• Instructor: Professor Alex Godwin
  • Email: godwin@american.edu
  • Website: Alex Godwin Website
  • Office: DMTI 112C
  • Office Hours: Tue/Wed/Fri: 11:30am-12:30pm. Zoom meetings are also available on request during these hours.

Coronavirus Policies

VACCINES For fall 2021, AU will require vaccines for all students who reside on campus or come to campus for any reason. This will enable us to expand activities and interactions that enrich the educational, research, and social experiences that are fundamental to AU. Students will be able to request exceptions for medical or religious reasons following existing protocols. We are also working to support international students who may require access to vaccines when they arrive in the United States. Please see Vaccine Requirement FAQs.

Academic Integrity

Sharing code on individual assignments or between groups on group assignments is strictly forbidden - this is a form of plagiarism. There is rarely one single correct way to write code that solves a problem. While we want you to feel free to discuss your approach with your classmates, you should know that there are often many solutions for a given problem, and it’s typically obvious when one student shares code with another. If you directly copy and paste code from the Internet (or even the text), cite your source in your comments (but also ensure that you understand what the code is doing - not all code on the web is good!). Assignments will be checked using plagiarism detection software and by hand to ensure the originality of the work.

Do not share your code with anyone other than a partner on group assignments. Do not show or share your work with other students, even just for a second. Do not let someone look at your screen. You may get behind, or your friend may ask for help, but the consequences for plagiarism are far worse than an incomplete submission - for the submission, you will still likely get some points. If I suspect that you have purposely shared code with another student or presented someone else’s work as your own, the matter will be referred to the CAS Academic Integrity Code Administrator for adjudication. If you are found responsible for an academic integrity violation, sanctions can include a failing grade for the course, suspension for one or more academic terms, dismissal from the university, or other measures as deemed appropriate by the Dean.

All students are expected to adhere to the American University Honor Code. Any questions regarding general rules and regulations should first be directed to the American University Catalog. If you still have questions, please seek out the TA or Instructor during the posted office hours.

All students are expected to adhere to the American University Honor Code.

Class Participation

It is expected that students will come to class, be prepared by doing the readings, and will pay attention and participate in discussions. Participation is scored by evaluation of in-class activities that you will submit at the end of most classes.

Any questions regarding general rules and regulations should first be directed to the American University Catalog. If you still have questions, please seek out the TA or Instructor during the posted office hours.

Use of Computers and Cell Phones in Class

Educational research shows that taking notes by hand on paper will lead to better retention of material than taking notes by typing. Also, in the past classrooms have had issues with students not only not paying attention but also disrupting others during class - by playing games, by accidentally clicking on a video with the sound on, etc.

Please do not use your cell phone in class. If you have gotten this far in reading the syllabus, then Snoop and I applaud you. Obviously, the language in the above section does not apply as much in remote learning as it does in the classroom. Still, it is good advice - many of the lectures are intended to be interactive, even online, and if you are casually ignoring the prof in a background tab you may miss something interesting.

ChatGPT and AI-Generated Writing Models

In this course, solutions to coding exercises generated by AI-Generated writing models like ChatGPT are considered academic plagiarism, and will be referred to the Academic Integrity Office of American University just as if you had copied the work of a friend, website, or online tutor. While we encourage you to create an OpenAI account and play around with this and other AI-Generated tools, you should not use it to generate complete solutions to the homework problems in this course that you submit as your own work. It is reasonable to expect that tools like this will eventually be integrated into the workflows of many businesses in the future, however, while you are still learning the fundamentals of computer science the process of designing algorithms and writing code is just as important as the final product. You will be instructed early in the course how to document that process in a way that provides evidence that your work is your own.

Audio/Camera Policy

We strongly encourage you to turn on your camera during lectures, labs, and office hours if conducted online. Faculty and students reported virtual classes are much better when we can see your faces because there is more visual communication, more engagement, sense of community and less multitasking. However, we understand you can’t always turn on your camera due to connectivity issues or privacy concerns. If you can’t connect with a camera, please upload a photo of yourself onto Zoom. If you have connectivity issues, please contact techtaskforce@american.edu.

Homework

Homework will be graded on a rubric of requirements that are expected to work correctly (e.g., returning the correct output for a given input). For most requirements, you will receive either a check plus, check, or check minus. Most tasks will receive a check. A check plus means “you impressed me”, and is typically achieved by checking for faulty input, elegant design, good comments, and/or a surprising approach. A check minus means the assignment is incomplete, incorrect, or sloppy in some way. Pluses and minuses are combined to give your grade for the assignment. A project receiving all check pluses will receive 100% of credit, while a project receiving all checks will receive a 90%. A project receiving minuses for all tasks will receive about 70% of credit, and a project that receives an X for all tasks will receive about 50% of credit or less. Tasks may be weighted differently to account for differences in difficulty or time. These are general guidelines to let you know what to expect. Grading on specific assignments may differ.

For more information, refer to the assignments section of this site.

Late Submission

Assignments are due at the beginning of class on the specified date unless stated otherwise. Assignments turned in after this time will be penalized with a letter grade (10%) for each 24-hour period after the initial deadline. Submissions received 72 hours after the deadline will be accepted but can receive no more that 70% of the available course credit. Any program features that are incomplete and do not execute during runtime will not receive full credit. Some projects are larger than the others, and many are quite larger than homework assigned in the previous course. Students are therefore given multiple weeks to complete them. Waiting until the last minute is a recipe for disaster - if you are stuck, come to office hours for the instructor or TA ASAP to get unstuck!

Attendance

Students must attend all lectures. Not attending the discussion sessions and/or not reading the assigned material will negatively affect your ability to do well in this course. Prolonged absences must be discussed with the instructor and are not guaranteed to be excused.

Grading

  • Assignments: 35%
  • Quizzes: 10%
  • Peer Reviews: 10%
  • Attendance and Participation: 10%
  • Final Project: 35%

Letter Grades

  • A [93, 100]
  • A- [90, 93)
  • B+ [87, 90)
  • B [83, 87)
  • B- [80, 83)
  • C+ [77, 80)
  • C [73, 77)
  • C- [70, 73)
  • D+ [67, 70)
  • D [63, 67)
  • D- [60, 63)
  • F [0, 60)

Students with Disabilities

If you wish to receive accommodations for a disability, please notify me with a letter from the Academic Support and Access Center. As accommodations are not retroactive, timely notification at the beginning of the semester, if possible, is strongly recommended. To register with a disability or for questions about disability accommodations, contact the Academic Support and Access Center at 202-885-3360 or asac@american.edu, or drop by the ASAC in MGC 243.

Academic Support

All students may take advantage of the Academic Support and Access Center (ASAC) for individual academic skills counseling, workshops, Tutoring, peer tutor referrals, and Supplemental Instruction. The ASAC is located in Mary Graydon Center 243. Additional academic support resources available at AU include the Bender Library, the Writing Center ( located in the Library), the Math Lab (located in Don Meyers Technology and Innovation Building), and the Center for Language Exploration, Acquisition, & Research (CLEAR) in Anderson Hall. A more complete list of campus-wide resources is available in the ASAC.

Tutoring

The Peer-Assisted Student Support (PASS) Program offers free, online tutoring in CSC-208. The PASS Program also provides tutoring in 20+ courses to students enrolled at AU in computer science, accounting, biology, chemistry, and several other academic disciplines.

For more information, visit the Peer-Assisted Student Support resources page online. To view the tutoring schedule, see supported courses, and to meet with PASS Tutors, please visit WCOnline.

Acknowledgments

Course design by Alex Godwin at American University. Assignments and ideas on this syllabus build from the work of many other instructors in information visualization, especially John Stasko at the Georgia Institute of Technology, Tamara Munzner at The University of British Columbia, and Hanspeter Pfister at Harvard University. This course utilizes in-class design materials that builds on the work of Jonathan C. Roberts at Bangor University and Eva Brandt at The Royal Danish Academy of Fine Arts. Finally, many thanks to the University of Washington Interactive Data Lab for the Observable notebooks that are used as readings in this course.