Week
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Topic
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Content and Reading Assignment
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Teaching Activities and Homework
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1
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Introduction and course overview
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2
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What is Human-Robot Interaction and Human-AI Interaction?
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Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of social issues, 56(1), 81-103.
Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., ... & Horvitz, E. (2019, May). Guidelines for human-AI interaction. In Proceedings of the 2019 chi conference on human factors in computing systems (pp. 1-13).
Lee, H. P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025, April). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. In Proceedings of the 2025 CHI conference on human factors in computing systems (pp. 1-22).
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Team Formation
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3
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Social Robots
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Forlizzi, J., & DiSalvo, C. (2006, March). Service robots in the domestic environment: a study of the roomba vacuum in the home. In Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction (pp. 258-265).
Breazeal, C., Dautenhahn, K., & Kanda, T. (2016). Social robotics. Springer handbook of robotics, 1935-1972.
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4
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Anthropomorphism
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Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: a three-factor theory of anthropomorphism. Psychological review, 114(4), 864.
Fink, J. (2012). Anthropomorphism and human likeness in the design of robots and human-robot interaction. In Social Robotics: 4th International Conference, ICSR 2012, Chengdu, China, October 29-31, 2012. Proceedings 4 (pp. 199-208). Springer Berlin Heidelberg.
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5
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Embodiment and Nonverbal Communication
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Mutlu, B., Shiwa, T., Kanda, T., Ishiguro, H., & Hagita, N. (2009, March). Footing in human-robot conversations: how robots might shape participant roles using gaze cues. In Proceedings of the 4th ACM/IEEE international conference on Human robot interaction (pp. 61-68).
Jung, M. F., Lee, J. J., DePalma, N., Adalgeirsson, S. O., Hinds, P. J., & Breazeal, C. (2013, February). Engaging robots: easing complex human-robot teamwork using backchanneling. In Proceedings of the 2013 conference on Computer supported cooperative work (pp. 1555-1566).
Mok, B. K. J., Yang, S., Sirkin, D., & Ju, W. (2015, August). A place for every tool and every tool in its place: Performing collaborative tasks with interactive robotic drawers. In 2015 24th IEEE international symposium on robot and human interactive communication (RO-MAN) (pp. 700-706). IEEE.
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6
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Chatbot and Verbal Communication
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Luger, E., & Sellen, A. (2016, May). " Like Having a Really Bad PA" The Gulf between User Expectation and Experience of Conversational Agents. In Proceedings of the 2016 CHI conference on human factors in computing systems (pp. 5286-5297).
Liao, Q. V., Mas-ud Hussain, M., Chandar, P., Davis, M., Khazaeni, Y., Crasso, M. P., ... & Geyer, W. (2018, April). All work and no play?. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1-13).
Torrey, C., Fussell, S. R., & Kiesler, S. (2013, March). How a robot should give advice. In 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 275-282). IEEE.
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Team Projects:
Idea Pitch
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7
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Designing AI user experiences
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Yang, Q., Steinfeld, A., Rosé, C., & Zimmerman, J. (2020, April). Re-examining whether, why, and how human-AI interaction is uniquely difficult to design. In Proceedings of the 2020 chi conference on human factors in computing systems (pp. 1-13).
Yang, Q., Steinfeld, A., & Zimmerman, J. (2019, May). Unremarkable AI: Fitting intelligent decision support into critical, clinical decision-making processes. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1-11).
Kay, M., Kola, T., Hullman, J. R., & Munson, S. A. (2016, May). When (ish) is my bus? user-centered visualizations of uncertainty in everyday, mobile predictive systems. In Proceedings of the 2016 chi conference on human factors in computing systems (pp. 5092-5103).
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8
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Transparent and explainable AI
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Wang, D., Yang, Q., Abdul, A., & Lim, B. Y. (2019, May). Designing theory-driven user-centric explainable AI. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1-15).
Shneiderman, B. (2020). Human-centered artificial intelligence: Reliable, safe & trustworthy. International Journal of Human–Computer Interaction, 36(6), 495-504.
(Optional) Ehsan, U., Passi, S., Liao, Q. V., Chan, L., Lee, I. H., Muller, M., & Riedl, M. O. (2024, May). The Who in XAI: How AI Background Shapes Perceptions of AI Explanations. In Proceedings of the CHI Conference on Human Factors in Computing Systems (pp. 1-32).
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9
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Team Projects:
Midterm Research Proposal Presentation
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Presentation
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10
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Collaboration, Teamwork, and Work Settings
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Hinds, P. J., Roberts, T. L., & Jones, H. (2004). Whose job is it anyway? A study of human-robot interaction in a collaborative task. Human–Computer Interaction, 19(1-2), 151-181.
Jung, M. F., Martelaro, N., & Hinds, P. J. (2015, March). Using robots to moderate team conflict: the case of repairing violations. In Proceedings of the tenth annual ACM/IEEE international conference on human-robot interaction (pp. 229-236).
Fraune, M. R., Šabanović, S., & Smith, E. R. (2017, August). Teammates first: Favoring ingroup robots over outgroup humans. In 2017 26th IEEE international symposium on robot and human interactive communication (RO-MAN) (pp. 1432-1437). IEEE.
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11
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Team Projects:
In-Class
Discussion
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12
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Team Projects:
In-Class
Data Collection
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13
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Emotion
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Boehner, K., DePaula, R., Dourish, P., & Sengers, P. (2007). How emotion is made and measured. International Journal of Human-Computer Studies, 65(4), 275-291.
Breazeal, C., & Brooks, R. (2005). Robot emotion: A functional perspective. Who needs emotions, 271-310.
Lee, M. K., Kiesler, S., Forlizzi, J., & Rybski, P. (2012, May). Ripple effects of an embedded social agent: a field study of a social robot in the workplace. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 695-704).
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14
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Ethics: Fairness & Trust
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Malle, B. F., Scheutz, M., Arnold, T., Voiklis, J., & Cusimano, C. (2015, March). Sacrifice one for the good of many? People apply different moral norms to human and robot agents. In Proceedings of the tenth annual ACM/IEEE international conference on human-robot interaction (pp. 117-124).
Pataranutaporn, P., Archiwaranguprok, C., Chan, S. W., Loftus, E., & Maes, P. (2025, April). Synthetic human memories: Ai-edited images and videos can implant false memories and distort recollection. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1-20).
Afroogh, S., Akbari, A., Malone, E., Kargar, M., & Alambeigi, H. (2024). Trust in AI: progress, challenges, and future directions. Humanities and Social Sciences Communications, 11(1), 1-30.
Claure, H., Kim, S., Kizilcec, R. F., & Jung, M. (2023). The social consequences of machine allocation behavior: Fairness, interpersonal perceptions and performance. Computers in human behavior, 146, 107628.
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15
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Ethics: Power
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Winkle, K., McMillan, D., Arnelid, M., Harrison, K., Balaam, M., Johnson, E., & Leite, I. (2023, March). Feminist human-robot interaction: Disentangling power, principles and practice for better, more ethical HRI. In Proceedings of the 2023 ACM/IEEE international conference on human-robot interaction (pp. 72-82).
Gero, K. I., Desai, M., Schnitzler, C., Eom, N., Cushman, J., & Glassman, E. L. (2025, April). Creative Writers' Attitudes on Writing as Training Data for Large Language Models. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1-16).
Hou, Y. T. Y., Lee, W. Y., & Jung, M. (2023, April). “Should I Follow the Human, or Follow the Robot?”—Robots in Power Can Have More Influence Than Humans on Decision-Making. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (pp. 1-13).
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16
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Team Projects: Final Poster Session
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- Poster
- Final Research Proposal
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* This syllabus is developed with reference to Professor Malte Jung's courses at Cornell University (USA): Robots, Teamwork, Emotion.
* Due to the rapid development of AI technologies, assigned readings are subject to change. Students may propose substitutions or opt out of readings during their assigned weeks. Final details will be discussed in Week 1.
* This course also includes 6 hours of online reading of recently published papers and submitting reflection reports on the Moodle platform. Detailed instructions will be provided in the first week.
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The total score of 100 points will be the accumulation of these activities:
- Leading a class (20%): Each student will lead one class over the course of the semester. (Students may form a team to co-lead. I will decide the size of the teams in the first week.) The class lead(s) will be responsible for the assigned readings and, if preferred, selecting 1-2 additional articles for students to read that apply concepts from that week’s readings to current work in Human-AI Interaction (HAII), Human-Robot Interaction (HRI), Computer-mediated communication (CMC), human-computer interaction (HCI), or a related area. Readings must be assigned to the rest of the class a week in advance. During the class session, the student(s) will be the class lead(s) to lead the discussion. The class lead(s) are encouraged to include multiple activities and up-to-date examples (such as short videos, memes, recent popular SNS posts, other student’s online discussion) to facilitate the discussion.
- Online Discussion (15%): Each week (except for Week 1, team project presentation, team project data collection, and final poster sessions), students are expected to post comments on the topic in the online forum set up for that week.
Each post should include (a) a short description of one surprising or interesting point from the readings assigned for that week, something you did not know before or had not thought deeply about; and (b) some implications of this interesting point for your own research or experience. Posts should be about 150-300 words and must be completed by 6 PM one day before the class to receive credit.
Students should also comment on two other student's posts by 10 PM one day before the class to receive full credit.
Each student is allowed to miss two weeks without any need for explanation, but no late submission will be accepted. If a student misses more than two assignments, no excuses will be accepted for subsequent missed assignments.
- Team Research Projects (55%): Students will work in teams to conduct a research project on an HRI or HAII topic. This project can be design-oriented, theoretical analysis, or related to human’s behavior related to intelligent agents.
Students are expected to work on:
- Idea Pitch (5%): Students will prepare 2-3 research topics, why they find these topics interesting and important, supported by key previous studies (2-4 for each topic). Every research topic should be less than 1 page, double spaced, excluding tables and figures.
- Midterm Research Proposal Presentation (15%): Students will present (1) one chosen research topic, (2) a refined introduction of research motivation supported by a brief literature review (with clear definitions of the main concepts, and at least 4 relevant studies), and (3) proposed research methods. The presentation should be between 8-12 minutes, followed by 5 minutes of Q&A.
- Final Poster Session (15%): Each research project team will present its research and results to the class via a short oral presentation and a poster. Students also need to prepare a 1-2 minute of short video and upload it onto YouTube to attract attention to their research. Further details will be provided later in the semester.
- Final Report (20%): Students will write a report of the project using standard report-writing style (e.g., introduction, related work (literature review), hypotheses, method, results, discussion). The research report should be 10-15 pages, double spaced, excluding tables and figures.
- Class participation (10%):
Active participation is essential for this course. Students are expected to come to each class prepared, having read and taken notes on the assigned materials. You may be called on to summarize the main arguments, strengths, weaknesses, or critiques of any assigned reading.
To receive full participation credit, each student must contribute verbally at least twice per class session. Simply attending class without speaking will result in zero points for participation that day.
Each student may miss up to two classes without explanation. However, no additional absences will be excused, regardless of the reason. In addition, students must not miss the class sessions during which they are responsible for leading discussions, presenting team projects, collecting data, or participating in the final poster session.
- Bonus (2%): Participating in any user studies related to communication, design, psychology, and human-computer interaction at NCCU will lead to +0.5 of the final semester points. Students can participate in up to 4 studies. (If a study takes more than 30 minutes, it counts as 2 studies.)
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