Gita Johar
(gvj1[at]gsb.columbia.edu), Business/Consumer Behavior Adam Royalty
(adam.royalty[at]columbia.edu), Process Design Erik Olesund
(erik.olesund[at]nytimes.com), User Experience
TAs
Alice Lassman (al4379)
Eric Park (sp3770)
Kevin Zhang (kyz2005)
Cross-disciplinary project-based course where teams of students from various departments work together on creating products or services to address important social problems. We will introduce and study a diverse set of ethnographic, psychological, and data science tools to help students generate customer insights, and build and test prototypes for a large-scale social challenge. Student projects will be closely guided by the instructors and domain experts The final deliverables will be shared with the domain expert to determine potential application of the concepts beyond the course. This could include advancing ideas through the formation of a startup, incorporating ideas into the domain expert’s work, or establishing partnerships with organizations working on similar challenges.
Recommended Background
Familiarity with design thinking principles (eg. IEME E4200 or IEOR 4562 or INAF U6126) Introductory programming in Python
Assessment
Class participation/preparedness (individual): 20 points
Assignments (individual and group): 80 points
- Depth interview and insights (individual) 15 points
- Text mining and insights (individual) 15 points
- Surveys and insights (individual) 15 points
- Final project submission (group) 25 points
- Final project pitch presentation (group) 10 points
Tentative Schedule
09/08 (Week 1)
Course introduction and presentation of the challenge by the content expert. Fundamentals of Design Thinking and Data Science.
09/15 (Week 2)
Introduction to data sources and mining. Basics of data collection, scraping and analysis techniques. (Nakul)
09/22 (Week 3)
Fundamentals of design thinking and principles (Adam)
09/29 (Week 4)
Techniques for understanding human behavior and market reserach: interviewing, observation and market analysis (Gita)
10/06 (Week 5)
Checkpoint #1: group meetings and progress analysis
10/13 (Week 6)
Analysis via ML techniques. Advanced data analysis and text mining techniques (Nakul)
10/20 (Week 7)
Analysis via ML techniques. Advanced data analysis and text mining techniques, contd. (Nakul)
10/27 (Week 8)
Analysis of interview and observation data. Advanced design principles and insight generation (Adam)
11/03 (Week 9)
Ideation using brainstorming and creativity templates (Adam/Gita)
11/10 (Week 10)
Checkpoint #2: detailed one-on-one meetings with the teams
11/17 (Week 11)
Physical and/or digital prototyping. Introduction to Makerspace and Figma (Adam/Erik)
12/01 (Week 12)
Prototype testing and finalizing (Adam/Gita/Nakul)
Students are expected to adhere to the Academic Honesty policy of the Computer Science Department, this policy can be found in full here.
Violations
Violation of any portion of these policies will result in a penalty to be assessed at the instructor's discretion. This may include receiving a zero grade for the assignment in question and a failing grade for the whole course, even for the first infraction.