Policies

Communication

If you wish to ask content-related questions in writing, please do not do so via e-mail. Instead, please use the course discussion forum Ed Discussion. That way all members of the teaching team can see your question, and all students can benefit from the ensuing discussion. You are also encouraged to answer one another’s questions.

If you have questions about personal matters that may not be appropriate for the public course forum (e.g. illness, accommodations, etc), then please e-mail the instructor directly (john.zito@duke.edu).

Note

You can ask questions anonymously on Ed. The teaching team will still know your identity, but your peers will not.

Late work and extensions

No late work will be accepted for application exercises, exams, or projects. Labs may be submitted up to 3 days late. A 5% deduction will be applied for each 24-hour period during which the assignment is late.

If circumstances prevent you from completing a lab by the stated due date, you may email the course coordinator, Dr. Mary Knox, before the deadline to waive the late penalty. In your email, you only need to request the waiver; you do not need to provide an explanation. This waiver may only be used once a semester, so only use it for a truly extenuating circumstance.

If circumstances have a longer-term impact on your academic performance, please let your academic dean know. They can be a resource. Please let me know if you need help contacting your academic dean.

Regrade requests

If you receive a graded assignment back, and you believe that some part of it was graded incorrectly, you may dispute the grade by submitting a regrade request in Gradescope. Note the following:

  • You have one week after you receive a grade to submit a regrade request;
  • You should submit separate regrade requests for each question you wish to dispute, not a single catch-all request;
  • Requests will be considered if there was an error in the grade calculation or if a correct answer was mistakenly marked as incorrect;
  • Requests to dispute the number of points deducted for an incorrect response will not be considered;
  • Regrade requests are not a mechanism for asking for clarification on feedback. Those questions should be brought to office hours;
  • No grades will be changed after the final exam has been administered on Tuesday, April 29;
Warning

If you submit a regrade request for part of an assignment, we reserve the right to regrade the entire assignment. As such, a regrade request can result in your grade going up, staying the same, or going down if we determine that, in fact, the original grader was too lenient.

Attendance

We are not tracking attendance, but success in this class and regular attendance are probably highly positively correlated. Furthermore, regular lecture attendance is necessary if you wish to earn full credit for the application exercises. Lastly, some components of the final project require you to complete activities with your teammates during lab. If you do not attend, you will forfeit these points.

Accommodations

If you need accommodations for this class, you will need to register with the Student Disability Access Office (SDAO) and provide them with documentation related to your needs. SDAO will work with you to determine what accommodations are appropriate for your situation. Please note that accommodations are not retroactive and disability accommodations cannot be provided until a Faculty Accommodation Letter has been given to me. Please contact SDAO for more information: sdao@duke.edu or access.duke.edu.

Collaboration

Only work that is clearly assigned as teamwork should be completed collaboratively.

  • You may discuss lab assignments with other students; however, you may not directly share (or copy) code or write-up with other students. For team assignments, you may collaborate freely within your team. You may discuss the assignment with other teams; however, you may not directly share (or copy) code or write-up with another team. Unauthorized sharing (or copying) of the code or write-up will be considered a violation for all students involved.
  • You may not discuss or otherwise work with others on the exams. Unauthorized collaboration or using unauthorized materials will be considered a violation for all students involved. More details will be given closer to the exam date.
  • Collaboration within teams is not only allowed but encouraged for the project. Communication between teams at a high level is also allowed; however, you may not share code or project components across teams.
  • On individual assignments, you may not directly share work (including code) with another student in this class; on team assignments, you may not directly share work (including code) with another team.

Use of outside resources, including AI

You may make use of any online resources (e.g. StackOverflow) but you must explicitly cite where you obtained any code you directly use (or use as inspiration). Any recycled code that is discovered and is not explicitly cited will be treated as plagiarism.

You should treat generative AI, such as ChatGPT, like other online resources. Two guiding principles govern how to use AI in this course:

  1. Cognitive dimension: Working with AI should not reduce your thinking ability. We will practice using AI to facilitate—rather than hinder—learning.

  2. Ethical dimension: Students using AI should be transparent about their use and ensure it aligns with academic integrity.

  • AI tools for code: You may use the technology for coding examples on assignments; if you do so, you must explicitly cite where you obtained the code. Any recycled code that is discovered and is not explicitly cited will be treated as plagiarism. Furthermore, you should not directly copy-paste the prompt from an assignment into the chat.

  • AI tools for narrative: Unless instructed otherwise, you may not use generative AI to generate a narrative that you then copy-paste verbatim into an assignment or edit and then insert into your assignment.

In general, you may use generative AI as a resource as you complete assignments but not to answer the exercises for you. You are ultimately responsible for the work you turn in; it should reflect your understanding of the course content. Identifying AI-generated content is fairly straightforward. Any code identified as AI-generated but not cited as such and any narrative identified as AI-generated will be considered plagiarism and treated as such.

Citing an LLM like ChatGPT

Here are some general guidelines for citing AI-generated content. In this class, if you use something like ChatGPT to help you, you need to cite that by providing a direct link to the conversation you had with the bot, like this: https://chatgpt.com/share/677c4060-1d58-8008-8e47-5caa5556a825. You can generate such a link here:

Academic honesty

As a student in this course, you have agreed to uphold the Duke Community Standard and the practices specific to this course.

Any violations in academic honesty standards as outlined in the Duke Community Standard and those specific to this course will automatically results in a zero for the relevant portion or the entire assignment, and will be reported to the Office of Student Conduct & Community Standards for further action. Furthermore:

  • If a conduct violation results in a zero on a lab, that zero will not be dropped;
  • If a conduct violation results in a zero on the in-class portion of a midterm, that zero will not be replaced with your final exam score;
  • If a conduct violation of any kind is discovered on any part of an exam, your final letter grade will be permanently reduced (A- down to B+, B+ down to B, etc);
  • If we discover that students are sharing and copying assignment solutions, all students involved will be penalized equally, the sharer the same as the recipient.