Course Overview

Course Description

This course provides an introduction to several major areas of Human-Computer Interaction (HCI) research. It is based in a combination of readings and discussion, a small statistics lab, and a self-defined project.

This course is explicitly not focused on the design methods used in HCI practice. We briefly cover some of these methods near the end of the course, but our focus is on research. We do not assume a strong background in HCI (i.e., there is no undergraduate HCI prerequisite).

The course readings will require preparing reports on a combination of historic framing papers and more current results. This will help you examine what the HCI community considers a meaningful contribution across a variety of problems, thus helping prepare you to understand and make meaningful contributions in these and other areas of HCI.

The course project will require hands-on experience with HCI, while remaining open to different possibilities. You might choose to design and implement a new piece of HCI technology, or you might choose to design and execute an appropriately compelling study with HCI research implications.

We will emphasize open discussion and feedback in all aspects of the course.

Basic Information

Contact: Email all instructors at cse510-instr [at] cs.washington.edu

Class Time & Location: Tuesdays & Thursdays, 10:30-11:50, CSE 403

Office Hours: By appointment, and as scheduled for project meetings.

Course Staff:

James Fogarty

James Fogarty

Daniel Epstein

Daniel Epstein

Readings

Assigned readings will often focus on research topics, generally consisting of:

  • A historic framing paper: presenting a theory, language, or understanding that can help in understanding and contextualizing the contributions of additional research.

  • Two papers that provide more recent or specific contributions: presenting the type of contribution you might initially be expected to attempt in your research.

You are expected to read: (1) the historical framing paper, and (2) either of the more current papers (in other words, whichever seems more compelling or interesting to you). You obviously may choose to read all three. The calendar will link to assigned readings and provide any day-specific revisions to this reading structure.

You are expected to have read and considered the assigned readings prior to class, as the in-class discussions are a critical component of this course.

Reading Reports

To help prepare for an engaging and meaningful discussion, we require posting thoughts and questions beforehand. You can start a new discussion, participate in an existing discussion, or do a bit of both. You can discuss all of the assigned readings, or focus on a portion of the reading that you found most interesting. The important part is that we can see intellectual effort in your forum participation, not just a simple paper summary.

We will create Canvas discussion threads for each paper. If you have a thought or question that relates to multiple papers, post it wherever seems more appropriate.

Your participation in the forum discussion for each day will be graded on a scale from 0 to 3.

  • 0: If you do not participate.
  • 1: If your participation seems weak and does not convince us you read, understood, and considered the readings.
  • 2: If your participation shows you read and understood the readings and had something interesting to say. This will be the most common grade.
  • 3: Reserved for especially insightful participation.

It is generally easy to find something to criticize in any piece of research. But focusing exclusively on the potential flaws of research is generally not productive. You will generally find it more intellectually worthwhile to focus on aspects of work that are particularly well done, new ideas are prompted by a piece of work, or what you might have done differently if you conducted the research. This will also lead to much more valuable discussions.

Potential topics for discussion are:

  • What idea or innovation enabled this, what more might be done based on that idea or innovation?
  • What new questions or research agendas are suggested by this research?
  • How might this research have informed some other research you have seen?
  • What aspects of this work were particularly well done or effective?
  • If you had conducted this research, what would you have done differently?

As we note in Submission, reading discussion must be posted by the night before each class meeting. This ensures time to review discussion the next morning before class.

Feel free to continue a discussion after this, even after class.

Project

A course project will be a major component of your work. Details of the project are here:

https://courses.cs.washington.edu/courses/cse510/16wi/assignments/project.html

Dates are also linked from the course calendar.

Some sample project ideas, gathered from faculty and researchers, have been made available here:

https://canvas.uw.edu/courses/1021534/discussion_topics/3155256

Exam

The exam is an opportunity to demonstrate and apply your understanding of the course material in a more substantial format. It requires you to connect concepts across papers, serving as an evaluation of your understanding and critical thinking about concepts covered in this course. If you have kept pace with the readings, you will find it much easier to approach this exam (e.g., simply referring back to readings, rather than needing to understand them from scratch). You may reference any of the articles, slides, notes, discussion posts, or other material readily available on the web. You may consult the course staff with any questions, but this is strictly an individual assignment (i.e., do not discuss it with others).

Download

The exam is available for download:

https://courses.cs.washington.edu/courses/cse510/16wi/assignments/finalexam.pdf

Submission

Due: Uploaded by end of day Thursday, March 10, 2016.

Statistics Lab

To aid in developing the necessary skills, you will complete a statistics lab in either JMP or R. The lab will walk you through analyzing an example data set, and you will then analyze two datasets from published research papers.

You will gain basic familiarity with analyzing experiments using mixed‑model analyses of variance. Consistent with lecture, this assignment is not intended to provide complete knowledge of how to design or analyze experiments, which is far beyond the scope of one lecture or assignment. This assignment is instead focused on a pragmatic introduction to analyzing experiments based in designs you might later find useful. Please consider this assignment in the context of the material covered in lecture, as not all of it is repeated here.

In addition to the lecture material and the contents of this assignment, you might benefit from working through the first four sections of Jacob Wobbrock’s independent in Practical Statistics for Human-Computer Interaction.

http://depts.washington.edu/aimgroup/proj/ps4hci/

Download

The assignment is available for download:

https://courses.cs.washington.edu/courses/cse510/16wi/assignments/statisticslab.zip

Submission

Due: Uploaded before class Tuesday, February 9, 2016.

Submit a ZIP archive including your document in PDF format and any additional files:

https://canvas.uw.edu/courses/1021534/assignments/3143422

Submit your time journal and assignment feedback:

https://canvas.uw.edu/courses/1021534/quizzes/880792

Grading

Grading will roughly correspond to:

  • 20%: Readings
  • 45%: Group Project
  • 15%: Exam
  • 10%: Statistics Lab
  • 10%: Participation

Much of the grading in this course is necessarily subjective. We will attempt to communicate expectations and feedback throughout the course, but it is your responsibility to communicate with us if you feel you would like guidance in this regard.

Submission

Submissions will be coordinated using Canvas:

https://canvas.uw.edu/courses/1021534/

Many assignments are due “the night before class”. We will implement this in Canvas as 4:00am the day of class.

This gives staff time to review submissions before class. Submitting the day of class, just before class, or in class is therefore unacceptable, risking zero credit.

Contributing

This course website lives on GitHub:

https://github.com/uwcse510/web-cse510-wi16

You can submit pull requests to update the website. Instructions for building the site are available here:

https://courses.cs.washington.edu/courses/cse510/16wi/development/