Course Information (Syllabus)

Course Information

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Course Resources

• Course website: https://people.eecs.ku.edu/~s299s471/eecs690_hri_fa_2026/
• Canvas: canvas.ku.edu/courses/204418 (submit peer-reviews and project deliverables; view grades)
• SharePoint: Discussion lead slide submissions (in this SharePoint folder).

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, design, collaboration & learning, and ethics & morality. In class meetings, students lead discussions about cutting-edge peer-reviewed research HRI publications. In weekly labs, students engage in hands-on activities to learn the essential skills of human-robot interaction research, including experiment design, robot programming, and data analysis techniques. Students also participate in a semester-long collaborative research project, where they pursue an HRI research question that involves conducting their own human-subjects research study where they recruit human subjects to interact with a robot.

Catalog description: Arranged as needed to present appropriate material to groups of students. May be repeated for additional credit. Prerequisite: Varies by topic, plus Upper-level EECS eligibility and consent of instructor.

Learning Outcomes

1. You will obtain a broad understanding and exposure to cutting-edge research in the field of Human-Robot Interaction through course readings and participating in discussions of those readings.
2. You will cultivate analytical and critical thinking skills when evaluating research in HRI through leading class discussions, making analytical comments on the readings, and writing peer-reviews.
3. You will practice and gain experience in HRI research skills (e.g., robot programming, designing experiments, analyzing data) through the course labs.
4. You will gain hands-on HRI research experience through the course project where you will design and execute an HRI study from scratch.

Credit Hours

This is a 3-credit course. Per KU policy, students should expect to spend approximately 6 hours per week outside of class on readings, assignments, lab preparation, and project work, in addition to scheduled class and lab meetings.

Required Materials

There is no required textbook for this course. All readings are available on the course schedule page.

Course Evaluations

At the end of the semester, you will have the opportunity to complete a course evaluation. Your feedback helps improve the course and is appreciated. Please take the time to complete the evaluation when it becomes available.

Device-Free Class Meetings (Mondays + Wednesdays)

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During our class meetings where we will be discussing HRI research papers, our classroom will be device free to allow us to better focus on the discussion and pay attention to one another.

Grading

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Flexibility

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

• 2 late reading reflections (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.

If you plan to observe a religious holiday that conflicts with a class meeting or deadline, please notify me as far in advance as possible so we can make arrangements. See KU's Religious Observances policy for more information.

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

Attendance/Participation

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

• Class and lab 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 class 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., reading reflection, 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.

Grade Appeals

If you believe a grade was assigned in error, please first discuss the matter with me directly. If the concern remains unresolved, you may pursue a formal appeal through KU's Change of Grade and Grade Appeals process.

Use of Generative AI

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Here, I detail the permitted and prohibited uses of generative AI in this course for both deliverables written in English and the generation of code for the labs and course project.

Deliverables written in English

This course emphasizes the development of students' original thinking, critical analysis, and theory-building skills in the field of Human-Robot Interaction. Writing, in this context, is not merely a means of communication but a tool for deep engagement, reflection, and synthesis of complex ideas. While generative AI tools (e.g., ChatGPT, Claude, GrammarlyGO, etc.) can support writing mechanics and refinement, relying on AI to generate content undermines the cognitive work expected in this course and impedes the development of your theoretical and analytical voice.

To support these learning outcomes while recognizing that generative AI is now part of the academic landscape, the following policy strikes a balance: You may use AI tools to revise or improve your writing, but not to write it for you:

• Permitted Uses of genAI:
  • Editing your own writing for clarity, grammar, or tone
  • Rephrasing your already-written sentences or paragraphs
  • Receiving feedback on your structure or style
  • Checking for redundancy or flow issues
  • Asking AI to explain difficult concepts you're reading (e.g., from papers)
• Prohibited Uses of genAI:
  • Using AI to generate first drafts, paragraphs, or entire sections of any deliverable (e.g., reading reflections, presentations, final paper)
  • Submitting AI-generated writing, even with light edits, as your own
  • Using AI to synthesize, summarize, or analyze readings in place of your own engagement

For each of your written deliverables, you will be asked to submit a genAI statement that describes if and how you used generative AI tools for that deliverable.

Why this matters: Part of this course involves developing your own theoretical lens, writing style, and scholarly reasoning. This growth happens most effectively through the process of writing: wrestling with ideas, organizing your thoughts, and receiving feedback from peers and your instructor. Overreliance on AI short-circuits that process and limits your intellectual development.

Code Deliverables (Labs and Project)

Robot programming in this course is primarily a means of implementing and testing ideas, not a central learning objective. Because of this, the use of generative AI tools for programming is permitted and encouraged for the labs and course project.

Permitted uses of genAI for programming:

• Generating or revising code
• Debugging errors or troubleshooting issues
• Understanding APIs, libraries, or documentation
• Writing comments or documentation for code

However, you remain responsible for the code you submit. You should understand how it works, be able to explain it if asked, and ensure it functions correctly and safely on the robot.

As with written assignments, you must include a genAI usage statement describing if and how generative AI tools were used in your implementation.

Policies

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Academic Integrity

This course is guided by KU's Statement of Commitment to Integrity and Ethical Conduct. In this course, we abide by the academic integrity policies of the KU School of Engineering (see KU Engineering Academic Misconduct Policy) and the broader KU Lawrence Campus (see KU's Academic Misconduct Policy). Academic misconduct includes, but is not limited to: unauthorized aid on exams or assignments, plagiarism, misrepresenting sources of academic work, grade falsification, and dishonesty in research.

Violations are handled first at the instructor level, with possible sanctions including a written warning, grade reduction on an assignment or in the course, or ineligibility to withdraw. More serious offenses are escalated to the Dean's office and may result in transcript citation, course suspension, suspension from the university, or expulsion. If you have any questions about whether an activity would constitute academic misconduct, please ask.

With respect to this course, please ensure that you appropriately cite all academic work that you paraphrase or quote and that you honestly and accurately report your use of genAI tools on written deliverables.

Selling or distributing course notes for profit is prohibited without the instructor's written permission (see KU's Commercial Note-Taking policy).

Respect & Nondiscrimination

In this course, we will abide by KU's policies the both uphold freedom of expression as well as expectations about respectful conduct, free of discrimination. The University of Kansas is committed to providing equal opportunity in its educational programs and activities, guided by the core values of respect, community, integrity, and responsibility outlined in the KU Code of Student Rights and Responsibilities. KU prohibits discrimination and harassment based on race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression, and genetic information (see KU's Nondiscrimination, Harassment, and Equal Opportunity Policy). Students have the right to be free from harassment or discrimination, and academic evaluation shall never be based on any of the protected characteristics listed above.

Sexual harassment — including sexual assault and other forms of gender-based misconduct — is additionally prohibited under Title IX of the Education Amendments of 1972 and covered by KU's Sexual Harassment Policy. To report discrimination, harassment, or sexual misconduct, contact the Office of Civil Rights & Title IX (email: civilrights@ku.edu, phone: 785-864-6414).

As a faculty member, I am a mandatory reporter: if you disclose an incident of discrimination, harassment, or sexual misconduct to me, I am required to report it to the Office of Civil Rights & Title IX.

I am committed to making this classroom a space where each student and their unique perspectives are valued. I expect all course-related interactions to be conducted with mutual respect and open communication, in accordance with KU's nondiscrimination policies. If you have any suggestions for how we can better create and maintain a respectful academic environment, please reach out to me.

Accessibility

KU is committed to ensuring that each student has access to academic programs and services. The Student Access Center (SAC) assists students with disabilities by facilitating accommodations that remove barriers to academic success. Students who need accommodations should register with SAC as soon as possible, complete an intake appointment with an Access Specialist, and request accommodations each semester through Access Online. Once you have submitted your accommodation request, please contact me privately so we can discuss how to implement your accommodations in this course.

Student Access Center
Strong Hall, Room 22, 1450 Jayhawk Blvd., Lawrence, KS 66045
Website: access.ku.edu  |  Email: access@ku.edu  |  Phone: 785-864-4064

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. If you or someone you know could benefit from mental health support, I encourage you to reach out to Counseling and Psychological Services (CAPS), which offers individual therapy, free groups and workshops, psychiatric services, and 24/7 crisis support (call or text 988). For broader well-being resources — including nutrition support, community connection, and student care services — visit Be Well @ KU. Additional support resources available to KU students include pregnant and parenting student resources, the KU Writing Center, and academic support services. If a personal emergency arises that may impact your work in this course, please reach out to me so we can discuss the best path forward.

Acknowledgments

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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. Portions of this syllabus were created and edited with the assistance of generative AI tools, including Claude and ChatGPT.