pilot to generate reasonable responses to the prompts)! By turning in generated answers, you are wasting others’ time.

Policies

Policies Overview

Lecture Capture Policy

Collaboration Policy and Academic Conduct

Communications Policy

Grading and Late Policy

Course Policy on the use of Generative AI Tools