The purpose of this course is to provide a structure for you to gain A LOT of hands-on practice with programming. This means that you are responsible for taking the time, every week, and making a diligent effort to keep up with this practice.

We will meet once a week, in a 2.5h studio, to review important concepts and to do in-class activities together. Attendance at these studios is mandatory. You must come to each class ready to engage with your peers and instructor, as a member of our learning community. You must also prepare for each studio session by thoroughly reviewing the concepts covered in the previous studio. You are expected to work at least 8 hours outside of class on reviewing the material, completing weekly check-ins, and working on assignments.

It is also your responsibility to follow the course policies and keep up with the course schedule. You must submit the all the check-ins, and assignments for this course. You must attend the midterm and final exam, no travel will be excused for either exam.

Note: If you have accommodations or extenuating circumstances, please let me know in a timely manner so that we can discuss how to adapt the course for your needs.

Absences. Because we will only be meeting once a week, attendance to studio is critical for keeping up with the course. If you cannot attend a studio, I appreciate knowing ahead of class and we will work together to help you catch-up. If your attendance is frequently tardy or irregular, your participation grade will be affected.

Late submissions. You must let me know prior to the deadline if you need to submit an assignment late due to unexpected circumstances and it will not be penalized. If your late submission is not excused, you will receive 50% of your grade on the assignment.

Note: Caveats to both of these policies include situations with a documented accommodation or unexpected circumstances. Please be pro-active in communicating with me about your needs for adapting these policies.

The Wellesley College honor code applies to CS 200. This course collaborative learning and learning to work effectively within a teams. Working with a team provides you with opportunities to develop and improve interpersonal, communication, leadership, and follower-ship skills.

I strongly encourage you to get to know all of your classmates and to collaborate extensively with them in and outside of class.

Here is a summary of the collaboration policy:
In-class activities and discussion: This class requires your active contribution during our time together. Please come to class prepared and ready to contribute to our learning community. During class you will work in group using different online collaboration tools.
Assignments: No collaboration on code but you can discuss the assignments with others.
Project: Teams of 2-3 students work together to complete and submit project milestones. You will be assigned to a team.
Exams: Absolutely no collaboration.

Because every course has different goals and structures, policies for Generative AI will be different in each course you take this semester and through your college career. Something that might be permitted in this course might not be in another, or vice versa. Take a moment to read through this policy and consider how your personal purpose and goals align with the aims of this course.

As an early programming course, the usage of Generative AI usage is restrictive in this course. A core goals for this course is to provide a structure for you to gain A LOT of hands-on practice with programming. This means that you need to spend time every week to practice programming (think of it like an instrument), so that you have the chance to make every mistake in the books (and overcome them!) and gain insights into solving problems that serve as patterns to solve others. Spoiler alert: Generative AI is quite good at solving the types of programming exercises you will be asked to do in this class. Consider this: what are you hoping to gain from this course?

Simply put, the AI policy for this course can be summarized as: Use generative AI tools to help your learning, not to avoid learning.

It is an honor code violation to use Generative AI tools (ChatGPT, Copilot, Gemini, or any other) for an exam or to copy any code from a generative AI tool and submit it as your work for a check-in, assignment, or project.

If you use generative AI as part of your learning CS200, you need to be mindful about the following aspects of these tools:

• They can produce incorrect information in a very believable way (known as “hallucinations”), if you take the output of generative AI for its word you might learn incorrect information.
• They are trained on old information and might not have the most up-to-date information that we discuss in class.
• Generative AI is trained on large volumes of data from the Internet and the ethics of its usage and proper attribution to originators is a controversial topic.

Here are my recommendations for using AI tools to avoid honor code violations:

• Interact with AI tool without exchanging code. If the AI produces code for you, never hit “Copy” within your conversation with an AI assistant. Use your interaction with the AI assistant as a learning experience, then let your lab/assignment reflect your improved understanding.
• Do not have your assignment and the AI agent itself open on your device at the same time. Similar to above, use your conversation with the AI as a learning experience, then close the interaction down, open your assignment, and let your assignment reflect your revised knowledge.
• Ask generative AI to produce questions for you as you study CS200 materials. As stated above, generative AI can produce incorrect solutions so don’t rely on their answers. However, they can produce sample questions and explanations that you can engage with to dive deeper into the course content. It will probably produce reasonable answers for very basic concepts about the class material.
• Practice asking for help. If you are unsure about what to ask of a TA or instructor, you may start formulating your question with generative AI and come to the CS230 team when you have identified your knowledge gap.