This course aims to equip students with skills for critically analyzing data and data-related systems in the context of human-computer interaction (HCI) and visualization research, as well as in computer science more broadly. Via readings, projects, and discussions students will develop conceptual tools for evaluating, interpreting, and critiquing data, interfaces, and systems—critical thinking in data writ large.

Relevant questions include: what is data? How do we evaluate the quality and relevance of systems for interacting with data? What biases might be inherent in these designs? To serve this goal we will explore perspectives from critical theory, science and technology studies, and HCI/VIS research (such as Data Feminism). Students will gain experience reading, understanding, and applying ideas from other fields to problems in familiar data domains.

Learning objectives:

• Critical thinking: at the end of the course students should feel comfortable applying a variety of theoretical lenses to data and data systems.
• Communication: at the end of the course students will be able to communicate and synthesize their ideas in a variety of formats
• Theory: at the end of the course students will be able to describe the content of a variety of theoretical perspectives and apply them to data and data systems.

Mechanically, the course is essentially a scavenger hunt with a small handful of requirements (showing up to class / being a good citizen/some other minor stuff) wherein you strive to get a certain number of points by the end (25). There are a variety of different types of works that you can do to get points, such as an essay or a project. It is up to you how you decide to approach this course. (Except for the required activities, that constitutes 5 points and is not available any other way) Thus there is a more mechanical learning objective of pushing students to deal effectively with time management.

Logistics

Instructor: Andrew McNutt
Contact: andrew.mcnutt@utah.edu
Class: 2:00 PM - 3:20 PM (Tu/Th) at BU C 302 Jones Conference room in WEB Office Hours: On demand Course Forum: link
Github link: github.com/mcnuttandrew/critical-hci-vis-class

FAQ

• How do I submit stuff? use THIS LINK
• How do I hear about course updates? Check the course forum
• How do I get in touch with the course staff? Post on the course forum, do not email
• How do I propose a work? Post on the course forum (or use the github for talks/help the course)
• How do I get grades? You'll be emailed once a week

Schedule:

For each class, there will be some assigned reading that you should do before class. Classes will involve discussions of the readings, so it is important that you do the readings.

Note: this schedule is subject to change (although whatever the next reading is will always be right).

Week 1: Introduction

Tuesday (1/7): Syllabus day, introductory discussions and stakes setting. Slide

Thursday (1/9): Raw Data is an Oxymoron, Gitelman: Introduction. Data Humanism Manifesto, Lupi, When the Body Became Data: Historical Data Cultures and Anatomical Illustration, Correll and Garrison

Week 2: Data/HCI Feminism amuse

Tuesday (1/14): Data Feminism, Introduction and Power Chapter, Feminist Data Visualization

Thursday (1/16): Towards a feminist HCI methodology: social science, feminism, and HCI Bardzell + Bardzell, Visualizing Junk: Big Data Visualizations and the Need for Feminist Data Studies

Week 3: Epistemologies

Tuesday (1/21): Read Entanglements for Visualization: Changing Research Outcomes through Feminist Theory by Akbaba et al. Read Framework for externalizing implicit error by McCurdy et al. Watch talk for Data Hunches

Thursday (1/23): On Bullshit Frankfurt, Towards a theory of bullshit visualization Correll

Week 4: Meta theory in HCI/VIS

Tuesday (1/28): Generative theories of interaction Beaudouin-Lafon et. al, Designing interaction, not interfaces Beaudouin-Lafon

Thursday (1/30): The nature of theory in information systems Gregor

Week 5: Meta theory in HCI/VIS?

Tuesday (2/4): The meaning of theory Abend

Thursday (2/6): ASYNC CLASS, go to the SCI distinguished lecture! Fourth Paradigm "Jim Gray on eScience: A Transformed Scientific Method", The Three Paradigms of HCI Harrison and friends

Week 6: Meta theory

Tuesday (2/11): ASYNC CLASS, go to the RAI lecture Structure of scientific revolutions (available at the library), chapter 5 paradigms, chapter 7 theories, chapter 9 revolutions

Thursday (2/13): Traditional and Critical Theory Horkheimer

Week 7: Critical Vis

Tuesday (2/18): Critical InfoVis: exploring the politics of visualization by Dork et al. Iceberg Sensemaking: A Process Model for Critical Data Analysis and Visualization

Thursday (2/20): Ethical dimensions of visualization research Correll The work that visualisation conventions do Kennedy et al.

Week 8: Feminism Return

Tuesday (2/25): Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective Haraway, Writing the Implosion: Teaching the World One Thing at a Time by Dumit

Thursday (2/27): Data Feminism for AI

Week 9: Political Considerations

Tuesday (3/4): Human-computer insurrection: Notes on an anarchist HCI Keyes et al, A Mulching Proposal: Analysing and Improving an Algorithmic System for Turning the Elderly into High-Nutrient Slurry

Thursday (3/6): Of Course it's Political! A Critical Inquiry into Underemphasized Dimensions in Civic Text Visualization Baumer et al.

SPRING BREAK

Week 10: Assorted topics
Tuesday (3/18): Individual Conferences

Thursday (3/20): Cripping Data Visualizations: Crip Technoscience as a Critical Lens for Designing Digital Access by Hsueh and co, How accessible is my visualization? Evaluating visualization accessibility with Chartability by Elavsky and friends

Week 11: Assorted topics
Tuesday (3/25): Braving Citational Justice by Kumar and Karusala, and Post-growth Human–Computer Interaction by Sharma, Kumar, Nardi

Thursday (3/27): On Use of Theory in Computing Education Research Nelson, Ko, In defence of sandcastles : research thinking through visualization in DH by Hinrichs and friends

Week 12: STS and friends
Tuesday (4/1): Visualisation and Cognition: Drawing Things Together by Latour

Thursday (4/3): Chapters 1 and 2 of Critical Visualization by Hall/Dávila

Week 13: PL
Tuesday (4/8): Programming as Theory Building* Purbid talk

Thursday (4/10): A Case for Feminism in Programming Language Design Hermans, Schlesinger, Refeminizing Creative Computing through a Programming Language for Quilts (see ed for preprint) Bonus: Pronoun Logic by Bohrer and Neth

Week 14: Assorted Topics
Tuesday (4/15): Disentangling the Power Dynamics in Participatory Data Physicalisation by Cazacu and friends

Thursday (4/17): Purbid and Chang give talks

Week 15: Test Tuesday (4/22): Test

Mechanics

This course is populated by a collection of optional assignments. Each assignment is worth some number of points. To get additional details about different activities you might do, see below. Note that this means there is not a notion of late work in this course. All coursework must be turned in by the last day of class before finals (specifically before class starts on 4/22).

Depending on how everyone does there may be a curve. The course staff will not know what the curve is until the end of the semester.

Possible works

There are many different paths through this course. You might write responses for all of the readings, do a project, and write an essay. Or you might write 5 essays! There are many possible approaches. Other works are allowed, but you must ask ahead. Unusual approaches and welcomed and (for now) encouraged. These might include a video essay, a podcast, a poster, or something else! An appropriate way to ask would be to post on the course forum (so that others can see as well), you'll get a response. Note, that merely submitting a work is not enough to get all of the points associated with that format, it will also be graded.

Large (10 points)

Make a project! This is the most traditional form of work in this course. Here you will propose a project (at least a month in advance of your submission of that project) for which you will receive feedback and approval. The project should be a substantial piece of work that is related to the course topic.

Take a test! If you have found yourself in dire need of points a final can be arranged in order to fill up the gap. This will be a timed exam held towards the end of the course that will cover material from the course, including free response and multiple choice.

Medium (6 points)

Write an essay! Write an essay about something related to the course. Relevant topics might include a reflection on a topic relevant to your domain knowledge or research, a synthesis related to course readings (although you should anticipate bringing in outside sources as well), a critique of a system or interface using one of our tools, or another appropriate topic (feel free to ask). This should be an academic essay and so refs should be used as appropriate. Think, 2-3 pages in IEEE VIS format (like a poster abstract length).

Do a talk! Here you'll do a presentation about something related to the course during class time. You must give at least a 1 week advance notice. Some possible presentations include: a discussion of a paper we did not read during class, an analysis of a system, an argument synthesizing multiple different perspectives we've considered. As part of your request for doing a talk, please file a pull request against this page using the github.

Make a zine! Like the essay option, this should cover a topic or topics relevant to the course, but be presented in a zine-style format. The length, content, and complexity should be appropriate to being a medium work.

Write Reflectively! Across the semester keep a reflective journal. This is an opportunity to think critically about what we've been working on in class, as well as your work more generally. "Keeping and Using Reflective Journals in the Qualitative Research Process" includes an introduction to it. Here is a potential starting prompt and tutorial video. If you wish to pursue this activity, you should start at the beginning of the semester and continue through to the end; its not worth much if you do it for a week.

Small (1 points)

Draw a postcard! Make a visual representation of a paper we've read. This can be a short lightweight visual abstract or some more in-depth. Use both sides. It should be enlightening to read.

Help the course! Suggest a reading not currently covered by the syllabus. If it is sufficiently interesting, we'll bring it into the course. Credit will only given for readings that are used in the course. To help the course file an issue on the github, if you get credit I'll enter it into your submissions.

Required Activities (5 points)

Respond to the reading This is something you should be doing for everything you read anyway, so you might as well get credit. No credit for obvious AI generated responses. This is the only assignment with a deadline, it must be turned in physically in class.

Show up to class

Make a plan! This course has a very loose structure that can make it easy to get lost. Write down a plan in a markdown file of what assignments you plan to do and when. This isn't binding, but it's a good idea to have a plan.

Notes and clarifications

It is possible that you could do nothing all semester and turn a whole bunch of work at once. This is allowed, but discouraged. Much in the same way that judges supposedly give harsher verdicts before lunch, requiring that the course staff grade a huge amount of submissions during finals week will likely lead to harsher grading. There is then, a game theory component to this system: when should you submit so that the grading system is currently least overwhelmed?

Similarly, it is possible that you could not show up all semester or engage with the class discussions, that is, generally not be a good citizen of the course. There will be a negative penalty for this or similar actions: up to -12 points.

Resubmissions of previous works for new grades is allowed and encouraged. They will not increase your point total, but will allow you to increase the score on your original work. Note: all course work is graded at discretion---submitting something numerous times does not mean it will be graded numerous times.

Given the variety of different types of works, there are a variety of different types of grading that are appropriate and necessary. Undercutting these are a general policy that you should not be disappointing. There are many ways to be disappointing. For instance, using an AI to generate an essay will be looked upon extremely negatively. Depending on the specifics of the infringement this may lead into our academic honesty policy.

Collaborations are allowed depending on the work. For instance, a group project is allowed and points are not split, but submitting an interesting paper as a group is not. The course staff must be informed of the collaboration before the work is turned in. If the collaboration is not disclosed, the work will be considered a violation of the academic honesty policy.

Note that because this course structure is experimental, components of it liable to change as the utility/non-utility of them becomes more apparent. For instance, depending on student engagement reading requirements may shift from a point value into a credit gate---such that credit for any assignment is unavailable without having done all the readings. Similarly, the maximum point value may increase or decrease.

Policies

Behavior during class activities All students are expected to maintain professional behavior, according to the University of Utah Student Code. Students should read the Code carefully and know that they are responsible for the content. According to Faculty Rules and Regulations, it is the faculty's responsibility to enforce responsible classroom behaviors, beginning with verbal warnings and progressing to dismissal from class and a failing grade. Students have the right to appeal such action to the Student Behavior Committee.

Cheating is taken very seriously and students must be careful not to collaborate on assignments unless otherwise noted. Submissions are routinely checked by the course staff for signs of unauthorized collaboration. Any student found cheating will fail the entire course. We will adhere by the School of Computing policy on academic misconduct.

Note: self-plagiarism is plagiarism, turning in work completed in other courses is viewed as plagiarism. Similarly, using AI tooling for text generation is considered plagiarism.

In cases where projects involve human subjects, mistreatment of those subjects (such as by not following the tenets of the Belmont Report) will be viewed as academic misconduct.

College of Engineering guidelines For information on withdrawing from courses, appealing grades, and more, see the College of Engineering guidelines.

It is our intent that students from all diverse backgrounds and perspectives be well-served by this course, that students' learning needs be addressed both in and out of class, and that the diversity that the students bring to this class be viewed as a resource, strength and benefit. It is our intent to present materials and activities that are respectful of diversity: gender identity, sexuality, disability, age, socioeconomic status, ethnicity, race, nationality, religion, and culture.

We also expect students to treat everyone in the class (including the teaching staff) in a respectful manner.

Student names & personal pronouns Class rosters are provided to the staff with the student's legal name as well as "Preferred first name" (if previously entered by you in the Student Profile section of your CIS account). Please advise the staff of any name or pronoun changes (and update CIS) so we can help create a learning environment in which you feel respected. If you need assistance getting your preferred name on your UID card, please visit the LGBT Resource Center Room 409 in the Olpin Union Building, or email bpeacock@sa.utah.edu to schedule a time to drop by. The LGBT Resource Center hours are M-F 8am-5pm, and 8am-6pm on Tuesdays.

NOTE: This syllabus is meant to serve as an outline and guide for our course. Please note that the staff may modify it with reasonable notice to you. The staff may also modify the course schedule to accommodate the needs of our class. Any changes will be announced in class and posted on the course forum under Announcements.

Credits

This course is indebted to wide variety of people for this work, their teaching, and their thoughtful commentary. Miriah Meyer's course on a related topic of HCI paradigms was a large inspiration. derya akababa provided some very useful and inspiring commentary. The course structure draws on a course I heard about taught at Reed College by Troy Cross, but it is not impossible in the intervening years the details have telephoned their way into being something different.