Students will be graded on:
In each category, the lowest grade will be dropped.
Each week there will be two written assignments. One due by noon the following Tuesday, and another and due at noon on Friday, 2 hours before class. The one due on Tuesday will cover what you worked on the previous class, the one due on Friday will be on the assigned reading for that upcoming class. These assignments are designed to help you reflect on your work from the previous class and prepare for the upcoming one. It is a space to document your project work, challenges you encountered, and your engagement with the course readings.
These consist of some short-answer and multiple-choice questions. They are graded on thoughtful completion, not on correctness. Your honest reflections are crucial, as they provide valuable feedback that will help us understand student experiences in working with GenAI and improve the course. Completing them promptly will allow us to take them into account in preparing for the following week.
Each week's writing assignments will be graded on a scale of 1-6, with a zero for an unexcused missing assignment. Any grade of 4 or less will be promptly discussed with the student. Submissions 1-3 days late will be given a 1 point penalty, 4-7 days late a 2 point penalty, more than 7 days late a 3 point penalty (penalties cannot reduce a grade to less than 1).
A draft of the submission forms for the first week learning log will be made available before class so students can understand the typical work required to complete each weeks learning log.
Graded each class based on instructor observation in the classroom during pair and group work. Graded on a scale of 0-10, with the expectation that most students will get a 10 each week. If a student doesn't attend a class, they will get a score of 0 for class participation for that week; it is not possible to submit something late to be counted for classroom participation. Excused absences are not graded and not included in the grade calculation.
Each assignment will be graded on a scale of 1-6, with a zero for an unexcused missing assignment. We will ask students to submit the code they worked on during class or after class. Grading will be based on an assessment of whether students made a good faith attempt to work on the assignment with an appropriate amount of time on task and provides context for their learning log and check-in. A good faith attempt that wasn't successful at achieving the desired functional outcomes can still get a top grade.
No A+ grades will be given. Given the design of the course, we don’t have a way to objectively identify exceptional work.