Human Computer Interaction (HCI) PhD Qualifier Spring 2022
Overview
The HCI Qualifying Exam tests students' ability to read and analyze HCI literature around a certain theme, find
and analyze more literature related to that theme, synthesize their knowledge to demonstrate a deep
understanding and interpretation of that literature, and develop their own novel ideas related to the theme.
The format of the exam is a written response to one or more related questions in the style of a technical
conference paper.
There is no oral component to the exam.
Faculty Committee
Registration and Withdrawal
Students must register by emailing the chair by the commitment deadline (see below).
Students may withdraw from taking the exam at any point prior to the public release of the exam questions
(see dates below). Once the exam questions are released, the exam is considered "in progress" and withdrawal
is prohibited.
To withdraw or to ask questions about this policy, please email the committee
chair.
Registered Students
- Rawan Alturkistani
- Anirban Mukhopadhyay
- Wyatt Swrat
Academic Integrity
Discussions among students of the papers identified for the HCI Qualifier are reasonable (and strongly
encouraged!) until the date the exam is released publicly.
Once the exam questions are released, we expect all such discussions will cease as students are required to
conduct their own work entirely to answer the qualifier questions.
This examination is conducted under the University's Graduate Honor
System Code.
Students are encouraged to draw from papers other than those listed in the exam to the extent that this
strengthens their arguments.
However, the answers submitted must represent the sole and complete work of the student submitting the answers.
Material substantially derived from other works, whether published in print or found on the web, must be
explicitly and fully cited.
Note that your grade will be more strongly influenced by arguments you make rather
than arguments you quote or cite.
Exam Schedule
- 1 December 2021 (by 11:59 PM EST): release of reading list
- 6 December 2021 (by 11:59 PM EST): last day for students to commit to taking the exam
- 5 January 2022 (by 11:59 PM EST): release of written exam
- 19 January 2022 (by 11:59 PM EST): student solutions to written exam due
Reading List
HCI qualifier exams ask that you reflect on important areas within HCI that are relevant to the research
interests of the faculty on the committee and important to HCI and Virginia Tech's Center for Human-Computer
Interaction.
The committee identifies a reading list of relevant and important scholarly articles within these focus areas.
Students are expected to read these articles closely and familiarize themselves with the ideas, concepts, and
technologies described.
It is expected that many of these articles will be referenced in the written qualifier exam.
It is strongly recommended that students develop an understanding of these texts through discussions with fellow
students who will be taking the exam.
These discussions should take place PRIOR to the exam period, as the exam must be taken individually.
The theme of this year's qualifier exam is Immersive learning in higher education: user experience, assessment and collaboration:
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F. Buttussi and L. Chittaro, "Effects of different types of virtual reality display on presence and learning in a safety training scenario," IEEE Transactions on Visualization and Computer Graphics, vol. 24, pp. 1063-1076, Feb. 2018.
DOI: https://doi.org/10.1109/TVCG.2017.2653117
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A. Delamarre, C. Lisetti, and C. Buche, "A cross-platform classroom training simulator: Interaction design and evaluation," in Proceedings of the 2020 International Conference on Cyberworlds (CW), pp. 86-93, Sept. 2020.
DOI: https://doi.org/10.1109/CW49994.2020.00020
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A. Dengel, J. Buchner, M. Mulders, and J. Pirker, "Beyond the horizon: Integrating immersive learning
environments in the everyday classroom," in Proceedings of the 2021 7th International Conference of
the Immersive Learning Research Network (iLRN), pp. 1-5, May 2021.
DOI: https://doi.org/10.23919/iLRN52045.2021.9459368
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S. Doolani, C. Wessels, V. Kanal, C. Sevastopoulos, A. Jaiswal, H. Nambiappan, and F. Makedon, "A review of extended reality (XR) technologies for manufacturing training," Technologies, vol. 8, no. 4, p. 77, 2020.
DOI: https://doi.org/10.3390/technologies8040077
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C. Fowler, "Virtual reality and learning: Where is the pedagogy?," British Journal of Educational Technology, vol. 46, no. 2, pp. 412-422, 2015.
DOI: https://doi.org/10.1111/bjet.12135
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X. Geng and M. Yamada, "The development and evaluation of an augmented reality learning system for Japanese compound verbs using learning analytics," in Proceedings of the 2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), pp. 71-76, Dec. 2020.
DOI: https://doi.org/10.1109/TALE48869.2020.9368345
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G. Makransky and G. B. Petersen, "The cognitive affective model of immersive learning (CAMIL): a theoretical research-based model of learning in immersive virtual reality," Educational Psychology Review, vol. 33, no. 3, pp. 937-958, 2021.
DOI: https://doi.org/10.1007/s10648-020-09586-2
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Z. Merchant, E. T. Goetz, L. Cifuentes, W. Keeney-Kennicutt, and T. J. Davis, "Effectiveness of virtual reality-based instruction on students' learning outcomes in K-12 and higher education: A meta-analysis," Computers & Education, vol. 70, pp. 29-40, 2014.
DOI: https://doi.org/10.1016/j.compedu.2013.07.033
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N. Pellas, A. Dengel, and A. Christopoulos, "A scoping review of immersive virtual reality in STEM education," IEEE Transactions on Learning Technologies, vol. 13, pp. 748-761, Oct. 2020.
DOI: https://doi.org/10.1109/TLT.2020.3019405
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G. B. Petersen, A. Mottelson, and G. Makransky, "Pedagogical agents in educational VR: An in the
wild study," in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, (New
York), pp. 1-12, Association for Computing Machinery, May 2021.
DOI: https://doi.org/10.1145/3411764.3445760
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J. Radianti, T. A. Majchrzak, J. Fromm, and I. Wohlgenannt, "A systematic review of
immersive virtual reality applications for higher education: Design elements, lessons learned, and research
agenda," Computers & Education, vol. 147, p. 103778, Apr. 2020.
DOI: https://doi.org/10.1016/j.compedu.2019.103778
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R. Skarbez, F. P. Brooks, Jr., and M. C. Whitton, "A survey of presence and related concepts," ACM Computing Surveys, vol. 50, pp. 1-39, Jan. 2018.
DOI: https://doi.org/10.1145/3134301
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S. Tan, "The rise of
immersive learning," Journal of Applied Learning & Teaching, vol. 2, pp. 91-94, 2019.
DOI: https://doi.org/10.37074/jalt.2019.2.2
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E. Wenger, "A social theory of learning," in Contemporary Theories of Learning (K. Illeris, ed.),
ch. 16, pp. 219-228, Routledge, 2nd ed., 2018.
DOI: https://doi.org/10.4324/9781315147277
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W. Winn, "Learning in artificial environments: Embodiment, embeddedness and dynamic adaptation," Technology, Instruction, Cognition and Learning, vol. 1, no. 1, pp. 87-114, 2003.
Publisher site: http://www.oldcitypublishing.com/journals/ticl-home/ticl-issue-contents/ticl-volume-1-number-1-2003/ticl-1-1-p-87-114/
Additional reference material:
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C. V. Gipps, Beyond Testing: Towards a Theory of Educational Assessment. Routledge education classic edition series, New York: Taylor & Francis Group, classic ed., 2011.
Publisher site: https://www.routledge.com/Beyond-Testing-Classic-Edition-Towards-a-theory-of-educational-assessment/Gipps/p/book/9780415689564
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R. Hartson and P. Pyla, UX
Book: Agile UX Design for a Quality User Experience. Cambridge, MA: Morgan Kaufmann, second ed., 2019.
Publisher site: https://www.elsevier.com/books/the-ux-book/hartson/978-0-12-805342-3
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M. J. W. Lee, M. Georgieva, B. Alexander, E. Craig, and J. Richter, "The state of XR and immersive learning: Outlook report
2021," 2021.
Question
Write a research proposal paper on a topic related to Immersive learning in higher education: user experience, assessment and collaboration.
The goal of the paper is to identify problems and propose research related to specific issues, subjects, courses and your personal experiences and expectations.
The proposal should be centered around one or more clearly stated research question(s).
Motivate and explicitly state your research question(s) in the introduction of the paper.
Be sure that your proposed research actually addresses these questions.
The proposal should also include at least the following components:
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A literature review:
This should synthesize a summary of the state of the art, identify relevant findings and guidelines, and identify gaps in the literature.
You are expected to include some of the publications on the qualifier list, as well as drawing from your own extensive set of readings and references.
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A proposed design:
This may be the design of a novel technique, approach, system, or application, or it may be the design of an experimental testbed (tasks, conditions).
In either case, provide detailed rationale for your design.
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One or more proposed studies:
The study or studies can be of any type (e.g., design validation, hypothesis testing, phenomenological, exploratory) and can use any relevant methods for user experience, assessment and collaboration aspects.
Provide detailed rationale for your study design(s).
You may choose to address each of these three aspects equally, or to emphasize one of them.
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Discussion:
You should make a compelling case for the need for the proposed research and clearly describe and give some indication of expected outcomes and the overall benefits of conducting the proposed research.
Be explicit about the proposed contributions of your work and where your emphasis lies.
Submission
Submit your paper in PDF format (use Formating
Guidelines for VGTC Conference Style Papers) by email to the committee
chair.
The length of the paper must be at least 6 pages but no more than 8 pages (without references).
Submissions are due by 11:59 PM EST on 19 January 2022.
Assessment
After the written examination, the examining faculty will determine the student's score for the examination
process.
The score is between 0-3 points, depending on the student's performance on the written exam.
(Note that there is no oral exam for the HCI qualifier.)
These points may be applied toward the total score necessary to qualify for the Ph.D. The assessment criteria,
as defined by GPC, are as follows.
Prime factors for assessment include being able to distinguish good work from poor work, and explain why; being
able to synthesize the body of work into an assessment of the state-of-the-art on a problem (as indicated by the
collection of papers); being able to identify open problems and suggest future work.
- 3: Excellent performance, beyond that normally expected or required for a PhD student.
- 2: Performance appropriate for PhD-level work.
- 1: While the student adequately understands the content of the work, the student is deficient in one or more
of the factors listed for assessment under score value of 2. A score of 1 is the minimum necessary for an
MS-level pass.
- 0: Student's performance is such that the committee considers the student unable to do PhD-level work in
Computer Science.