Instructors: Marianne Petit ( & Matthew Belanger (
TEE Fellow: Kyle Greenberg (

Course Description

Humans have an inherent impulse to collaborate and share. In this course, designed for NYU Shanghai Interactive Media Arts majors studying abroad, students will be asked to integrate a variety of collaborative processes and methodologies for sharing into their work. First, by establishing a coauthored or user-generated storytelling environment for the collection and distribution of narratives, either fiction or nonfiction. Next, students will learn to programmatically acquire and aggregate data from a variety of online sources. Official APIs for popular social media outlets will be introduced, and standard methods for data parsing as well as unofficial data scraping techniques will both be employed to create online mashups featuring content from multiple sources. Students will then propose and execute an open content / open source final project that synthesizes the concepts and techniques explored within this course. Readings and discussions will further involve students in debate over related issues, including intellectual property and open data. Students are encouraged to incorporate site specific elements into their projects, and students and their collaborators will be free to use text, audio, video, animation, and transmedia approaches within their work.

Note: This course is an online distributed course. Registration for this course is limited to IMA Majors studying at the Global Sites.

Note About This Syllabus

This syllabus is a dynamic document. Each week, links, video lectures, slide decks, and more may be added.

Learning Objectives

To develop an understanding of:

  • the fundamentals of narrative and storytelling
  • alternative, interactive, multi-modal, and transmedia storytelling forms
  • participatory models for inclusive and collective storytelling
  • the tools and techniques of extracting and understanding data that tells us stories
  • the tools and techniques for building interactive and participatory storytelling environments
  • the tools and techniques of extracting and understanding data that tells us stories
  • web page semantics and structure
  • data, data mining, and data scraping techniques using both JavaScript and Python
  • collaborative programming tools and techniques


  • 20% – Attendance & Participation
  • 15% – Responses to Readings & Viewings
  • 25% – Assignments & Documentation
  • 15% – Critique of Classmates Work
  • 25% – Final Project


This course will meet weekly online/in-person for one hour and 15 minutes every Wednesday. Attendance is mandatory. The course time is:

  • 11:00 – 12:00 UK (Dyadra, Echo, Maggie)
  • 12:00 – 13:00 Florence/Berlin/Prague (Nicholas, Nicole, Rewant, Tyler)
  • 18:00 – 19:00 Shanghai (Marianne, Matthew, Kyle)

Not all sites observe daylight saving time on the same dates. The class time is locked to the time in the UK. Keep track of local time changes as they may affect your schedule as the semester progresses.

We observe the NYU Shanghai academic calendar for holidays in this class. It is your responsibility to makeup any classes missed as a result of local holidays.

An invitation will be sent to you shortly before each class session for a video conference. Check your email and / or the Slack channel for the invitation.

Mandatory office hour appointments will also be scheduled roughly every two weeks to review your progress in the class.


Assignments should be completed with documentation posted by the day indicated so that others can review and post comments before class.

Post your documentation to the IMA Documentation Blog ( Be sure to use the Collective Methods category when posting your documentation.


Maintaining communication in an online course is essential. We may communicate through email, Skype, Slack, or by other means as necessary. Be sure to respond to messages in a timely manner. Our primary means of communication will be through Slack. Slack works best when you download the app to your computer and / or smartphone and enable notifications.

Office Hours

Office hours will be determined.


Each week there will be selected chapters from the following books:

  • Title: What We Made: Conversations on Art and Social Cooperation
    Author: Tom Finkelpearl
    Publisher: Duke University Press Books (December 19, 2012)
    Publication Date: December 19, 2012
    Sold by: Amazon Digital Services, Inc.
    Language: English
  • Title: Convergence Culture: Where Old and New Media Collide
    Author: Henry Jenkins
    Publisher: NYU Press; Revised edition (August 1, 2006)
    Publication Date: August 1, 2006
    Sold by: Amazon Digital Services, Inc.
    Language: English
    ASIN: B002GEKJ5E
  • Title: Spreadable Media: Creating Value and Meaning in a Networked Culture
    Author: Henry Jenkins
    Publisher: NYU Press (January 21, 2013)
    Publication Date: January 21, 2013
    Sold by: Amazon Digital Services, Inc.
    Language: English
    ASIN: B00B1Q88EW
  • Title: The One and the Many: Contemporary Collaborative Art in a Global Context
    Author: Grant H. Kester
    Publisher: Duke University Press Books (August 22, 2011)
    Publication Date: August 22, 2011
    Sold by: Amazon Digital Services, Inc.
    Language: English
    ASIN: B005RZD2BC
  • Title: The Art of Immersion: How the Digital Generation Is Remaking Hollywood, Madison Avenue, and the Way We Tell Stories
    Author: Frank Rose
    Publisher: W. W. Norton & Company; Reprint edition (February 28, 2011)
    Publication Date: March 5, 2012
    Sold by: Amazon Digital Services, Inc.
    Language: English
    ASIN: B004J35KQI

There will also be links to other readings and viewings as noted below.

Weekly Breakdown

  • Week 1: Welcome & Introduction (Wednesday, January 27)
  • Week 2: Oral History, Oral Traditions, Contemporary Practices, & GitHub (Wednesday, February 3)
  • Week 3: Spring Festival Holiday / No Class (Wednesday, February 10)
  • Week 4: Webpage Semantics, Data Scraping Techniques & Artoo.js (Wednesday, February 17)
  • Week 5: Museums & Tours (Wednesday, February 24)
  • Week 6: Python (Wednesday, March 2)
  • Week 7: Objects & Locations (Wednesday, March 9)
  • Week 8: Beautiful Soup (Wednesday, March 16)
  • Week 9: Interactions, Transactions, & Narrative (Wednesday, March 23)
  • Week 10: Data Mining Social Websites (Wednesday, March 30)
  • Week 11: Spring Recess / No Class (Wednesday, April 6)
  • Week 12: Storytelling Transactions (Wednesday, April 13)
  • Week 13: Regular Expressions (Wednesday, April 20)
  • Week 14: Final Project Work In Progress Presentations (Wednesday, April 27)
  • Week 15: Visualizing Data (Wednesday, May 4)
  • Week 16: Final Project Presentations (Wednesday, May 11)