Passcode: 561538

PRELIMINARY COURSE SYLLABUS

CS 6961: Personal Informatics

Spring 2021

Course Description

Personal informatics systems help people collect and use personally relevant information for the purpose of personal benefit, for example self-reflection and gaining self-knowledge. These systems are increasingly ubiquitous, supporting goals such as self-improvement (e.g., weight loss, increased exercise, improved productivity), satisfying curiosity (e.g., seeing spending patterns or places visited visualized), discovering new content (e.g., music or movie tracking to feed a recommender system), connecting with friends, or simply for keeping a record for the future.

Computing is expanding our ability to collect and process data about our everyday lives. These advances create new challenges for collecting, integrating, sharing, reflecting, and acting on large amounts of personal data. The tools for these activities must also fit into the everyday lives and routines of the people that use them.

This semester, we will review progress and discuss current frontiers in each of these challenges. We will cover methods for knowing more about yourself through using technology to track different types of data and how to interpret them, and run controlled experiments on yourself. We will learn about self-reflection and visualization, experimental design, time-series analysis and apply them to domains of location, sleep, activity, time spent, health and wellness. We will consider what it takes to provide broad access to personal informatics for users from diverse backgrounds, including varying technical experience, levels of disability, and other characteristics.

We will pursue these topics through independent reading, assignments, class discussion, and a semester-long self-tracking and experimentation project. Students should already be comfortable working programmatically with data, and preferably taken a course in: data science, machine learning, user interfaces, or probability/statistics. Personal informatics necessarily relies on a multi-disciplinary and user-centric perspective. All students should be comfortable with human-centered computing and user-centered design concepts, and should have taken 3540/6540.

In contrast to the highly-curated presentation of content in a more introductory course, students will be expected to contribute to all aspects of the definition and content of this course. This will include identifying relevant content and contributing to discussion of that content.

Readings

Assigned readings will explore many dimensions of personal informatics. In-class discussion is a critical component of this course. To maximize the quality and effectiveness of that discussion, every participant is expected to read the assigned readings before class. This will typically mean one to two full-length research papers per class.

Any set of readings is inherently incomplete, and part of the value of this course is assembling diverse perspectives on personal informatics. We will therefore encourage posting of additional resources, including additional resources that participants surface in the course of discussion.

Reading queries

To help facilitate useful in-class discussion, you are expected to post at least one question or comment on the topic discussed to Teams by midnight the day before. Simply criticizing the details of research often leads to an underwhelming discussion. We encourage participants to draw upon their backgrounds to surface more interesting potential discussions. Potential topics for discussion might be inspired by considering:

• What new questions or research agendas are suggested by this research?
• How might this research have informed some other research you have seen?
• If you had conducted this research, what would you have done differently?

Importantly, we do not want to have the discussion on Teams. The goal of surfacing potential discussion topics is to then have the actual discussion in-class.

All of your classmates will have read the paper, so do not simply post a summary of the paper. Participants are expected to post one potential discussion topic per day, not necessarily one per paper. Participants are welcome and encourage to submit multiple potential topics, but this is not expected.

Reading queries will be graded on a binary scale.

• 0: If you did not participate according to the directions above.
• 1: If you did participate according to the directions above.

You may miss up to one reading query without penalty.

Reading queries are due at 11:59pm the night before each class meeting. This ensures time the next day to review questions before class. Submitting the day of class, just before class, or in class is therefore unacceptable, risking zero credit. But feel free to continue a discussion after this, even after class.

Reading presentations

One participant will sign up to present the day's assigned readings. Discussion of each reading will begin with this presentation. Unless advised otherwise, presentation should focus on the context of an assigned reading. This might include:

• Information about the researchers involved in the work.
• Key research that preceded or informed the assigned reading.
• Key research that followed or was informed by the assigned reading.
• A contrast between the assigned reading and other contemporary alternatives.

All of your classmates will have read the paper, so do not simply present a summary of the paper.

We welcome and encourage you to seek guidance or feedback on your overall approach to the presentation. It is probably not time effective to seek feedback on detailed minutia of your presentation. For calibration, we expect students to spend 60 to 90 minutes researching the context of a paper. We then expect presentations will be 5 to 10 minutes.

As part of preparation, the presenter should share any additional resources or slides they create.

In-class time

Class will generally be a mix of reading presentations, discussion, and mini-presentations of assignment results. In-class time aims to be interactive and participatory.

Course Communication

We will use Teams for sharing content and posting comments about readings, and the only written handin will be one assignment writeup (A0). Reading comments should be interesting things you noticed in the reading that you'd like us to talk about in class. The assignments will be opportunities for you to do something fun with your own data, and you will share the findings in short (<5 minute) "show and tells" in class.

Course communication will be over email and Teams. I will send course announcements over Canvas Announcements when necessary, but DO NOT send me direct messages in Canvas. Rather, send me an email (jason.wiese@utah.edu) with "[PI-CLASS]" in the beginning of the subject line.

Course Time and Location

Location: Zoom
Time: 3:00-4:20pm on Mondays and Wednesdays

Final Presentations Monday May 3 3:30-5:30

Instructor

Jason Wiese, wiese@cs.utah.edu
Office hours: Mondays 1-2: https://utah.zoom.us/j/97560457346

Schedule

See the Schedule page

Assignments

Semester-long self-tracking assignment "You vs You" - A hypothesis-driven self-experiment study you perform on yourself

TBD

Important things to know

Collaboration policy: if you use something (code, an idea, text, etc.) that you didn't come up with yourself, cite it!

Pay attention during class. Recognize that it's even easier to get distracted or stop paying attention on Zoom than it is in person.

The late policy is: Extensions will not be routinely granted, but can be requested with a reasonable explanation. If you are asked to present your assignment to the class and are unable to do so (i.e. the assignment is due on Monday, but you ask to wait until Wednesday to present) you will lose 10% of your grade on that assignment.

Moderating: everyone should moderate 1 discussion, which involves leading the discussion (short summary and open with questions) and contextualizing the backstory for the paper, and giving an idea of what has happened on the topic since the paper was published (e.g. who cited it).

Reading comments: you should make substantive comments for each reading on Teams (adding to the discussion).

Getting help: Help with technical parts of the assignment will be limited: I assume that you have reviewed the expectations for the course and have determined whether or not you have the requisite skills. Use each other as a resource: post questions on slack and talk to your classmates, but don't simply copy code from each other.

Grading

• 5% Moderating - Leading reading discussions in class
• 20% Readings - Reading comments on Teams
• 10% participating in class
• 25% Semester-Long Self-Tracking Assignment
• 40% Assignments

Most 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 would like guidance in this regard.

Attribution

This course is based on materials from Jeff Huang (Links to an external site.)'s Personal Informatics Seminar (Links to an external site.) course and Daniel Epstein's Personal Informatics course. Many thanks to both of them.

College of Engineering Guidelines and Policies