Blinded by novelty: a reflection on participant curiosity and novelty in automated vehicle studies based on experiences from the field
Abstract
Interacting with a novel technology or a known technology in a novel context can influence a user's interaction with said technology in both a positive or negative way. Research is often primarily interested in capturing interaction under regular conditions, rendering such influences less desirable. Depending on the actual novelty of any given technology, such halo or novelty effects might be weaker or stronger, and thereby more difficult to mitigate. In this paper, we want to share a number of experiences related to participant curiosity and technology novelty in interaction with automated vehicles. We intend to use our experiences from several studies to open the discussion on a potential underestimation of technology novelty and its effects on user research in vehicle automation technology and want to particularly highlight the role, researchers, manufacturers, and media play in shaping such effects.
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It cannot be ruled out that parts of the observations came about due to the 'novelty effect' of generative AI technologies for students and teachers.
“As such, it cannot be ruled out that parts of our observations came about due to the 'novelty effect' (see [2, 63]) of generative AI technologies for students and teachers.”
From Responding to Generative AI Technologies with Research-through-Design: The Ryelands AI Lab as an Exploratory Study (2024) · cites this paper as [63]
Cites
Agarwal, R., & Karahanna, E. (2000) · MIS Quarterly · doi:10.2307/3250951 · Cited by 4,726 · see citing works
The External Validity of Experiments
Bracht, G. H., & Glass, G. V. (1968) · American Educational Research Journal · doi:10.3102/00028312005004437 · Cited by 602 · see citing works
Hekkert, P., Snelders, D., & van Wieringen, P. V. (2003) · British Journal of Psychology · doi:10.1348/000712603762842147 · Cited by 594 · see citing works
Karapanos, E., Zimmerman, J., Forlizzi, J., & Martens, J.-B. (2009) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1518701.1518814 · Cited by 580 · see citing works
Wells, J. D., Campbell, D. E., Valacich, J. S., & Featherman, M. S. (2010) · Decision Sciences · doi:10.1111/j.1540-5915.2010.00292.x · Cited by 309 · see citing works
The Integrative Framework of Technology Use: AN Extension and Test1
Kim (2009) · MIS Quarterly · doi:10.2307/20650307 · Cited by 217 · see citing works
The Case for Implicit External Human-Machine Interfaces for Autonomous Vehicles
Moore, D. J., Currano, R., Strack, G., & Sirkin, D. M. (2019) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3342197.3345320 · Cited by 153 · see citing works
How Should Automated Vehicles Interact with Pedestrians?
Löcken, A., Golling, C., & Riener, A. (2019) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3342197.3344544 · Cited by 136 · see citing works
Hedonic and pragmatic halo effects at early stages of User Experience
Minge, M., & Thüring, M. (2017) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2017.07.007 · Cited by 128 · see citing works
Dey, D., Martens, M., Eggen, B. H., & Terken, J. M. B. (2019) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2019.07.027 · Cited by 117 · see citing works
Are your users actively involved? A cognitive absorption perspective in mobile training
Reychav, I., & Wu, D. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.09.021 · Cited by 87 · see citing works
Overcoming interaction blindness through curiosity objects
Houben, S., & Weichel, C. (2013) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/2468356.2468631 · Cited by 50 · see citing works
Benge, C. L., Onwuegbuzie, A. J., & Robbins, M. E. (2012) · International Journal of Education · doi:10.5296/ije.v4i4.2360 · Cited by 34 · see citing works
Curiosity vs. Control: Impacts of Training on Performance of Teams Working with Robots
You, S., & Robert, L. (2016) · doi:10.1145/2818052.2869121 · Cited by 12 · see citing works
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Liu, I., Liu, F., Xiao, Y., Huang, Y., Wu, S., & Ni, S. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2023.2300015 · Cited by 44 · see citing works
Benjamin, J. J., Lindley, J., Edwards, E., Rubegni, E., Korjakow, T., Grist, D., & Sharkey, R. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3660677 · Cited by 32 · see citing works
Accept or Address? Researchers’ Perspectives on Response Bias in Accessibility Research
Ming, J., Heung, S., Azenkot, S., & Vashistha, A. (2021) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3441852.3471216 · Cited by 27 · see citing works
Fridolin: participatory design and evaluation of a nutrition chatbot for older adults
Weber, P. P., Mahmood, F., Ahmadi, M., von Jan, V., Ludwig, T. G., & Wieching, R. (2023) · i-com · doi:10.1515/icom-2022-0042 · Cited by 21 · see citing works
Goldie, J., Dennis, S., Hipgrave, L., & Coleman, A. (2025) · JMIR Human Factors · doi:10.2196/71065 · Cited by 7 · see citing works
Thellman, S., Babel, F., & Tom Ziemke, B. (2024) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3610978.3640594 · Cited by 6 · see citing works
Mirnig, A. G., Gärtner, M., Wallner, V., Demir, C., Özkan, Y. D., Sypniewski, J., & Meschtscherjakov, A. (2023) · Personal and Ubiquitous Computing · doi:10.1007/s00779-023-01781-6 · Cited by 5 · see citing works
Self-citationBeyond Controllers: Exploring On-Body Micro-Gestures for Mixed Reality Adventure Gameplay
Haneling, M., Lundqvist, J., & Matviienko, A. (2025) · ACM Symposium on Virtual Reality Software and Technology (VRST) · doi:10.1145/3756884.3766008 · Cited by 2 · see citing works
Andersson, J., Habibovic, A., & Rizgary, D. (2021) · it - Information Technology · doi:10.1515/itit-2020-0023 · Cited by 1 · see citing works
Goldie, J.-M. D., Dennis, S. J., Hipgrave, L., & Coleman, A. (2025) · doi:10.2196/preprints.71065
- Authors
- Mirnig, A. G., Gärtner, M., Meschtscherjakov, A., & Tscheligi, M.
- Affiliations
- University of Salzburg (AT)
- Venue
- Proceedings of the Conference on Mensch und Computer
- Publisher
- ACM
- Published
- 2020-09-06
- Pages
- 373-381
- OpenAlex
- W3090325953
- Cited by
- 10
- References
- 14
- Citations by year
- 2025: 3 · 2024: 3 · 2023: 2 · 2021: 2
- FWCI
- 1.41
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Mensch und Computer (MuC) (publishedVersion)
- Funders
- Österreichische Forschungsförderungsgesellschaft (865110)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- halo effect, novelty effect, autonomous vehicles, vehicle automation, user interaction, user research, media influence, researcher influence
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