This course provides an introduction to human-computer interaction and the design process. Students will learn methods and skills for designing and prototyping interactive systems. The course covers a design process from the initial formulation of a design problem to creation of digital prototypes. The course structure is a mix of lectures, classroom activities, and design critiques by peers and course staff. The course is overwhelmingly organized around a group project, in which students:
Class Time & Location:
Check the calendar for non-standard times or locations.
Section Times & Locations:
Check the calendar for non-standard times, locations, or staffing.
Scheduled office hours require that you email beforehand (i.e., at least one hour beforehand). If nobody has emailed regarding the office hour, staff may not be present. Hours are scheduled most weeks, but check the calendar. Other meetings are by appointment.
As a focus for Winter 2019, we will ask students to explore self-tracking and everyday interaction with personal intelligences.
People have long sought to better understand themselves, but continuing technology advances enable new approaches. Students will examine problems people encounter in gathering and gaining value from personal data, then explore how a combination of design and machine intelligence can help go beyond simple data fetishes to help people in using personal data as part of reaching their goals.
Understanding and designing for self-tracking is also known as personal informatics:
Personal informatics systems are systems that help people collect personally relevant information for the purpose of self-reflection and gaining self-knowledge.
Self-tracking and personal informatics are related to the
Self-knowledge through numbers.
Instead of limiting self-tracking to dashboards for an isolated self-analyst, we will ask students to consider the many different ways people might gather and interact with personal data, together with how machine intelligence might add meaningful value to these activities.
Tracking can therefore take many mobile forms:
Tracking can include many social contexts:
Tracking can explore new forms of interaction:
Any problem where people gather or seek value in personal data introduces opportunities and challenges in designing for effective interaction around that data. It can also present opportunities and challenges in how integrated machine intelligence can provide meaningful value to that individual.
Projects are organized around four assignments, each consisting of several milestones:
Sample projects from prior offerings include:
Note that details of assignments may have changed since prior offerings, so their reports may not map to the current project. Also note these samples are intended to illustrate a variety of approaches, none of which is intended to be ideal or exemplary. Be sure to understand and carefully consider project requirements and feedback from the course staff in the context of your own work.
A small set of readings are assigned throughout the quarter, with additional resources also made available.
Strive to do good work because you care about your own opportunities to learn, including the opportunities this course provides in working with a group in an intensive project.
The overall course grade will be computed as follows:
Each assignment will also provide a point breakdown intended to convey how it will be graded. Design is an inherently subjective practice, and so grading in this course is necessarily subjective. The stated project requirements are the minimum, leaving room for groups to wow us with your work.
Because the course is designed around feedback on project milestones, grades given to those milestones indicate that you have invested sufficient effort and insight at the time of the milestone. You will get feedback and are expected to continue acting upon that feedback in your design process. The bulk of project grades is therefore attached to the final deliverables, which are evaluated on their quality.
We expect groups to take collective responsibility and to resolve any coordination issues. The course staff is always happy to make suggestions with regard to your effort and coordination. If an issue needs to be raised with the course staff, we expect it to be raised early enough to be addressed. If necessary, we reserve the ability to adjust an individual's grade with regard to the group project.
Many assignments are due "the night before class". We will implement this in Canvas as 11:59pm. In order to be prepared to give you feedback, the course staff must have your submission in the morning. Submitting the day of class, just before class, or in class is therefore unacceptable, risking zero credit.
Submissions should be in PDF format (i.e., not plain text, not Word). The PDF should be printable, containing everything we need to review and grade the assignment (e.g., your name). The course staff has a large number of submissions to manage, so format and completeness issues are problematic.
This course website lives on GitHub:
You can submit pull requests to update the webpage, and you will publish project webpages via pull request.