Course Description

This graduate seminar equips students with the major animating theories of human-computer interaction, and connects those theories to modern innovations. We will examine foundational work in design, social computing, ubiquitous computing, cognition, and human-centered AI. We will consider how these foundations have in turn led to research advances in virtual/augmented reality, automated design tools, accessibility and collaborative support. Unlike CIS4120/5120, this course will primarily be focused on conceptual understanding rather than implementation and design practice.

Intended Audience: PhD students in computer science and other related fields; select advanced Master’s and undergraduate students.

Prerequisites: Some familiarity with computing; academic maturity for participation in a graduate-level seminar. (Programming is not a prerequisite for the course.)

Logistics

Schedule: Tuesday/Thursday, 1:45 PM - 3:15 PM

Location: Towne 327

Office Hours: By appointment (email)

Attendance: We expect attendance and active participation. Discussion is important; it is how we probe and deepen our understandings of this material. Lectures are not recorded. All students can miss up to two lectures for any reason (e.g., illness, interviews, conflicts) without penalty. Any missed beyond two will count against the attendance and participation grade. If you have exhausted your two freebies and are experiencing extenuating circumstances that will cause you to miss additional lectures, email your Head TA and we will work out an individual plan. Full credit for attendance requires that you arrive on time, before lecture starts. Full credit also requires that you be actively engaged, not simply present.

Course Staff

Instructor: Andrew Head (head@seas.upenn.edu)

Instructor: Danaé Metaxa (metaxa@upenn.edu)

Head TA: Jeff Tao (jefftao@seas.upenn.edu)

TA: Ro Encarnación (rone@seas.upenn.edu)

Generative AI Usage Policy

In this course, use of AI is strictly regulated. Reading responses must reflect your own human, complete, deep reading of the material. You must read all assigned readings in full yourself in full, you must write all responses yourself, and your responses must reflect opinions and arguments that are fully your own creation.

AI use will not be tolerated if it impacts your complete and deep reading and written reflection, which provides the basis for learning in this course.

That said, outside of these restrictions, AI use is permitted. For instance, we allow it as a study aide (e.g., using it as a question generator for quizzes). If there are other contexts in which you think AI could support the learning that happens in the class, ask the instructors and we are happy to help you navigate a path that helps you get the most you can out of the class.

Grading

Readings & Commentaries (30%)

Students should submit a short commentary for each individual reading on Canvas. Commentaries will be graded on a check-minus/check/check-plus scale. These scores correspond to B, A, and A+ respectively. We will automatically drop the four lowest commentary grades at the end of class: meaning, you may drop four readings’ (not four days’) worth of commentaries. You may pass for any reason (e.g., personal or family matters, conflicting deadlines). There are no exemptions beyond this.

Quizzes (40%)

There will be five in-class quizzes, about once every three weeks, worth 10% each. All quizzes will be closed-note. They will ask you to recognize and apply concepts from lecture. Each quiz will cover content spanning from the lecture day of the previous quiz up until, but not including, the current quiz’s day. For example, if Quiz 1 were held on Thursday of Week 4, it would cover the first lecture of Week 1 through the first lecture of Week 4.

Final Exam: May 7, 12:00 PM - 2:00 PM, Towne 303 (20%)

There will be an in-person, closed-notes final exam. The exam format will be similar to the quizzes, but will cover topics from the entire semester.

Presentation (5%)

The final two lectures are reserved for student presentations. You will be asked to present a brief (5-10min) presentation on an HCI topic that resonates with you. Further logistical details TBD.

Participation (5%)

Class participation grades are based on productive contribution to classroom discussions.