research-article

Planning Adaptive Mobile Experiences When Wireframing

Authors:

John Zimmerman,

Aaron Steinfeld,

Anthony TomasicAuthors Info & Claims

DIS '16: Proceedings of the 2016 ACM Conference on Designing Interactive Systems

Pages 565 - 576

https://doi.org/10.1145/2901790.2901858

Published: 04 June 2016 Publication History

Abstract

Machine learning improves mobile user experience. Interestingly, envisioning apps with adaptive interfaces that reduce navigation and selection effort is not standard UX practice. When implementing an adaptive UI for our mobile transit app, we encountered a number of problems. Our original design did not log necessary information nor did it induce users to provide good labels. On reflection, we realized UX designers should identify and refine UI adaptions when sketching wireframes. To advance on this insight, we reviewed the interfaces of popular apps and extracted six design patterns where UI adaptation can improve in-app navigation. Next, we designed an exemplar set of wireframes, illustrating how UX designers might annotate their interaction flows to communicate planned adaptation and note the information (logs and labels) needed to make the desired inferences.

References

[1]

Gregory D. Abowd, Christopher G. Atkeson, Jason Hong, Sue Long, Rob Kooper, and Mike Pinkerton. 1997. Cyberguide: a mobile context-aware tour guide. Wireless Networks 3, 5: 421--433. http://doi.org/10.1023/A:1019194325861

Digital Library

[2]

Daniel Billsus, Clifford a Brunk, Craig Evans, Brian Gladish, and Michael Pazzani. 2002. Adaptive Interfaces for Ubiquitous Web Access. Communications of the ACM 45, 5: 34--38.

Digital Library

[3]

Jan O. Borchers. 2001. A pattern approach to interaction design. AI & Society 15, 4: 359--376. http://doi.org/10.1007/BF01206115

Digital Library

[4]

Robert Bridle and Eric McCreath. 2006. Inducing shortcuts on a mobile phone interface. Proceedings of the international conference on Intelligent user interfaces (IUI '06), 327. http://doi.org/10.1145/1111449.1111526

Digital Library

[5]

Dermot Browne. 2014. Adaptive User Interfaces. Elsevier.

[6]

John Brownlee. 2015. Apple Finally Learns AI Is The New UI. Retrieved December 25, 2015 from http://www.fastcodesign.com/3047199/applefinally-learns-ai-is-the-new-ui

[7]

Christian Crumlish and Erin Malone. 2009. Designing Social Interfaces: Principles, Patterns, and Practices for Improving the User Experience. "O'Reilly Media, Inc."

[8]

Razak Eun Lee, Young and Benbasat. 2003. Interface Design for Mobile Commerce. Communications of the ACM 46, 12: 48--52.

Digital Library

[9]

Leah Findlater and Krzysztof Z. Gajos. 2009. Design Space and Evaluation Graphical User Interfaces. AI Magazine, Höök 2000: 68--73. http://doi.org/10.1609/aimag.v30i4.2268

[10]

Leah Findlater and Joanna McGrenere. 2008. Impact of screen size on performance, awareness, and user satisfaction with adaptive graphical user interfaces. Proceedings of the 26th SIGCHI Conference on Human Factors in Computing Systems: 1247--1256. http://doi.org/10.1145/1357054.1357249

Digital Library

[11]

Dan Frommer. 2015. These are the 25 most popular mobile apps in America. Retrieved January 17, 2016 from http://qz.com/481245/these-are-the-25most-popular-2015-mobile-apps-in-america/

[12]

Krzysztof Z. Gajos, Daniel S. Weld, and Jacob O. Wobbrock. 2010. Automatically generating personalized user interfaces with Supple. Artificial Intelligence 174, 12--13: 910--950. http://doi.org/10.1016/j.artint.2010.05.005

Digital Library

[13]

Kz Gajos, Mary Czerwinski, Ds Tan, and Ds Weld. 2006. Exploring the design space for adaptive graphical user interfaces. Proceedings of Advanced visual interfaces: 201--208. http://doi.org/10.1145/1133265.1133306

Digital Library

[14]

Jason Hong. 2009. Usable Privacy and Security?: A Grand Challenge for HCI Usable Privacy and Security?: A Grand Challenge for HCI.

[15]

Steven Hoober and Eric Berkman. 2011. Designing Mobile Interfaces. "O'Reilly Media, Inc."

Digital Library

[16]

K. Höök. 2000. Steps to take before intelligent user interfaces become real. Interacting with Computers 12, 4: 409--426. http://doi.org/10.1016/S09535438(99)00006-5

[17]

Eric Horvitz. 1999. Principles of Mixed-Initiative User Interfaces. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '99). http://doi.org/10.1145/302979.303030

Digital Library

[18]

Natalia Juristo and Ana Moreno. 2008. Moving usability forward to the beginning of the software development process. Human Computer Interaction, Bass 1999.

[19]

Azam Khan, Lyn Bartram, Eli Blevis, Carl DiSalvo, Jon Froehlich, and Gordon Kurtenbach. 2011. CHI 2011 sustainability community invited panel. Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems CHI EA '11, ACM Press, 73. http://doi.org/10.1145/1979742.1979484

Digital Library

[20]

Cliff Kuang. 2013. Why a New Golden Age for UI Design Is Around the Corner. Wired Magazine

[21]

09. Retrieved December 28, 2015 from http://www.wired.com/2013/08/design-and-thedigital-world/ 21. Miroslav Kubat, Robert C. Holte, and Stan Matwin. Machine Learning for the Detection of Oil Spills in Satellite Radar Images. Machine Learning 30, 2--3: 195--215. http://doi.org/10.1023/A:1007452223027

Digital Library

[22]

Pat Langley. 1997. Machine Learning for Adaptive User Interfaces. In KI-97: Advances in Artificial Intelligence, Gerhard Brewka, Christopher Habel and Bernhard Nebel (eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 53--62. http://doi.org/10.1007/3-540-63493-2

Digital Library

[23]

Pat Langley. 1999. User Modeling in Adaptive Interfaces. UM '99 Proceedings of the seventh international conference on User modeling, Springer-Verlag New York, Inc., 357--370. Retrieved from http://citeseer.ist.psu.edu/viewdoc/summary?doi=1 0.1.1.29.8715/nhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.29.8715&rep=rep1&am p;type=pdf

Digital Library

[24]

Min Kyung Lee. 2013. Designing personalization in technology-based services. Retrieved January 9, 2016 from http://dl.acm.org/citation.cfm?id=2575012

[25]

Henry Lieberman, Hugo Liu, Push Singh, and Barbara Barry. 2004. Beating Commons Sense into Interactive Applications. AI Magazine 25: 63--76.

[26]

Xiaolei Ma, Yao-Jan Wu, Yinhai Wang, Feng Chen, and Jianfeng Liu. 2013. Mining smart card data for transit riders' travel patterns. Transportation Research Part C: Emerging Technologies 36, January 2016: 1--12. http://doi.org/10.1016/j.trc.2013.07.010

[27]

Sean M. McNee, John Riedl, and Joseph A. Konstan. 2006. Being accurate is not enough: How Accuracy Metrics have hurt Recommender Systems. CHI '06 extended abstracts on Human factors in computing systems CHI EA'06, ACM Press, 1097. http://doi.org/10.1145/1125451.1125659

Digital Library

[28]

Kyle Montague, Vicki L Hanson, and Andy Cobley. 2011. Adaptive Interfaces?: A Little Learning is a Dangerous Thing. In Universal Access in Human-Computer Interaction. Design for All and eInclusion. 391--399. http://doi.org/10.1007/978-3-642-21672-5_43

Digital Library

[29]

Issam El Naqa and Martin J. Murphy. 2015. What Is Machine Learning? In Machine Learning in Radiation Oncology, Issam El Naqa, Ruijiang Li and Martin J. Murphy (eds.). Springer International Publishing, Cham, 3--11. http://doi.org/10.1007/978-3-319-18305-3

[30]

D. Narayanan, J. Flinn, and M. Satyanarayanan. 2000. Using history to improve mobile application adaptation. Proceedings Third IEEE Workshop on Mobile Computing Systems and Applications, December: 31--40. http://doi.org/10.1109/MCSA.2000.895379

Digital Library

[31]

Le T Nguyen, Heng-tze Cheng, Pang Wu, Senaka Buthpitiya, and Ying Zhang. 2012. PnLUM?: System for Prediction of Next Location for Users with Mobility.

[32]

Kayur Patel. 2010. Lowering the Barrier to Applying Machine Learning. Adjunct Proceedings of the 23Nd Annual ACM Symposium on User Interface Software and Technology: 355--358. http://doi.org/10.1145/1866218.1866222

Digital Library

[33]

Jenny Preece, Helen Sharp, and Yvonne Rogers. 2015. Interaction Design: Beyond HumanComputer Interaction. John Wiley & Sons.

[34]

Rudy Raymond, Takamitsu Sugiura, and Kota Tsubouchi. 2011. Location recommendation based on location history and spatio-temporal correlations for an on-demand bus system. Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems GIS '11, ACM Press, 377. http://doi.org/10.1145/2093973.2094027

Digital Library

[35]

Yvonne Rogers. 2006. Moving on from Weiser's Vision of Calm Computing: engaging UbiComp experiences. Ubicomp '06: 404--421. http://doi.org/10.1007/11853565_24

Digital Library

[36]

Brian J. Rosmaita. 2006. Accessibility first!: a new approach to web design. Proceedings of the 37th SIGCSE technical symposium on Computer science education SIGCSE '06, ACM Press, 270. http://doi.org/10.1145/1121341.1121426

Digital Library

[37]

Roland T. Rust and Tuck Siong Chung. 2006. Marketing Models of Service and Relationships. Marketing Science 25, 6: 560--580. http://doi.org/10.1287/mksc.1050.0139

Digital Library

[38]

Emily Schwartzman. Designer's Toolkit: Prototyping Tools, Reviews and rankings to help you find the best prototyping tool for the job. Retrieved January 7, 2016 from http://www.cooper.com/prototyping-tools

[39]

Ahmed Seffah and Homa Javahery. 2005. Multiple User Interfaces: Cross-Platform Applications and Context-Aware Interfaces. John Wiley & Sons.

[40]

Ling Shao, Caifeng Shan, Jiebo Luo, and Minoru Etoh. 2010. Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications. Retrieved January 13, 2016 from http://dl.acm.org/citation.cfm?id=1869926

Digital Library

[41]

Daniel Siewiorek, Asim Smailagic, Junichi Furukawa, et al. 2003. SenSay: A Context-Aware Mobile Phone. 248. Retrieved January 15, 2016 from http://dl.acm.org/citation.cfm?id=946249.946884

[42]

Jenifer Tidwell. 2010. Designing Interfaces. "O'Reilly Media, Inc."

Digital Library

[43]

Anthony Tomasic, John Zimmerman, Aaron Steinfeld, and Yun Huang. 2014. Motivating Contribution in a Participatory Sensing System via Quid-pro-quo. Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing.: 979--988. http://doi.org/10.1145/2531602.2531705

Digital Library

[44]

Daniel S. Weld, Corin Anderson, Pedro Domingos, et al. 2003. Automatically personalizing user interfaces. IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence, Morgan Kaufmann Publishers Inc., 1613--1619. Retrieved December 26, 2015 from http://dl.acm.org/citation.cfm?id=1630659.1630944

Digital Library

[45]

John Zimmerman, Anthony Tomasic, Isaac Simmons, et al. 2007. Vio: a mixed-initiative approach to learning and automating procedural update tasks. Proceedings of the SIGCHI conference on Human factors in computing systems CHI '07, ACM Press, 1445. http://doi.org/10.1145/1240624.1240843

Digital Library

Cited By

Petridis STerry MCai C(2024)PromptInfuser: How Tightly Coupling AI and UI Design Impacts Designers’ WorkflowsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661613(743-756)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661613
Cho SJon SJin YJung JOh C(2024)Understanding the Dynamics in Creating Domain-Specific AI Design Guidelines: A Case Study of a Leading Digital Finance Company in South KoreaExtended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650759(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3650759
Santos IAgapito AYalong KDe Jesus ROlipas C(2023)MENTORVERSE: The Development and Assessment of a Cross-Platform Mentor Finder Using React JS and MongoDBEuropean Journal of Contemporary Education and E-Learning10.59324/ejceel.2023.1(2).041:2(33-44)Online publication date: 1-Sep-2023
https://doi.org/10.59324/ejceel.2023.1(2).04
Show More Cited By

Index Terms

Planning Adaptive Mobile Experiences When Wireframing
1. Human-centered computing

Recommendations

Mobile experiences for tourism: brick city tours
CHI EA '13: CHI '13 Extended Abstracts on Human Factors in Computing Systems

We present a mobile user experience design prototype called Brick City Tours (BCT), which is aimed at prospective university students who are visiting the Rochester Institute of Technology (RIT) campus. Our ongoing research and development is looking at ...
Understanding the Design of Playful Experiences Around Ingestible Sensors
CHI PLAY '18 Extended Abstracts: Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts

The advancement of sensor technology has provided new opportunities for bodily play and consequently enriched our bodily experiences. The emergence of ingestible sensors supports capturing the user's body data continuously. The intimacy between ...
Usability of interaction patterns
CHI EA '06: CHI '06 Extended Abstracts on Human Factors in Computing Systems

Interaction patterns are becoming an important method for bridging the gap between analysis and design in user-centered design. Recent studies, however, have indicated problems in their usability. Our overall research goal is to improve the usability of ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

DIS '16: Proceedings of the 2016 ACM Conference on Designing Interactive Systems

June 2016

1374 pages

ISBN:9781450340311

DOI:10.1145/2901790

General Chair:
Marcus Foth
Queensland University of Technology
,
Program Chairs:
Wendy Ju
Stanford University
,
Ronald Schroeter
Queensland University of Technology
,
Stephen Viller
University of Queensland

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 June 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

JSPS KAKENHI

Conference

DIS '16

Sponsor:

SIGCHI

DIS '16: Designing Interactive Systems Conference 2016

June 4 - 8, 2016

QLD, Brisbane, Australia

Acceptance Rates

DIS '16 Paper Acceptance Rate 107 of 418 submissions, 26%;

Overall Acceptance Rate 1,158 of 4,684 submissions, 25%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

42
Total Citations
View Citations
1,952
Total Downloads

Downloads (Last 12 months)390
Downloads (Last 6 weeks)132

Reflects downloads up to 28 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Petridis STerry MCai C(2024)PromptInfuser: How Tightly Coupling AI and UI Design Impacts Designers’ WorkflowsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661613(743-756)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661613
Cho SJon SJin YJung JOh C(2024)Understanding the Dynamics in Creating Domain-Specific AI Design Guidelines: A Case Study of a Leading Digital Finance Company in South KoreaExtended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650759(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3650759
Santos IAgapito AYalong KDe Jesus ROlipas C(2023)MENTORVERSE: The Development and Assessment of a Cross-Platform Mentor Finder Using React JS and MongoDBEuropean Journal of Contemporary Education and E-Learning10.59324/ejceel.2023.1(2).041:2(33-44)Online publication date: 1-Sep-2023
https://doi.org/10.59324/ejceel.2023.1(2).04
Gudoniene DStaneviciene EBuksnaitis VDaley N(2023)The Scenarios of Artificial Intelligence and Wireframes Implementation in Engineering EducationSustainability10.3390/su1508685015:8(6850)Online publication date: 19-Apr-2023
https://doi.org/10.3390/su15086850
Vlahu-Gjorgievska EBurazor AWin KTrajkovik V(2023)mHealth Apps Targeting Obesity and Overweight in Young People: App Review and AnalysisJMIR mHealth and uHealth10.2196/3771611(e37716)Online publication date: 19-Jan-2023
https://doi.org/10.2196/37716
Shi YGao TJiao XCao N(2023)Understanding Design Collaboration Between Designers and Artificial Intelligence: A Systematic Literature ReviewProceedings of the ACM on Human-Computer Interaction10.1145/36102177:CSCW2(1-35)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610217
Upadhyay AShekhawat MManhas R(2023)Data Driven UX/UI design for reproductive health tracker2023 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS)10.1109/SCEECS57921.2023.10063134(1-5)Online publication date: 18-Feb-2023
https://doi.org/10.1109/SCEECS57921.2023.10063134
Sun LLi ZZhou ZLou SLi WZhang Y(2023)Towards the conceptual design of ML-enhanced products: the UX value framework and the CoMLUX design processArtificial Intelligence for Engineering Design, Analysis and Manufacturing10.1017/S089006042200027037Online publication date: 30-Mar-2023
https://doi.org/10.1017/S0890060422000270
Polignano MLops Pde Gemmis MSemeraro G(2023)HELENAInformation Processing and Management: an International Journal10.1016/j.ipm.2022.10312460:1Online publication date: 20-Jan-2023
https://dl.acm.org/doi/10.1016/j.ipm.2022.103124
Poiroux JMaudet NPineau KBrulé ETabard A(2023)Design IndirectionsComputer Supported Cooperative Work (CSCW)10.1007/s10606-022-09459-yOnline publication date: 23-May-2023
https://doi.org/10.1007/s10606-022-09459-y
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents