Course Policies

GRADING

Participation 20% Tutorials: 30% Short Projects: 30% Final Project: 20%

PARTICIPATION

It goes without saying that active participation in discussions benefits everyone in class. This is especially true for data visualization. In the past, disagreements on the merits of design decisions have yielded some of the most interesting class sessions, and also generated ideas for projects. The class is structured to encourage sharing of student work and providing feedback to classmates.

DEVICE POLICY

Devices can only be used for class related purposes. If there are any circumstances where a student needs an exception to this rule, please notify the instructor ahead of time.

SUBMISSION OF WEEKLY ASSIGNMENTS

Tutorials

• Tutorials are assigned every 1–2 weeks and are designed to take no more than 1.5 hours to complete. They allows hands on experience with code that is addressed in class. They are cumulative and should be completed in sequence.

Short Projects

• Short projects are quick assignments designed to generate ideas for discussion. Projects vary in length and tools used. Be ready to talk about your short project each week

Submission Deadlines

• Take home assignments are to be submitted before midnight on Thursday via courseworks. The instructor will start reviewing submissions at that time.
  Each late day equals a 10% deduction
  Friday = -10%, Saturday = -20%, Sunday = -30%, Monday = -40%, Tuesday = -50% — latest day.

Completeness

• Sometimes your code will have bugs that you cannot fix on your own. In those cases, please get in touch with your TA or instructor well ahead of the due date to address the issues together. Please refer to the email policy when getting in touch.

Code commenting

• Commenting your code and attributing code you use are required as part of every programming assignment. Writing comments inline with the code helps you to think through how to best complete particular programming tasks and also helps the instructor troubleshoot with you when there are issues. If your code is not functional, comments identifying issues will be necessary to receive partial credit for an assignment.

FINAL PROJECT

• The final Project can be on a topic of your choosing
• You will work in a team of 2–3
• Your project will be an interactive visualization hosted on the web that tells a well researched data driven story visually

ACADEMIC HONESTY

Students in this course will work in accordance with the student honor code and the statement of academic integrity for Columbia University. Please refer to the Faculty Statement of Academic Integrity for all submissions of your work, and contact the instructor if you have any questions about a specific case related to the contents of this course.

For your reference, consult GSAPP’s Honor System (https://www.arch.columbia.edu/honor-

system) and Plagiarism Policy (https://www.arch.columbia.edu/plagiarism-policy).

ACADEMIC HONESTY IN CODING

Plagiarism can be a serious issue in programming courses.

In the context of this course, it is permissible to use pieces of code you find in the wild that suits your project under these circumstances:

You have checked the author’s permissions and their work is under either a creative commons, MIT, or similar license in which noncommercial use is permitted.

AND

You have included clear attributions of the code you incorporate from others as comments directly within your work. Attributions must include a sentence explaining the function of the code you have incorporated. Attributions should also include, to the extent available, the original author’s name and the URL of the original source.

NEW AND EXPERIMENTAL GUIDELINE FOR FALL 2023

AI Usage according to GSAPP guidelines:
“This course encourages students to explore using Artificial Intelligence (AI) generative or machine learning tools for course deliverables, assignments, and assessments. Any such use must be appropriately acknowledged and cited. In addition, note that the information produced by AI generative tools may be unreliable, inaccurate, biased, outdated, or copyrighted. If you find yourself uncertain about the appropriate ways and circumstances in which to employ it, please feel free to seek guidance from your instructor. Please be aware that each student is responsible for assessing the validity and applicability of any submitted AI output, and violations of this policy will be considered academic misconduct.”

In short — It is permissible to use AI assisted tools to produce code. However, all generated code must be cited clearly to reflect its source, citation must include the prompt that was used to generate the code. Most importantly, the student bears the sole responsibility for the function and logic of all lines of code they incorporate into their work regardless of source.