Course Information (Syllabus)

Teaching Team

Instructor
Sarah Sebo (she/her/hers)
You can call me by my first name.
sarahsebo@uchicago.edu

Teaching Assistant
Lauren Wright (she/her/hers)
llwright@uchicago.edu

Class Sessions

Monday, Wednesday, Friday
9:30 - 10:20am CST
JCL 011

Course Resources

Website: https://classes.cs.uchicago.edu/archive/2024/winter/20630-1/
Canvas: https://canvas.uchicago.edu/courses/53963
Office hours:
- Sarah: Tuesdays from 4:00pm - 5:00pm in JCL 373
- Lauren: Wednesdays from 10:30am - 11:30am in JCL 379

Course Description

Robots are increasingly common in our everyday spaces: tutoring elementary students, assisting human workers in manufacturing contexts, providing museum tours, interacting with families within their homes, and helping to care for the elderly. One critical factor to the success of these robots is their ability to effectively interact with people: human-robot interactions.

This course focuses on the core concepts and cutting-edge research in the field of human-robot interaction (HRI), covering topics that include: nonverbal robot behavior, verbal robot behavior, social dynamics, norms & ethics, collaboration & learning, group interactions, applications, and future challenges of HRI. Course meetings involve students in the class leading discussions about cutting-edge peer-reviewed research HRI publications. Students also participate in a quarter-long collaborative research project, where they pursue an HRI research question that often involves conducing their own human-subjects research study where they recruit human subjects to interact with a robot.

This course is offered as a Computer Science HCI elective. The course has no prerequisites, however backgrounds in robotics or human-computer interaction is encouraged. Programming knowledge is not necessary, however, is often useful for the course project.

Learning Objectives

You will obtain a broad understanding and exposure to cutting-edge research in the field of Human-Robot Interaction through course readings and discussions of those readings.
You will cultivate analytical and critical thinking skills when evaluating research in HRI through leading class discussions and making analytical comments on the readings.
You will gain hands-on HRI research experience through the course project.

Course Communication

Course website: We will use the schedule page of the course website to organize course readings and the project page of the course website for everything regarding the project including project deliverables.
hypothes.is: We will use hypothes.is annotations for analytical comments on the course readings as well as any paper-centered discussion (e.g., questions about the readings).
Canvas: We will use Canvas to post grades.
Google Drive: We use Google Drive for discussion lead slide submissions (in this Google Drive folder) and project deliverable submissions (each project team will create one Google Drive folder that will be shared with me - sarahsebo@uchicago.edu).

Grading

20% analytical comments on the readings
10% discussion leadership & peer-reviews of readings
60% project
10% attendance/participation

This course counts as a human-computer interactions elective for PhD students and as a CMSC elective (as well as towards honors credit) for undergraduate students.

Flexibility

The course grading is flexible to the following exceptions without penalty:

2 late analytical comments (no more than 2 weeks late)
1 missed class discussions where you are not the discussion lead (please notify me in advance when possible)

If you get sick, please spend your time focusing on your recovery. Reach out to me once you are able and we will figure out how best to handle your absence and assignment grading.

Beyond this, if your circumstances require additional flexibility, please reach out to me.

Analytical Comments and Questions on the Readings

For each class meeting, we will discuss one academic research paper. In order to get the most out of class discussions, you are required to submit at least one analytical comment on each research paper by 8:30am CST the morning before class. You will make these analytical comments using the Google Chrome plugin hypothes.is and making your annotations visible within the group "CMSC20630 Winter 2024". Your analytical comment should be a minimum of 2-3 sentences in length and should showcase critical thinking about the paper, for example, your analytical comment could:

Highlight strengths or weaknesses with aspects of the methodology, assumptions, analyses, or design of the work; providing evidence for the strength/weakness
Suggest a fruitful avenue for future research by detailing an experimental study design or computational method that would continue the investigations proposed in the paper
Discuss possible implications of the findings of this paper in other application domains
Reference another academic paper that provides an interesting perspective on the assigned paper, explaining the connection between the two and the implications for the assigned paper's conclusions
Expose a possible confounding factor that could provide an alternative explanation for the authors' observations
Propose an alternative study design that would more effectively answer the authors' research questions

You may make more than one analytical comment if you wish. Additionally, if you have any questions about the content of the paper please also ask them using a hypothes.is annotation. Please feel free to also answer each others' questions and follow up on other people's comments. These hypothes.is annotations are designed to store all communications and student perspectives about the research paper in one place before the class discussion.

Additionally, if we are hosting a guest speaker in class, who will be presenting their work (that we will also have read before their presentation), you are required to submit at least one question related to the research paper by 8:30am CST the morning before class. Just like the analytical comments, you will submit your question using hypothes.is.

Peer-Reviews of the Readings

During the quarter, you will be asked to write at least 2 peer-reviews of the assigned course readings. We will request that your review takes either the perspective that the paper should be accepted for publication (FOR acceptance) or that the paper should not be accepted for publication (AGAINST acceptance). Regardless of the perspective that your review takes, your review is expected to be 0.75 - 2 pages in length and should include all of the following elements:

Header information: The paper title, year, authors as well as YOUR name.
Summary: Summarize the paper and its contributions in 1 paragraph.
Strengths: List out 3-5 strengths of the paper as it is currently written, these can be formatted as bullet points. Examples of strengths I’ve listed for papers I’ve reviewed include:
- "The paper is well written and is situated in the relevant literature."
- "The analysis of the results, especially using Bayesian statistics, is thorough and well explained."
- "The authors provide helpful information (including tables) on their methods and measures."
- "The authors chose a nice array of explanation types to investigate and also studied interesting personality dispositions that may influence human-robot trust."
- "The study design is robust, well executed, and communicated effectively."
- "The influence of human-likeness of a person's trust of and relationship with a robot is a very interesting and relevant topic to the HRI community."
Weaknesses: List out the 3-5 main weaknesses you see in the paper/work as it is currently presented. Examples of weaknesses I’ve listed for papers I’ve reviewed include:
- "The study did not yield many results, most of the hypotheses were not confirmed, and there are few takeaways of this work about the main variables of interest. It seems that to answer the authors’ research questions, a new study needs to be designed that addresses the shortcomings of the study presented in this paper."
- "The study design itself does not make the robot’s trust violations negatively impact the participant, nor does it seem to set up a situation in which repair attempts could be successful."
- "There is a potential confounding effect that could explain the results of the study, which is the robot in one condition appears more human-like than the robot in the other condition."
- "Some of the claims made by the authors about the significance of their findings seem overstated (e.g., the claim that this work is the first to demonstrate the influence of robot human-likeness on people's positive impressions of the robot). The paper needs reframing with regards to the claims it makes about its novelty."
- "The paper does not motivate the research by providing real-life examples of when robots may leverage different group characteristics, and could improve in its motivation of the concepts studied and the research questions posed."
Suggestions for Improvement: List out the main 4-6 changes you think the authors could make that would serve to make the largest improvement for the paper. Please elaborate on each of these suggestions for improvement.
Conclusion: In a few sentences, summarize your overall impressions of the paper. Praise what you believe to be the main merits and strengths of the paper and also briefly summarize the main change(s) you believe will help improve the paper.

Your peer-review must be uploaded to Canvas by 8:30am CST the morning before class. Your peer review can be in Word document or PDF format. Also, please name your peer-review file after the first author last name, the year the paper was published, the peer-review review type, and your own name (e.g. "Bainbridge_2011_review_against_Sarah_Sebo").

Discussion Leadership

During the quarter, you will be asked to lead at least 1 class discussion. You will prepare 6-ish slides that you will present in no more than 5 minutes. Here's an outline of what your slides may look like:

Slide 1: Title of the paper, authors, publication venue
Slide 2: Summary of the methods of the paper
Slide 3: Summary of the main results of the paper
Slide 4: Strengths and weaknesses of the paper
Slide 5: 2-3 Warm up questions for small group discussion
Slide 6: 5-7 Large group discussion questions

Your slides must be uploaded in PDF format to this Google Drive folder by 9:30am the day BEFORE the class when you are to lead the class discussion (24 hours in advance). Also, please make sure that your name is on the first slide and name the PDF file after the first author last name, the year the paper was published, and your own name (e.g. "Bainbridge_2011_Sarah_Sebo"). Uploading your slides 24 hours in advance of the class will allow the other students in the class to view your slides and the discussion questions, if they so choose, in order to best prepare for the class discussion.

Project

The course project is your chance to gain hands on HRI research experience. You can find more details on the project page.

Attendance/Participation

This class is designed to facilitate active and critical discussions about cutting-edge work in the field of human-robot interaction. Your attendance of class meetings and participation in these discussions is essential to get the most out of this class. Specifically you will be assessed on the following two factors:

Class attendance: You are expected to arrive on time for class and be present for all class meetings. If you arrive more than 10 minutes late for class, three such late arrivals will equate to one missed class meeting.
Discussion participation: You are expected to come to every discussion prepared and ready to engage. Your participation in these discussions will be evaluated on your ability to demonstrate critical thinking about the HRI research papers. At minimum, we expect you to verbally contribute to class discussions at least one out of every three class periods.

Late Assignments

A late assignment is one that does not provide the requested deliverable (e.g., analytical comment, project proposal, discussion lead slides) in the requested format by the stated deadline. Late assignments will be docked 10% of the total grade for each 24 hours period, up to 3 days, that they are late. After three days, the assignment will receive a zero.

The only exceptions to this policy are listed in the 'Flexibility' section above and in case of emergency. If you experience an emergency, please take care of the situation at hand, and afterwards please reach out to me so that we can discuss a best path forward.

Policies

Academic Integrity

In this course, we abide by the University of Chicago's Policy on Academic Honesty and Plagiarism. If you violate this policy (depending on the severity of the offense) you risk being dismissed from this course. All cases will be referred to the Dean of Students office, which may impose further penalties, including suspension and expulsion. If you have any questions about whether an activity or written work would constitute cheating or plagiarizing, please ask.

With respect to this course, please ensure that you appropriately cite all academic work that you paraphrase or quote. With regard to the use of large language models (LLMs), such as ChatGPT, in this course, we encourage and allow the use of LLMs to edit/improve your English writing on analytical comments on the readings and on the final project deliverables (e.g., "rephrase this sentence"). However, we do not allow the use of LLMs (including GitHub Copilot) to generate text from scratch for your analytical comments or for your final project deliverables.

Diversity, Equity, and Inclusion

I stand with the University of Chicago in my dedication to "creating an environment where people of different backgrounds feel valued and where their ideas and contributions can flourish" (see UChicago's Diversity Commitment Statement). I strive to make this classroom environment one where the diverse backgrounds and perspectives of each individual are valued and included for the benefit of us all, including gender identity, sexuality, disability, generational status, socioeconomic status, ethnicity, race, religion, national origin, and culture. I expect that all class related interactions will be conducted with mutual respect, open communication, and non-discrimination. If you have any suggestions for how we can better promote an inclusive and open environment, please reach out to me.

Accessibility

The University of Chicago and I are committed to ensuring equitable access to academic programs and services. Students with disabilities who have been approved for the use of academic accommodations by Student Disability Services (SDS) and need a reasonable accommodation(s) to participate fully in this course should follow the procedures established by SDS for using accommodations. Timely notifications are required in order to ensure that your accommodations can be implemented. Please meet with me to discuss your access needs in this class after you have completed the SDS procedures for requesting accommodations.

Phone: (773) 702-6000
Email: disabilities@uchicago.edu

Sexual Misconduct

The University of Chicago is "committed to taking necessary action to stop, prevent, and remedy instances of sexual misconduct" (see the University of Chicago's website for the Office for Sexual Misconduct Prevention and Support). Title IX prohibits discrimination on the basis of sex, including sexual assault, sexual abuse, sexual harassment, dating violence, domestic violence, and stalking. Sexual misconduct is unacceptable at the University of Chicago, including any interactions that occur related to this course.

If you would like to speak confidentially about an incident of sexual misconduct, want more information about filing a report, or have questions about school policies and procedures, please contact our Title IX Coordinator. In certain situations, the University may have an institutional obligation to respond to a report of sexual misconduct. Additionally, as a faculty member, I am required by Title IX and the University of Chicago to report incidents of sexual misconduct, even if I am requested to keep the information confidential.

Wellness

As you pursue your education, your health and overall wellbeing is extremely important. Do your best to maintain a healthy lifestyle this quarter by eating well, exercising, getting enough sleep, and taking time to relax. Despite our best efforts, all of us benefit from support at times. Asking for support when a problem is small can help keep it from growing larger, but there is no wrong time to ask for help. If you or someone you know could benefit from mental health services, I strongly recommend that you reach out to UChicago Student Wellness, whose services do not come at any additional cost to students. Additionally, If a personal emergency arises that may impact your work in this course, please alert me so that the appropriate arrangements can be made.

Acknowledgments

This course is centered around the excellent recent work in the field of Human-Robot Interaction. The policies outlined in this syllabus was informed and adapted from those of Henny Admoni, Ravi Chugh, Blase Ur, and Marshini Chetty.