research-article

The role of user differences in customization: a case study in personalization for infovis-based content

Authors:

Sébastien Lallé,

Cristina ConatiAuthors Info & Claims

IUI '19: Proceedings of the 24th International Conference on Intelligent User Interfaces

Pages 329 - 339

https://doi.org/10.1145/3301275.3302283

Published: 17 March 2019 Publication History

Abstract

Although there is extensive evidence that personalization of interactive systems can improve the user's experience and satisfaction, it is also known that the two main approaches to deliver personalization, namely via customization or system-driven adaptation, have limitations. In particular, many users do not use customize mechanisms, while adaptation can be perceived as intrusive and opaque. In this paper, we explore an intermediary approach to personalization, namely delivering system-driven support to customization. To this end, we study a customization mechanism allowing to choose the type and amount of information displayed by means of information visualizations in a system for decision making, and examine the impact of user differences on the effectiveness of this mechanism. Our results show that, for the users who did use the customization mechanism, customization effectiveness was impacted by their levels of visualization literacy and locus of control. These results suggest that the customization mechanism could be improved by system-driven assistance to customize depending on the user's level of visualization literacy and locus of control.

Supplementary Material

MP4 File (p329-lalle.mp4)

Download
564.70 MB

References

[1]

G. Abla, E. N. Kim, D. P. Schissel, and S. M. Flanagan. 2010. Customizable scientific web portal for fusion research. Fusion Engineering and Design 85, 3 (July 2010), 603--607.

[2]

G. Abla, E. N. Kim, D. P. Schissel, and S. M. Flanagan. 2010. Customizable scientific web portal for fusion research. Fusion Engineering and Design 85, 3 (July 2010), 603--607.

[3]

Jae-wook Ahn and Peter Brusilovsky. 2013. Adaptive visualization for exploratory information retrieval. Information Processing & Management 49, 5 (2013), 1139--1164.

Digital Library

[4]

William Albert and Thomas Tullis. 2013. Measuring the user experience: collecting, analyzing, and presenting usability metrics. Newnes.

Digital Library

[5]

Nikola Banovic, Fanny Chevalier, Tovi Grossman, and George Fitzmaurice. 2012. Triggering Triggers and Burying Barriers to Customizing Software. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, 2717--2726.

Digital Library

[6]

Michael A. Beam and Gerald M. Kosicki. 2014. Personalized news portals: Filtering systems and increased news exposure. Journalism & Mass Communication Quarterly 91, 1 (2014), 59--77.

[7]

Jeremy Boy, Ronald A. Rensink, Enrico Bertini, and Jean-Daniel Fekete. 2014. A Principled Way of Assessing Visualization Literacy. IEEE Transactions on Visualization and Computer Graphics 20, 12 (2014), 1963--1972.

[8]

Peter Brusilovsky, Jae-wook Ahn, Tibor Dumitriu, and Michael Yudelson. 2006. Adaptive Knowledge-Based Visualization for Accessing Educational Examples. In Proceedings of the 10th International Conference on Information Visualization. IEEE, London, UK, 142--150.

Digital Library

[9]

Andrea Bunt, Cristina Conati, and Joanna McGrenere. 2007. Supporting interface customization using a mixed-initiative approach. ACM Press, 92.

Digital Library

[10]

Emanuele Coluccia, Anna Maria Longoni, and Fabio Ferlazzo. 2005. The Role of Visuo-Spatial Working Memory in map learning. (2005).

[11]

Cristina Conati, Giuseppe Carenini, Dereck Toker, and Sébastien Lallé. 2015. Towards User-Adaptive Information Visualization. In Proceedings of the 29th AAAI Conference on Artificial Intelligence. AAAI Press, Austin, TX, USA, 4100--4106.

Digital Library

[12]

Cristina Conati, Sébastien Lallé, Md. Abed Rahman, and Dereck Toker. 2017. Further Results on Predicting Cognitive Abilities for Adaptive Visualizations. In Proceedings of the 26th International Joint Conference on Artificial Intelligence. AAAI Press, Melbourne, Australia, 1568--1574.

Digital Library

[13]

Cristina Conati and Heather Maclaren. 2008. Exploring the role of individual differences in information visualization. In Proceedings of the working conference on Advanced visual interfaces. ACM, New York, NY, USA, 199--206.

Digital Library

[14]

Ionut Damian, Birgit Endrass, Peter Huber, Nikolaus Bee, and Elisabeth André. 2011. Individualized agent interactions. Motion in games (2011), 15--26.

Digital Library

[15]

Vagner Figueredo de Santana, Rosimeire de Oliveira, Leonelo Dell Anhol Almeida, and Marcia Ito. 2013. Firefixia: An accessibility web browser customization toolbar for people with dyslexia. In Proceedings of the 10th International Cross-Disciplinary Conference on Web Accessibility. ACM, 16.

Digital Library

[16]

Ruth B. Ekstrom and United States Office of Naval Research. 1996. Manual for Kit of Factor Referenced Cognitive Tests. Educational Testing Service.

[17]

Andy Field. 2012. Discovering Statistics Using IBM SPSS Statistics (4. ed ed.). Sage Publications Ltd, London.

Digital Library

[18]

Leah Findlater and Joanna McGrenere. 2004. A Comparison of Static, Adaptive, and Adaptable Menus. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, 89--96.

Digital Library

[19]

Keisuke Fukuda and Edward K. Vogel. 2009. Human Variation in Overriding Attentional Capture. The Journal of Neuroscience 29, 27 (July 2009), 8726--8733.

[20]

Krzysztof Gajos and Daniel S. Weld. 2004. SUPPLE: automatically generating user interfaces. In Proceedings of the 9th international conference on Intelligent user interfaces. ACM, 93--100.

Digital Library

[21]

Krzysztof Z. Gajos and Krysta Chauncey. 2017. The Influence of Personality Traits and Cognitive Load on the Use of Adaptive User Interfaces. In Proceedings of the 22nd International Conference on Intelligent User Interfaces. ACM, 301--306.

Digital Library

[22]

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

Digital Library

[23]

Arin Ghazarian and S. Majid Noorhosseini. 2010. Automatic detection of users' skill levels using high-frequency user interface events. User Modeling and User-Adapted Interaction 20, 2 (June 2010), 109--146.

Digital Library

[24]

Matthew Junghyun Gingerich and Cristina Conati. 2015. Constructing Models of User and Task Characteristics from Eye Gaze Data for User-Adaptive Information Highlighting. In Proceedings of the 29th AAAI Conference on Artificial Intelligence. AAAI Press, Austin, TX, USA, 1728--1734.

Digital Library

[25]

Samuel D. Gosling, Peter J. Rentfrow, and William B. Swann. 2003. A very brief measure of the Big-Five personality domains. Journal of Research in personality 37, 6 (2003), 504--528.

[26]

Tear Marie Green and Brian Fisher. 2010. Towards the Personal Equation of Interaction: The impact of personality factors on visual analytics interface interaction. In 2010 IEEE Symposium on Visual Analytics Science and Technology (VAST). 203--210.

[27]

Kari L. Halsted and James H. (Jamie) Roberts. 2002. Eclipse Help System: An Open Source User Assistance Offering. In Proceedings of the 20th Annual International Conference on Computer Documentation. ACM, New York, NY, USA, 49--59.

Digital Library

[28]

Danial Hooshyar, Seolhwa Lee, YeongWook Yang, Jaechoon Jo, and Heuiseok Lim. 2018. Long-term effects of adaptive customization support on elderly people. Cognition, Technology & Work (Aug. 2018).

[29]

Eric Horvitz. 1999. Principles of mixed-initiative user interfaces. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems. ACM, Pittsburgh, PA, USA, 159--166.

Digital Library

[30]

Dandan Huang, Melanie Tory, Bon Adriel Aseniero, Lyn Bartram, Scott Bateman, Sheelagh Carpendale, Anthony Tang, and Robert Woodbury. 2015. Personal visualization and personal visual analytics. IEEE Transactions on Visualization and Computer Graphics 21, 3 (2015), 420--433.

Digital Library

[31]

Amy Hurst, Scott E. Hudson, and Jennifer Mankoff. 2007. Dynamic Detection of Novice vs. Skilled Use Without a Task Model. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, San Jose, CA, USA, 271--280.

Digital Library

[32]

Gerald Häubl and Valerie Trifts. 2000. Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids. Marketing Science 19, 1 (Feb. 2000), 4--21.

[33]

Anthony Jameson. 2009. Adaptive interfaces and agents. In Human-Computer Interaction: Design Issues, Solutions, and Applications. Vol. 105. CRC Press.

Digital Library

[34]

Samad Kardan and Cristina Conati. 2015. Providing adaptive support in an interactive simulation for learning: An experimental evaluation. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, Seoul, South Korea, 3671--3680.

Digital Library

[35]

Heather Kennedy-Eden and Ulrike Gretzel. 2012. A taxonomy of mobile applications in tourism. (2012).

[36]

Sébastien Lallé, Cristina Conati, and Giuseppe Carenini. 2017. Impact of Individual Differences on User Experience with a Visualization Interface for Public Engagement. In Proceedings of the 2nd International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments (in conjunction with UMAP). ACM, Bratislava, Slovakia, 247--252.

Digital Library

[37]

Wendy E. Mackay. 1991. Triggers and Barriers to Customizing Software. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, 153--160.

Digital Library

[38]

Udi Manber, Ash Patel, and John Robison. 2000. Experience with personalization of Yahoo! Commun. ACM 43, 8 (2000), 35--39.

Digital Library

[39]

Sampada Marathe and S. Shyam Sundar. 2011. What drives customization?: control or identity?. In Proceedings of the SIGCHI conference on human factors in computing systems. ACM, 781--790.

Digital Library

[40]

Kawa Nazemi, Reimond Retz, Jürgen Bernard, Jörn Kohlhammer, and Dieter Fellner. 2013. Adaptive Semantic Visualization for Bibliographic Entries. In Advances in Visual Computing. Springer, Berlin, Heidelberg, 13--24.

[41]

Reinhard Oppermann and Helmut Simm. 1994. Adaptability: User-initiated individualization. Adaptive User Support-Ergonomic Design of Manually and Automatically Adaptable Software. Hillsdale, New Jersey (1994).

Digital Library

[42]

Alvitta Ottley, Huahai Yang, and Remco Chang. 2015. Personality as a Predictor of User Strategy: How Locus of Control Affects Search Strategies on Tree Visualizations. ACM Press, 3251--3254.

Digital Library

[43]

Stanley R. Page, Todd J. Johnsgard, Uhl Albert, and C. Dennis Allen. 1996. User customization of a word processor. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 340--346.

Digital Library

[44]

Leysia Palen. 1999. Social, individual and technological issues for groupware calendar systems. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems. ACM, 17--24.

Digital Library

[45]

Peter Pawlowski. 2010. Basic Player Whose Appearance and Functions can be Customized Freely. Windows Forest, Japan, Jan 12 (2010), 3.

[46]

Antoine Ponsard and Joanna McGrenere. 2016. Anchored customization: anchoring settings to the application interface to afford customization. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 4154--4165.

Digital Library

[47]

Julian B. Rotter. 1966. Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs: General and Applied 80, 1 (1966), 1--28.

[48]

Batul Saati, May Salem, and Willem-Paul Brinkman. 2005. Towards customized user interface skins: investigating user personality and skin colour. Proceedings of HCI 2005 2 (2005), 89--93.

[49]

Shoshana Shiloh, Shelly Koren, and Dan Zakay. 2001. Individual differences in compensatory decision-making style and need for closure as correlates of subjective decision complexity and difficulty. Personality and Individual Differences 30, 4 (March 2001), 699--710.

[50]

Harold Soh, Scott Sanner, Madeleine White, and Greg Jamieson. 2017. Deep Sequential Recommendation for Personalized Adaptive User Interfaces. In Proceedings of the 22Nd International Conference on Intelligent User Interfaces. ACM, New York, NY, USA, 589--593.

Digital Library

[51]

Cheri Speier. 2006. The influence of information presentation formats on complex task decision-making performance. International Journal of Human-Computer Studies 64, 11 (2006), 1115--1131.

Digital Library

[52]

S. Shyam Sundar and Sampada S. Marathe. 2010. Personalization versus Customization: The Importance of Agency, Privacy, and Power Usage. Human Communication Research 36, 3 (July 2010), 298--322.

[53]

Jieun Sung, Torger Bjornrud, Yu-hao Lee, and D. Wohn. 2010. Social network games: exploring audience traits. In CHI'10 Extended Abstracts on Human Factors in Computing Systems. ACM, 3649--3654.

Digital Library

[54]

Dereck Toker, Cristina Conati, Giuseppe Carenini, and Mona Haraty. 2012. Towards adaptive information visualization: on the influence of user characteristics. In Proceedings of the 20th International Conference on User Modeling, Adaptation, and Personalization. Springer, Montreal, Canada, 274--285.

Digital Library

[55]

Dereck Toker, Ben Steichen, Matthew Gingerich, Cristina Conati, and Giuseppe Carenini. 2014. Towards Facilitating User Skill Acquisition-Identifying Untrained Visualization Users through Eye Tracking. In Proceedings of the 2014 international conference on Intelligent user interfaces. ACM.

Digital Library

[56]

Gwo-Hshiung Tzeng and Jih-Jeng Huang. 2011. Multiple Attribute Decision Making: Methods and Applications. CRC Press. Google-Books-ID: _C7n1ar4f8IC.

[57]

Maria C. Velez, Deborah Silver, and Marilyn Tremaine. 2005. Understanding visualization through spatial ability differences. In Proceedings of the IEEE Conference on Visualization. IEEE, Minneapolis, MN, USA, 511--518.

[58]

Emily Wall, Subhajit Das, Ravish Chawla, Bharath Kalidindi, Eli T. Brown, and Alex Endert. 2018. Podium: Ranking data using mixed-initiative visual analytics. IEEE transactions on visualization and computer graphics 24, 1 (2018), 288--297.

[59]

Michaela Weiss and Norbert Heidenbluth. 2012. Future chances of software customization: an empirical evaluation. In Proceedings of the Seventh International Conference on Software Engineering Advances. Lisbon/Portugal.

[60]

Chunlei Wu, Camilo Orozco, Jason Boyer, Marc Leglise, James Goodale, Serge Batalov, Christopher L. Hodge, James Haase, Jeff Janes, Jon W. Huss, and others. 2009. BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources. Genome biology 10, 11 (2009), R130.

[61]

Michelle X. Zhou and Vikram Aggarwal. 2004. An optimization-based approach to dynamic data content selection in intelligent multimedia interfaces. In Proceedings of the 17th annual ACM symposium on User interface software and technology. ACM, 227--236.

Digital Library

[62]

Caroline Ziemkiewicz, R. Jordan Crouser, Ashley Rye Yauilla, Sara L. Su, William Ribarsky, and Remeo Chang. 2011. How locus of control influences compatibility with visualization style. In Proceedings of the IEEE Conference on Visual Analytics Science and Technology. IEEE, Providence, RI, USA, 81--90.

Cited By

Alves SCosta RMontague KGuerreiro T(2024)Citizen-Led Personalization of User Interfaces: Investigating How People Customize Interfaces for Themselves and OthersProceedings of the ACM on Human-Computer Interaction10.1145/36869858:CSCW2(1-23)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686985
DOĞAN EKAZANÇOĞLU İ(2023)ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMAENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMAJournal of Business in The Digital Age10.46238/jobda.1299432Online publication date: 30-Nov-2023
https://doi.org/10.46238/jobda.1299432
Tomasi SLiu JCheng FHan C(2023)The role of individual characteristics: How thinking style and domain expertise affect performances on visualizationInformation Visualization10.1177/1473871623116718022:3(265-276)Online publication date: 12-Apr-2023
https://doi.org/10.1177/14738716231167180
Show More Cited By

Index Terms

The role of user differences in customization: a case study in personalization for infovis-based content
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User studies
  2. Visualization
    1. Visualization application domains
      1. Information visualization

Recommendations

Understanding the User Perception and Experience of Interactive Algorithmic Recourse Customization
Generating actionable algorithmic recourse requires understanding each user’s preferences. Users provide their relevant information, and the system uses it to generate recourse that can be easily followed by individual users. To gain insight into users’ ...
QoS customization in distributed object systems
Special issue: Middleware

Applications built on networked collections of computers are increasingly using distributed object platforms such as CORBA, Java Remote Method Invocation (RMI), and DCOM to standardize object interactions. With this increased use comes the increased ...
Heterogeneity in Customization of Recommender Systems By Users with Homogenous Preferences
CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

Recommender systems must find items that match the heterogeneous preferences of its users. Customizable recommenders allow users to directly manipulate the system's algorithm in order to help it match those preferences. However, customizing may demand a ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

IUI '19: Proceedings of the 24th International Conference on Intelligent User Interfaces

March 2019

713 pages

ISBN:9781450362726

DOI:10.1145/3301275

General Chairs:
Wai-Tat Fu,
Shimei Pan,
Program Chairs:
Oliver Brdiczka,
Polo Chau,
Gaelle Calvary

Copyright © 2019 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

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 March 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

IUI '19

Sponsor:

IUI '19: 24th International Conference on Intelligent User Interfaces

March 17 - 20, 2019

California, Marina del Ray

Acceptance Rates

IUI '19 Paper Acceptance Rate 71 of 282 submissions, 25%;

Overall Acceptance Rate 746 of 2,811 submissions, 27%

Upcoming Conference

IUI '25

Sponsor:
sigai
sigai

30th International Conference on Intelligent User Interfaces

March 24 - 27, 2025

Cagliari , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

21
Total Citations
View Citations
658
Total Downloads

Downloads (Last 12 months)75
Downloads (Last 6 weeks)8

Reflects downloads up to 09 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Alves SCosta RMontague KGuerreiro T(2024)Citizen-Led Personalization of User Interfaces: Investigating How People Customize Interfaces for Themselves and OthersProceedings of the ACM on Human-Computer Interaction10.1145/36869858:CSCW2(1-23)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686985
DOĞAN EKAZANÇOĞLU İ(2023)ENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMAENDÜSTRİYEL PAZARDA SOHBET ROBOTUNUN KULLANIMINA YÖNELİK NİTEL BİR ARAŞTIRMAJournal of Business in The Digital Age10.46238/jobda.1299432Online publication date: 30-Nov-2023
https://doi.org/10.46238/jobda.1299432
Tomasi SLiu JCheng FHan C(2023)The role of individual characteristics: How thinking style and domain expertise affect performances on visualizationInformation Visualization10.1177/1473871623116718022:3(265-276)Online publication date: 12-Apr-2023
https://doi.org/10.1177/14738716231167180
Alsayahani H(2023)Overcoming Customisation Challenges in Information DashboardsProceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization10.1145/3565472.3595646(285-289)Online publication date: 18-Jun-2023
https://dl.acm.org/doi/10.1145/3565472.3595646
Kunkel JZiegler J(2023)A comparative study of item space visualizations for recommender systemsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2022.102987172:COnline publication date: 9-Mar-2023
https://dl.acm.org/doi/10.1016/j.ijhcs.2022.102987
Mosconi Gde Carvalho ASyed HRandall DKarasti HPipek V(2023)Fostering Research Data Management in Collaborative Research Contexts: Lessons learnt from an ‘Embedded’ Evaluation of ‘Data Story’Computer Supported Cooperative Work10.1007/s10606-023-09467-632:4(911-949)Online publication date: 15-May-2023
https://dl.acm.org/doi/10.1007/s10606-023-09467-6
Alves TRamalho BGonçalves DHenriques-Calado JGama S(2023)Leveraging Conscientiousness-Based Preferences in Information Visualization DesignVisualization Psychology10.1007/978-3-031-34738-2_13(293-330)Online publication date: 7-Nov-2023
https://doi.org/10.1007/978-3-031-34738-2_13
Deja J(2022)Piano Learning and Improvisation through Adaptive Visualisation and Digital AugmentationCompanion Proceedings of the 2022 Conference on Interactive Surfaces and Spaces10.1145/3532104.3571464(41-45)Online publication date: 20-Nov-2022
https://dl.acm.org/doi/10.1145/3532104.3571464
Satkowski MKessler FNarciss SDachselt R(2022)Who benefits from Visualization Adaptations? Towards a better Understanding of the Influence of Visualization Literacy2022 IEEE Visualization and Visual Analytics (VIS)10.1109/VIS54862.2022.00027(90-94)Online publication date: Oct-2022
https://doi.org/10.1109/VIS54862.2022.00027
Alves TDias CGoncalves DGama SHenriques-Calado J(2022)How Personality and Visual Channels Affect Insight Generation2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)10.1109/BELIV57783.2022.00010(47-55)Online publication date: Oct-2022
https://doi.org/10.1109/BELIV57783.2022.00010
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