CS 546: Human-Computer Interaction
Course Syllabus
| Course: | CS 546, Human-Computer Interaction, Fall 2026 |
| Location: | Unity Hall 405 |
| Times | Tuesdays 6-8:50pm |
| Professor: | Erin Solovey |
| Email: | esolovey @ wpi.edu |
| Office: | Fuller Laboratory 232 |
| Office Hours: | Posted on website |
| TA: | Mai Do |
| Email: | pdo @ wpi.edu |
| Office Hours: | TBD |
Why the "Human" Comes First in Human-Computer Interaction
For computer scientists, the word design is too often used exclusively in the context of code and architecture. The result of this narrow perspective is that engineers have a habit of building complex, intricate products that are wonderfully functional, but never used. When they are used, neglecting people in your design can lead to unexpected consequences that range from clumsiness to discrimination for individuals, groups, or cultures.This course explores how people interact with technology, and how we can design those interactions to be intuitive, ethical, and impactful. We'll study both human behavior and computational systems to understand how interfaces shape our actions, decisions, and relationships.
Why HCI Matters More Than Ever
Computers are no longer confined to desktops. They're embedded in our homes, cars, classrooms, and even our bodies. We interact with them through voice, gesture, gaze, and AI-driven systems. As computing becomes more pervasive, the quality of our interactions with technology directly affects our quality of life.Whether you're building apps, wearables, or intelligent systems, understanding HCI is essential. Usability and user experience are not just "nice to have." They're competitive advantages and ethical imperatives.
In this class, you will learn to:
- Identify Human-Centered Problems: Discover design opportunities grounded in real human needs and behaviors.
- Apply Human-Centered Design Processes: Use iterative, research-based methods to design and evaluate interactive systems.
- Explore Emerging Interaction Paradigms: Engage with cutting-edge topics like AI-assisted interfaces, extended reality (XR), multimodal interaction, and inclusive design.
- Practice HCI Research Methods: Develop skills in prototyping, user research, critical reading, and communicating design insights, preparing you for both industry and academic research.
- Design With and Critically Evaluate AI: Use AI tools to accelerate design and research work, validate their output against real users and evidence, and judge where AI helps, misleads, or falls short.
- Communicate and Defend Design Decisions: Present, critique, and defend your choices, grounding them in HCI principles and evidence rather than assertion.
Responsibilities
Participation, Professionalism, and Critique
When the core content of a course involves people, engagement is essential. In this class, we will engage in collaborative design exercises, test interactive systems with one another, and provide thoughtful critiques of each other's work. Because of this, participation plays a larger role in your grade than in many other courses. Coffee up!Your participation grade will reflect:
- Consistent attendance and punctuality
- Active involvement in class activities and discussions
- Constructive and respectful critique of classmates' work
Learning Materials & In-Class Activities
Each week, the course schedule will include materials for you to read, watch, or listen to in advance. These will help you engage more deeply with our in-class work. Class sessions will combine short lectures to introduce or clarify concepts with hands-on activities, discussions, and collaborative exercises. You'll have time in class to explore ideas, iterate on designs, present your work, and give and receive constructive critiques. This blend of lecture and active learning is designed to help you both understand the concepts and apply them in practice.You'll also be assessed through occasional written reflections on class activities and through your engagement with the assigned reading (described next).
Reading and reading engagement. Each week you'll have assigned reading: a mix of foundational material on HCI, design, and research methods, and research papers connected to your classmates' presentations. We'll use Perusall for reading engagement: you read and annotate each assigned text, responding both to the material and to each other's comments. This prepares you for in-class work and discussion, and your reading engagement counts toward your grade. Good comments include a question you had, something you didn't understand, an idea the reading inspired, a connection to your own experience or other coursework, or a thoughtful response to a classmate's annotation. In particular, doing the reading before a classmate's presentation matters and counts.
We'll draw excerpts from the following books, all available as free eBooks through WPI's Gordon Library. If you'd like to explore further, these are excellent resources:
- Introduction to Human-Computer Interaction - Open Access textbook by Kasper Hornbæk, Per Ola Kristensson, Antti Oulasvirta
- Designing with the Mind in Mind by Jeff Johnson
- The Design of Everyday Things by Don Norman
- Human-Computer Interaction : An Empirical Research Perspective by Scott MacKenzie
- Sketching User Experiences: Getting the Design Right and the Right Design by Bill Buxton
Presentations
Each student will give an individual presentation and lead a class discussion on one of the special topic readings. This is an opportunity to deepen your understanding of a specific area of HCI and to help your peers engage critically with the material. You will be responsible for:- Preparing and posting slides that summarize the reading and present your analysis and critique of the work.
- Situating the reading within the broader context of the course (e.g., how it connects to themes, methods, or debates we've discussed).
- Leading a discussion, encouraging thoughtful dialogue and questions from your classmates.
Assignments
Assignments will solidify and expand on the topics we cover, and some will be done in class. Any work unfinished at the end of class will be completed on your own time by the posted deadline (usually before the next class meeting). Across the term, assignments are designed to build the core skills of the course, including reading and critiquing HCI research, practicing user-research and evaluation methods, and working thoughtfully and critically with AI tools as part of a design and research process. Specific deliverables and due dates will be described in each assignment and on Canvas.Team Project
This course includes a multi-week team project that synthesizes the concepts, methods, and skills developed throughout the semester. Students will work in small teams and pursue a direction that fits their interests:- Design and prototype a novel interactive system that addresses a real-world HCI challenge, or
- Conduct an HCI research project, such as an empirical study or an exploratory system/artifact that investigates a research question.
At the end of the project, students will evaluate the contributions of their fellow team members. These peer evaluations will be used alongside the overall group project grade to determine each student's final grade for the project.
Individual grades may be adjusted based on:
- The quality and consistency of contributions as reported by team members
- Evidence of collaboration, initiative, and responsibility
- Any documented concerns or exceptional contributions
Exams
There will be no exams.Grading
In this course, grading is designed not only to evaluate your work but to cultivate the professional skills expected in HCI research and practice. Rubrics will be provided for most assignments. These are detailed evaluation frameworks that:- Specify the standards for exemplary, satisfactory, and incomplete work
- Clarify expectations before you begin
- Serve as a tool for self-review before submission
- Team Project: 45%
- Assignments: 24% (individual and in-class assignments, including short reflections on your goals for the course)
- Research Presentation & Discussion: 10%
- Reading Engagement (Perusall): 10%
- Participation: 11% (attendance, in-class engagement, and critique)
Regrade requests
In graduate-level work, evaluation is part of an iterative process, similar to how research papers are reviewed and authors respond with clarifications or additional evidence. If you believe a grading decision on an assignment or other graded work does not accurately reflect your work, you may submit a formal regrade request.Timeline: Requests must be submitted within one week of the grade being posted. After this period, you may still discuss your work for learning purposes, but no grade adjustments will be made.
Process:
- Prepare a written, professional explanation addressed to your grader.
- For each rubric item in question, clearly state:
- The score you believe is appropriate
- A concise rationale supported by evidence from your work, the rubric, and/or relevant course materials
- The entire assignment will be re-evaluated, not just the items contested.
- As with professional peer review, reassessment can result in a higher score, a lower score, or no change.
- Only one regrade request per assignment is permitted.
Late Work
Assignments are expected to be submitted by the posted deadline. Work submitted late without prior arrangement will be penalized at 10% of the total possible points per calendar day past the deadline.If you anticipate difficulty meeting a deadline due to illness, personal emergency, or other exceptional circumstances, contact the instructor before the due date whenever possible to discuss alternative arrangements. Extensions are granted at the instructor's discretion and typically require a clear plan for completion.
Technical issues (e.g., file corruption, last-minute network problems) are not generally accepted as reasons for waiving late penalties. Plan ahead and back up your work.
Inclusivity & Professional Conduct
This course values and relies on diversity of perspectives, experiences, and disciplines. Effective human-computer interaction design depends on engaging with varied viewpoints and respecting the lived experiences of others.All members of the class are expected to:
- Engage respectfully in discussions and critiques, even when viewpoints differ.
- Listen actively and ensure all voices have the opportunity to be heard.
- Contribute constructively to group work, honoring deadlines and shared responsibilities.
- Uphold professional standards in communication (both verbal and written) and in how you represent your work.
- Consider inclusivity in your designs, proactively addressing accessibility, cultural context, and ethical implications.
Communication
The instructor will disseminate important announcements through Canvas. Also, Canvas contains a timeline with links to all information (lecture slides, assignments, etc.) relevant to the course.Generative AI Usage Policy (adapted from Prof. Gillian Smith)
I want this to be a class where we can come to a greater understanding of what generative AI systems mean for our discipline. We can learn together about what works, what doesn't, and how it's going to impact your creative and/or research processes. We will also discuss inherent biases in generative AI systems in class, and what that means for usage both in class and in our larger professional context.To support these goals, I request the following:
- If you decide to use generative AI in a project or assignment, please disclose how you have used it in a supplemental document that you upload with your submission. At a minimum, I want to know: which tool(s) you used and for what, what you perceive as the pros and cons of having used it, how you incorporated generative AI into your process, and whether there remains text/code/art/music generated by the system in your final product.
- If you use a generative AI system and do not understand its output (e.g. it creates code or written language you do not understand), please make your best attempt at understanding it. You can always bring it to me or a TA with questions.
- Generative AI usage should be supplemental to your own work. Do: feel free to experiment with it for brainstorming, use it to embellish work you have done, or significantly modify its output (with disclosure!). Don't: give an assignment prompt as input and paste the output as your submission.
- Using generative AI is absolutely not mandatory or expected. If you prefer to avoid these tools, for whatever reason, that's okay!
- Some coursework is deliberately done without AI (interviews with real users, in-class activities, and in-class presentations and the final project defense), so that you build the underlying skills. Fabricating user data or presenting AI output as your own understanding is an integrity violation.