research-article

On the Influence of Human Factors in Adaptive User Interface Design

Author:

Tilman DeuschelAuthors Info & Claims

UMAP '18: Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization

Pages 187 - 190

https://doi.org/10.1145/3213586.3213587

Published: 02 July 2018 Publication History

Abstract

The increased utilisation of adaptive visualisation techniques in commercial software requires design principles that provide guidance on how to design user interfaces that change their appearance during runtime. To contribute to the ongoing adaptive user interface (AUI) research, the development of a model is proposed that enables the methodological development of design principles for AUIs. The adoption of the conceptual framework of design-science is proposed for that purpose. Following the framework, the literature of AUI research (to identify observed user behaviour) as well as the literature of human factors (to explain the observed behaviour) have been reviewed. Design principles are built based on this knowledge. This thesis can contribute to an quality improvement of AUI systems.

References

[1]

Khalid Al-Omar and Dimitrios Rigas. 2009. A user performance evaluation of personalised menus. In Second International Conference on the Applications of Digital Information and Web Technologies (ICADIWT). 104--109.

[2]

Apple Inc. 2018. Adaptive User Interfaces: Designing Great Apps. (2018). https://developer.apple.com/design/adaptivity/

[3]

Jacques Bertin. 1983. Semiology of Graphics. University of Wisconsin Press.

Digital Library

[4]

Jason Bronwin, Andre Calitz, and Jean Greyling. 2010. The evaluation of an adaptive user interface model. In Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists (SAICSIT '10), Kotzé et al. (Ed.). ACM, New York, NY, USA, 132--143.

Digital Library

[5]

J. P. Chin, V. A. Diehl, and K. L. Norman. 1988. Development of an Instrument Measuring User Satisfaction of the Human-Computer Interface. (1988).

[6]

Tilman Deuschel, Christian Greppmeier, Bernhard Humm, and Wolfgang Stille. 2014. Semantically Faceted Navigation with Topic Pies. In Proceedings of the 10th International Conference on Semantic Systems (SEM '14), Sack et al. (Ed.). ACM, New York, NY, USA, 132--139.

Digital Library

[7]

Tilman Deuschel, Timm Heuss, Bernhard Humm, and Torsten Fröhlich. 2014. Finding without Searching: A Serendipity-based Approach for Digital Cultural Heritage. In Proceedings of the Digital Intelligence 2014, Milad Doueihi et al. (Ed.). Université Nantes.

[8]

Tilman Deuschel and Ted Scully. 2016. On the Importance of Spatial Perception for the Design of Adaptive User Interfaces. In Proceedings of the 10th IEEE International Conference on Self-Adaptive and Self-Organizing Systems. IEEE, 70--79.

[9]

Martin Dostál and Zdenek Eichler. 2011. Fine-Grained Adaptive User Interface for Personalization of a Word Processor: Principles and a Preliminary Study. In HCI International 2011 -- Posters' Extended Abstracts (Communications in Computer and Information Science), Constantine Stephanidis (Ed.), Vol. 173. Springer Berlin Heidelberg, Berlin, Heidelberg, 496--500.

[10]

Karin Eilers, Friedhelm Nachreiner, and Kerstin Hänecke. 1986. Entwicklung und Überprüfung einer Skala zur Erfassung subjektiv erlebter Anstrengung: SEA. Zeitschrift für Arbeitswissenschaft Jg. 40, H. 4 (1986), 215--224.

[11]

Leah Findlater and Joanna McGrenere. 2007. Evaluating reduced-functionality interfaces according to feature findability and awareness. In Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction (INTERACT'07), C. Baranauskas et al. (Ed.). Springer-Verlag, Berlin, Heidelberg, New York, 592--605.

Digital Library

[12]

Leah Findlater, Karyn Moffatt, Joanna McGrenere, and Jessica Dawson. 2009. Ephemeral adaptation: the use of gradual onset to improve menu selection performance. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '09), Dan R. Olsen et al. (Ed.). ACM, New York, NY, USA, 1655--1664.

Digital Library

[13]

Elizabeth Furtado. 2001. Incorporating Human Factors into a Method for Designing of Adaptive User Interfaces. In Tools for Working with Guidelines, Jean Vanderdonckt and Christelle Farenc (Eds.). Springer London, London, 147--156.

[14]

Krzysztof Gajos, Mary Czerwinski, Desney S. Tan, and Daniel S. Weld. 2006. Exploring the design space for adaptive graphical user interfaces. In Proceedings of the working conference on Advanced visual interfaces (AVI '06), Augusto Celentano and Piero Mussio (Eds.). ACM, New York, NY, USA, 201--208.

Digital Library

[15]

Krzysztof Z. Gajos, Daniel S. Weld, and Jacob O. Wobbrock. 2010. Automatically generating personalized user interfaces with Supple. Artificial Intelligence 174, 12--13 (2010), 910--950.

Digital Library

[16]

Günther Gediga, Kai-Christoph Hamborg, and Ivo Düntsch. 1999. The IsoMetrics Usability Inventory: An operationalisation of ISO 9241--10. Behaviour and Information Technology 18 (1999), 151--164.

[17]

J. T. Goodman, C. M. Kadie, D. M. Chickering, D. E. Bradford, and D. A. Glasgow. 2010. Intelligent autofill. (2010). https://www.google.com/patents/US7660779.

[18]

Marc Hassenzahl, Michael Burmester, and Franz Koller. 2003. AttrakDiff: Ein Fragebogen zur Messung wahrgenommener hedonischer und pragmatischer Qualität. Mensch &Computer (2003), 187--196.

[19]

Alan R. Hevner, Salvatore T. March, Jinsoo Park, and Sudha Ram. 2004. Design Science in Information Systems Research. MIS Q 28, 1 (2004), 75--105.

[20]

K. Höök. 2000. Steps to take before intelligent user interfaces become real. Interacting with Computers 12, 4 (2000), 409--426.

[21]

Jamil Hussain, Wajahat Ali Khan, Muhammad Afzal, Maqbool Hussain, Byeong Ho Kang, and Sungyoung Lee. 2014. Adaptive User Interface and User Experience Based Authoring Tool for Recommendation Systems. In Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services (Lecture Notes in Computer Science), Ramón Hervás et al. (Ed.), Vol. 8867. Springer International Publishing, Cham, 136--142.

[22]

Google Inc. 2018. Introduction - Material design: Google design guidelines. (2018). https://www.google.com/design/spec/material-design/introduction.html

[23]

Anthony Jameson and Krzysztof Gajos. 2012. Systems That Adapt to Their Users. In The human-computer interaction handbook, Julie A. Jacko (Ed.). Human factors and ergonomics, Vol. 20126252. CRC, Taylor &Francis, Boca Raton, Fla., 431--456.

[24]

Wiard Jorritsma, Fokie Cnossen, and Peter M.A. van Ooijen. 2015. Adaptive support for user interface customization: A study in radiology. International Journal of Human-Computer Studies 77 (2015), 1--9.

Digital Library

[25]

Cyrus Dominik Khazaeli. 2005. Systemisches Design: Intelligente Oberflächen für Information und Interaktion. rororo Computer, Vol. 60078. Rowohlt-Taschenbuch- Verl., Reinbek bei Hamburg.

[26]

Rachel Kumar. 2015. Why We Banished the Hamburger Menu From Our iPhone App. (2015). https://redbooth.com/blog/hamburger-menu-iphone-app.

[27]

Sébastien Lallé, Cristina Conati, and Giuseppe Carenini. op. 2017. Impact of Individual Differences on User Experience with a Visualization Interface for Public Engagement. In Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (ACM proceedings), Marko Tkalčič et al. (Ed.). ACM, New York (NY), 247--252.

Digital Library

[28]

Louis Li and Krzysztof Z. Gajos. 2014. Adaptive click-and-cross: adapting to both abilities and task improves performance of users with impaired dexterity. In Proceedings of the 19th international conference on Intelligent User Interfaces (IUI '14), Tsvi Kuflik et al. (Ed.). ACM, New York, NY, USA, 299--304.

Digital Library

[29]

I. Scott MacKenzie. 2013. Human-computer interaction: An empirical research perspective. Morgan Kaufmann, Waltham (MA).

Digital Library

[30]

Joanna McGrenere, Ronald M. Baecker, and Kellog S. Booth. 2002. An evaluation of a multiple interface design solution for bloated software. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '02), Dennis Wixon (Ed.). ACM, Minneapolis, MN, USA, 163--170.

Digital Library

[31]

Joanna McGrenere and G. Moore. 2000. Are we all in the same "bloat"?. In Proceedings of Graphic Interface 2000 (GI '00), Sidney Fels and Pierre Poulin (Eds.). Lawrence Erlbaum Associates, 187--196.

[32]

Microsoft. 2018. Design Universal Windows Platform (UWP) app: Windows app development. (2018). https://dev.windows.com/en-us/design

[33]

Kawa Nazemi. 2016. Adaptive Semantics Visualization (1st ed. 2016 ed.). Springer, Cham.

Digital Library

[34]

Matthias Peissner and Rob Edlin-White. 2013. User Control in Adaptive User Interfaces for Accessibility. In Human-Computer Interaction -- INTERACT 2013 (Lecture Notes in Computer Science), David Hutchison, Takeo Kanade, Josef Kittler, Jon M. Kleinberg, Friedemann Mattern, John C. Mitchell, Moni Naor, Oscar Nierstrasz, C. Pandu Rangan, Bernhard Steffen, Madhu Sudan, Demetri Terzopoulos, Doug Tygar, Moshe Y. Vardi, Gerhard Weikum, Paula Kotzé, Gary Marsden, Gitte Lindgaard, Janet Wesson, and Marco Winckler (Eds.), Vol. 8117. Springer-Verlag, Berlin, Heidelberg, New York, 623--640.

[35]

Mark S. Sanders and Ernest J. McCormick. 1987. Human factors in engineering and design (6 ed.). McGraw-Hill, New York.

[36]

Anne Treisman and Garry Gelade. 1980. A Feature-Integration Theory of Attention. 12 (1980), 97--136.

[37]

Kritina Holden &. Jill Butler William Lidwell. 2012. Universal Principles of Design, Revised and Updated: 125 Ways to Enhance Usability, Influence Perception, Increase Appeal, Make Better Design Decisions, and Teach through Design. Rockport Publishers.

Cited By

Chiossi FTurgut YWelsch RMayer S(2023)Adapting Visual Complexity Based on Electrodermal Activity Improves Working Memory Performance in Virtual RealityProceedings of the ACM on Human-Computer Interaction10.1145/36042437:MHCI(1-26)Online publication date: 13-Sep-2023
https://dl.acm.org/doi/10.1145/3604243
Zhou ZWang WGuo MWang YGotz D(2023)A Design Space for Surfacing Content Recommendations in Visual Analytic PlatformsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.320944529:1(84-94)Online publication date: Jan-2023
https://doi.org/10.1109/TVCG.2022.3209445
Choi YKim Y(2022)An Adaptive UI Based on User-Satisfaction Prediction in Mixed RealityApplied Sciences10.3390/app1209455912:9(4559)Online publication date: 30-Apr-2022
https://doi.org/10.3390/app12094559
Show More Cited By

Index Terms

On the Influence of Human Factors in Adaptive User Interface Design
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. Laboratory experiments
  2. Interaction design
    1. Interaction design process and methods
      1. User interface design
2. Information systems
  1. World Wide Web
    1. Web searching and information discovery
      1. Personalization

Recommendations

The evaluation of an adaptive user interface model
SAICSIT '10: Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists

User expertise and skill affects the way users interact with software. It is envisaged that an adaptive user interface (AUI) which dynamically changes from a novice user interface (UI) to an expert UI could possibly improve users' performance. Contact ...
Capricorn - an intelligent user interface for mobile widgets
MobileHCI '08: Proceedings of the 10th international conference on Human computer interaction with mobile devices and services

Widgets are embeddable objects that provide easy and ubiquitous access to dynamic information sources, e.g., weather, news or TV program information. Interactions with widgets take place through a so-called widget engine, which is a specialized client-...
Exploring a Design Space of Graphical Adaptive Menus: Normal vs. Small Screens
Special Issue on IUI 2018

Graphical Adaptive Menus are Graphical User Interface menus whose predicted items of immediate use can be automatically rendered in a prediction window. Rendering this prediction window is a key question for adaptivity to enable the end-user to ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

UMAP '18: Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization

July 2018

349 pages

ISBN:9781450357845

DOI:10.1145/3213586

General Chairs:
Tanja Mitrovic
University of Canterbury, New Zealand
,
Jie Zhang
Nanyang Technological University, Singapore
,
Program Chairs:
Li Chen
Hong Kong Baptist University, China
,
David Chin
University of Hawaii, USA

Copyright © 2018 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 the author(s) 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

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 July 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Hessisches Ministerium für Wissenschaft und Kunst

Conference

UMAP '18

Sponsor:

UMAP '18: 26th Conference on User Modeling, Adaptation and Personalization

July 8 - 11, 2018

Singapore, Singapore

Acceptance Rates

UMAP '18 Paper Acceptance Rate 26 of 93 submissions, 28%;

Overall Acceptance Rate 162 of 633 submissions, 26%

Upcoming Conference

UMAP '25

Sponsor:
sigchi
sigchi

33rd ACM Conference on User Modeling, Adaptation and Personalization

June 16 - 19, 2025

New York City , NY , USA

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
436
Total Downloads

Downloads (Last 12 months)77
Downloads (Last 6 weeks)5

Reflects downloads up to 12 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

Chiossi FTurgut YWelsch RMayer S(2023)Adapting Visual Complexity Based on Electrodermal Activity Improves Working Memory Performance in Virtual RealityProceedings of the ACM on Human-Computer Interaction10.1145/36042437:MHCI(1-26)Online publication date: 13-Sep-2023
https://dl.acm.org/doi/10.1145/3604243
Zhou ZWang WGuo MWang YGotz D(2023)A Design Space for Surfacing Content Recommendations in Visual Analytic PlatformsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.320944529:1(84-94)Online publication date: Jan-2023
https://doi.org/10.1109/TVCG.2022.3209445
Choi YKim Y(2022)An Adaptive UI Based on User-Satisfaction Prediction in Mixed RealityApplied Sciences10.3390/app1209455912:9(4559)Online publication date: 30-Apr-2022
https://doi.org/10.3390/app12094559
Domínguez-Báez CMendoza-González RLuna-García HRodríguez-Díaz MLuna-Rosas FMartínez-Romo JCelaya-Padilla JGalván-Tejada JGalván-Tejada CGamboa-Rosales H(2021)A Methodological Process for the Design of Frameworks Oriented to Infotainment User InterfacesSustainability10.3390/su1311598213:11(5982)Online publication date: 26-May-2021
https://doi.org/10.3390/su13115982

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