HCI PhD Qualifier Exam – Spring 2025

last updated Jan 4, 2025

CS PhD Qualifier 2025 page is here

Faculty Organizers

  • Chair: Chris North, north@vt.edu (direct all questions to the chair)
  • Committee members: Brendan David-John, Kurt Luther, Sehrish Nizamani, Yaxing Yao
  • Backups: Scott McCrickard, Yan Chen, Eugenia Rho

Exam Schedule

  • Jan 1 – Jan 13: Ph.D. Qualifier Exam webpages goes online. Students register for the exam at CS PhD Qualifier 2025 page
  • Jan 13 – 20: Committee releases decisions on qualifier waiver to students who requested it 
  • Jan 20 – Feb 23: Students prepare the written exam
  • Feb 24 – Feb 28: Students present oral exam (backups Mar 3-7)
  • Mar 15: Committees finalize the results for Qualifier Exam
  • Mar 20: Results released to students

Waivers

Waivers: For students that have already published a paper as the first author at a high-quality HCI venue, then you have already satisfied the goal of the qualifier and you can apply for a waiver. The quality of the paper and venue will be judged by the committee. If the waiver is denied, the student should proceed to take the qualifier exam. If accepted, the student does not need to complete the exam.

The wavier application is part of the PhD Qualifier Registration process found at CS PhD Qualifier 2025 page.

Exam

The goal of the qualifier exam is to prepare students for PhD level research. The qualifier serves as a pre-prelim, and gets students started towards publishing their first high-quality first-authored research paper. The exam includes both written and oral formats.

Craft a research plan to investigate a specific novel HCI issue of your choice. The plan should creatively synthesize content from the HCI literature, and leverage core HCI approaches to propose novel research. Your report should be in the form of a research proposal, and should serve as the starting point of a potential future research paper should you proceed to execute the proposed plan and obtain results. You will submit a written proposal and give a short oral presentation about it to the committee.

  • If you already have a faculty research advisor and/or research project at Virginia Tech, the specific topic of your research plan can be related to the topic that you are already working on with that advisor or project. Thus, use this exam as an opportunity to make progress towards a relevant paper with your advisor or project team. Your proposal should be your own ideas and writing, not something that was given or assigned to you by your advisor or project leader.
  • If you do not already have an advisor or project, we provide a default research topic and reading list in the Appendix below to get you started on crafting a proposal idea.

Written Proposal Format

Your written proposal should be centered around at least one or more clearly stated research question(s). Motivate and explicitly state your research questions in the introduction of the paper. Be sure that your proposed research plan would provide data or insights that address your research questions (if the plan were to be executed; we do not expect results as part of the submitted proposal). The research questions should be specific and appropriate in scope for a single research paper. Common mistakes are to propose research questions that are too broad, open-ended, or ill-defined.

The proposal should also include at least the following components:

  • Literature review: This should synthesize a summary of the state of the art, identify relevant findings and guidelines, and identify specific gaps in the literature that lead to your idea. You are expected to include at least 10 papers drawn from your own extensive set of readings relevant to your proposed questions.  The literature review should cover multiple facets of your research effort, including but not limited to the framing and the approach. 
  • Proposed design: This may be the design of a novel technique, model, system, or application, or it may be the design of an experimental testbed (tasks, conditions). In either case, provide a detailed rationale for your design.
  • Proposed research methods: The methods can be of any type (e.g., design validation, hypothesis testing, field study, phenomenological, etc.) and can use any relevant methods for user experience, assessment, impact, etc. Provide detailed rationale for your study design(s).

You should make a compelling case for the need for the proposed research and clearly describe and give some indication of expected outcomes, potential challenges or pitfalls, and the overall benefits of conducting the proposed research.

Be explicit about the expected contributions of your work and where your emphasis lies. You may choose to address each of the three major aspects (review, design, method) equally, or to emphasize one of them.

Limit your writeup to 4000 words, not including references. The paper format is up to you; it could be in the format of a favorite conference or journal, or in Virginia Tech’s dissertation format, if desired. Include a list of all references that you cite in any widely accepted (but consistent) format.  Appropriate pictures, figures, and tables that enhance the content of your submission are highly encouraged.

Written Proposal Submission

Submissions should be emailed in PDF form to the chair of the HCI qualifier exam committee by 11:59 pm on Feb 23, 2025.

Oral Presentation Format and Scheduling

To evaluate oral communication skills, you will present the proposal to the committee. Presentation time is 15 minutes maximum, plus 15 minutes of Q&A. You may use any media as part of your presentation. The presentations will take place the week after the written proposals are submitted.

Scheduling TBA.

Evaluation Criteria

The qualifier exam is graded on a pass/fail basis. To pass the exam, the written proposal and oral exam should clearly identify research questions, synthesize literature, propose a novel approach and appropriate methods, contain convincing and consistent arguments in adequate depth, and be clearly written and presented.

Academic integrity

This examination is conducted under the University’s Graduate Honor System Constitution. Each student is required to conduct their own work entirely, and the written report and oral presentation should be the sole authorship of the student. Material substantially derived from other works, whether published in print or found on the web, should be explicitly and fully cited. The evaluation will be more strongly influenced by arguments you make rather than arguments you quote or cite. For policy on usage of LLMs for writing submissions, we recommend seeing the ACM policy and the additional guidance from SIGCHI.

Appendix: Default Topic and Reading List

The default topic, if needed, is Human-AI interaction or AI in HCI in general. The advance of AI, including classical machine learning methods, neural networks, LLMs, etc., offers many new opportunities as well as pitfalls in HCI. A growing literature examines the unique HCI challenges that arise when designing, using, and testing HCI technologies that involve AI. To help you immerse yourself in the space, this reading list provides a diverse (yet incomplete) view of many HCI issues associated with human-AI interaction, from specific interaction techniques, to broader theories, to design and evaluation methodologies, to practical impacts.

  • Xu, Xuhai, Anna Yu, Tanya R. Jonker, Kashyap Todi, Feiyu Lu, Xun Qian, João Marcelo Evangelista Belo et al. “Xair: A framework of explainable AI in augmented reality.” In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, pp. 1-30. 2023. https://doi.org/10.1145/3544548.3581500
  • Dogan, Mustafa Doga, Eric J. Gonzalez, Karan Ahuja, Ruofei Du, Andrea Colaço, Johnny Lee, Mar Gonzalez-Franco, and David Kim. “Augmented Object Intelligence with XR-Objects.” In Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology, pp. 1-15. 2024. https://doi.org/10.1145/3654777.3676379
  • Qian Yang, Aaron Steinfeld, Carolyn Rosé, and John Zimmerman. 2020. 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 (CHI ’20), 1–13. https://doi.org/10.1145/3313831.3376301
  • Correia, A., Grover, A., Schneider, D., Pimentel, A. P., Chaves, R., de Almeida, M. A., & Fonseca, B. (2023). Designing for Hybrid Intelligence: A Taxonomy and Survey of Crowd-Machine Interaction. Applied Sciences, 13(4), 2198. https://doi.org/10.3390/app13042198
  • Shneiderman, B. (2020). Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy.International Journal of Human–Computer Interaction, 36(6), 495–504.https://doi.org/10.1080/10447318.2020.1741118
  • J. Wenskovitch and C. North, “Interactive Artificial Intelligence: Designing for the ‘Two Black Boxes’ Problem,” in Computer, vol. 53, no. 8, pp. 29-39, Aug. 2020. https://doi.org/10.1109/MC.2020.2996416
  • Daniel Buschek. 2024. Collage is the New Writing: Exploring the Fragmentation of Text and User Interfaces in AI Tools. In Proceedings of the 2024 ACM Designing Interactive Systems Conference (DIS ’24), 2719–2737. https://doi.org/10.1145/3643834.3660681
  • Saleema Amershi, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, Paul N. Bennett, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, and Eric Horvitz. 2019. Guidelines for Human-AI Interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI ’19), Paper 3, 1–13. https://doi.org/10.1145/3290605.3300233
  • Xiao Ge, Chunchen Xu, Daigo Misaki, Hazel Rose Markus, and Jeanne L Tsai. 2024. How Culture Shapes What People Want From AI. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI ’24), Article 95, 1–15. https://doi.org/10.1145/3613904.3642660
  • Chen, C., Li, W., Song, W., Ye, Y., Yao, Y., & Li, T. J. J. (2024, May). An Empathy-Based Sandbox Approach to Bridge the Privacy Gap among Attitudes, Goals, Knowledge, and Behaviors. In Proceedings of the CHI Conference on Human Factors in Computing Systems (pp. 1-28). https://doi.org/10.1145/3613904.3642363

If you want to refresh your core knowledge about HCI methods, approaches, frameworks, and theories, one or more of the following books are recommended:

  • Hartson & Pyla (2018). The UX Book.
  • Sharp, Rogers, & Preece (2023). Interaction Design: Beyond Human-Computer Interaction.
  • Shneiderman et al. (2016). Designing the User Interface.