Instructors

Current Students (Fall 2023)

Find complete and up-to-date assignments, schedule, and policies on Fall 2023 Canvas

Course Description:

HCI research involves conceiving, designing, performing, analyzing data and reporting the results of experiments in HCI contexts and evaluating interactive technologies in engineering. Topics include defining the research question, selecting experimental objects, tasks, and participants, the ethical protection of subjects, selecting an experimental design, threats to validity, the collection and analysis of both qualitative and quantitative data, and reporting experimental research in publications.
This is a course designed primarily for PhD students in the Interactive Computing area. It may additionally be appropriate for PhD students in other areas, or advanced master’s students seeking to enter graduate research. This course does not assume prior research experience or experience in HCI, but will also be useful to students who have experience. We welcome a range of students!
This section will address practical and philosophical approaches to research in HCI. We will cover a breadth of methods for data collection and analysis, and fundamental HCI research skills such as defining research questions, designing research evaluations, and providing and receiving critique. Key learning goals will include building an individual research identity and developing research community norms. Students will choose a subset of methods in which to gain individual depth, and begin to develop an individual research identity situated within the broader context of HCI. Students will work in groups to engage with HCI methods, receive and provide feedback, propose and defend research ideas, and engage with scholars and scholarly work in HCI.
Section SMC is for CS on campus MCS students only. Section SPH is for CS and I-school PhD students. There will be no undergrad overrides for either section.

Learning Objectives:

Students who successfully complete this course should be able to...
  • Propose new research questions situated within the context set by prior research
    • Identify what is a research question
    • Identify what is a good research question
  • Design research approaches within your chosen depth to address proposed RQs and existing gaps
    • Choose appropriate research methods
    • Discuss and critique tradeoffs and contexts of research methods
    • Explain epistemological commitments behind research methods
  • Apply multiple research methods
    • Remember terminology for key methods
    • Understand and remember key methods, tradeoffs, and considerations for data collection, analysis, and reporting
    • Collect data with multiple methods
    • Analyze data with multiple methods
    • Gain experience with some methods from all “types” of methods that we’re covering (try something new)
  • Provide, receive, and act on constructive feedback
    • Recognize strengths of prior papers and ideas
    • Recall key connections to disadvantages, advantages, and contexts of methods
  • Self-teach new methods in the future
  • Develop a personal research identity and a research community
    • Defend your own philosophy and approach to research
    • Refine your own research identity
    • Situate your approach within the broader context