Xing Huang
ABSTRACT
In self-tracking applications, data visualizations play a fundamental role in delivering efficient information and creating personalized user experiences. Literature consistently indicates that data visualization is a powerful tool to make data persuasive and improve motivation. However, how to leverage different data visualizations to boost motivation remains largely unknown. In this study, the researcher explores the effects of different data visualizations on user motivation within self-tracking mobile applications. Through design space analysis and semi-structured interviews, the researcher defines a set of design factors that impact users’ exercise motivation at different levels of exercise adoption. Based on these factors, the researcher delivers a set of practical design suggestions for design practitioners and people who create visualizations for large data sets.
- Sharma, A., Madaan, V., and Petty, F. D. 2006. Exercise for mental health. Primary care companion to the Journal of clinical psychiatry, 8(2), 106. https://doi.org/10.4088/pcc.v08n0208a Google Scholar
- Parker, K., Uddin, R., Ridgers, N. D., Brown, H., Veitch, J., Salmon, J., Timperio, A., Sahlqvist, S., Cassar, S., Toffoletti, K., Maddison, R., and Arundell, L. 2021. The Use of Digital Platforms for Adults' and Adolescents' Physical Activity During the COVID-19 Pandemic (Our Life at Home): Survey Study. Journal of medical Internet research, 23(2), e23389. https://doi.org/10.2196/23389 Google ScholarCross Ref
- Feng, S., Mäntymäki, M., Dhir, A., and Salmela, H. 2021. How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review. J Med Internet Res. 2021;23(9): e25171. doi: 10.2196/25171 Google Scholar
- Budd, J., Miller, B.S., Manning, E.M. 2020. Digital technologies in the public-health response to COVID-19. Nat Med 26, 1183–1192. https://doi.org/10.1038/s41591-020-1011-4Google ScholarCross Ref
- Sullivan, A. N., and Lachman, M. E. 2017. Behavior Change with Fitness Technology in Sedentary Adults: A Review of the Evidence for Increasing Physical Activity. Frontiers in public health, 4, 289. https://doi.org/10.3389/fpubh.2016.00289 Google Scholar
- Kosara, R., Cohen, S., Cukier, J., and Wattenberg, M. 2009. Panel: Changing the world with visualization. In IEEE Visualization Conference Compendium. Google Scholar
- Mason, S., and Azzam, T. 2019. In Need of an Attitude Adjustment? The Role of Data Visualization in Attitude Change and Evaluation Influence. American Journal of Evaluation, 40(2), 249–267. https://doi.org/10.1177/1098214018778808Google ScholarCross Ref
- Kostelnick, C., 2008. "The Visual Rhetoric of Data Displays: The Conundrum of Clarity*," in IEEE Transactions on Professional Communication, vol. 51, no. 1, pp. 116-130, doi: 10.1109/TPC.2007.914869Google Scholar
- Pandey, A. V., Manivannan, A., Nov, O., Satterthwaite, M., and Bertini, E. 2014. The persuasive power of data visualization. IEEE transactions on visualization and computer graphics, 20(12), 2211-2220. 31 Dec. 2014. doi: 10.1109/TVCG.2014.2346419Google Scholar
- Tversky, A., and Kahneman, D. 1981. The framing of decisions and the psychology of choice. science, 211(4481), 453-458. Google Scholar
- King, D., Greaves, F., Exeter, C., and Darzi, A. 2013. ‘Gamification’: influencing health behaviours with games. Journal of the Royal Society of Medicine, 106(3), 76-8. Google ScholarCross Ref
- Card, Stuart K., Mackinlay, Jock., and Shneiderman, Ben., 1999. Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann, San Francisco. Google ScholarDigital Library
- Sorapure, Madeleine., 2019. Text, Image, Data, Interaction: Understanding Information Visualization. Computers and Composition, Volume 54. ISSN 8755-4615. https://doi.org/10.1016/j.compcom.2019.102519.Google Scholar
- Ware, C. 2012. Information Visualization: Perception for Design. Journal of Software Engineering and Applications, Vol.9 No.7. Elsevier.Google Scholar
- Few, S. 2009. Now You See It: Simple Visualization Techniques for Quantitative Analysis (1st. ed.). Analytics Press, Oakland, CA, USA.Google Scholar
- Clark, R. C., and Mayer, R. E. 2003. e-learning and the science of instruction. San Francisco: Jossey-Bass.Google Scholar
- Bilbokaite, R. 2015. Effects of computer based visualization on students' cognitive processes in education process. Society Integration Proceedings of the International Scientific Conference, doi: 10.17770/sie2015vol4.417Google ScholarCross Ref
- Viegas, F. B., Wattenberg, M., Van Ham, F., Kriss, J., and McKeon, M., 2007. "ManyEyes: a Site for Visualization at Internet Scale," in IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1121-1128, Nov.-Dec. 2007, doi: 10.1109/TVCG.2007.70577Google ScholarDigital Library
- Dörk, M., Feng, P., Collins, C., and Carpendale, S. 2013. Critical InfoVis: exploring the politics of visualization. In CHI'13 Extended Abstracts on Human Factors in Computing Systems (pp. 2189-2198).Google Scholar
- Dick, M. 2013. Interactive Infographics and News Values. Digital Journalism. (Ahead-of-print), pp.1-17.Google Scholar
- C. A. Welhausen. 2002. "Precarious Data: Crack, Opioids, and Enacting a Social Justice Ethic in Data Visualization Practice," in IEEE Transactions on Professional Communication, vol. 65, no. 1, pp. 50-69, March 2022, doi: 10.1109/TPC.2022.3144826.Google ScholarCross Ref
- C. Lauer and S. O'Brien. 2020. "How People Are Influenced by Deceptive Tactics in Everyday Charts and Graphs," in IEEE Transactions on Professional Communication, vol. 63, no. 4, pp. 327-340, Dec. 2020, doi: 10.1109/TPC.2020.3032053.Google ScholarCross Ref
- Lambrecht, K. 2021. Tracking the Differentiation of Risk: The Impact of Subject Framing in CDC Communication Regarding COVID-19. Journal of Business & Technical Communication, 35(1), 94-100.Google ScholarCross Ref
- Richards, D. 2016. Helping Local Residents Make Informed Decisions with Interactive Risk Visualization Tools. SIGDOC ’16: The 34th ACM International Conference on the Design of Communication Proceedings. New York: ACM.Google ScholarDigital Library
- Velázquez-Iturbide, J. Á., Hernán-Losada, I., and Paredes-Velasco, M. 2017. Evaluating the effect of program visualization on student motivation. IEEE Transactions on Education, 60(3), 238-245.Google ScholarDigital Library
- Park, S., Bakemeier, B., Flaxman, A., and Schultz, M. 2014. Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review. Informatics for Health and Social Care, https://doi.org/10.1080/17538157.2021.1982949Google Scholar
- Eberhard, K. 2021. The effects of visualization on judgment and decision-making: a systematic literature review. Manag Rev Q. https://doi.org/10.1007/s11301-021-00235-8Google Scholar
- Hullman, J., and Diakopoulos, N. 2011. Visualization rhetoric: Framing effects in narrative visualization. IEEE Transactions on Visualization and Computer Graphics, 17(12), 2231-2240.Google ScholarDigital Library
- Deci, E. L., and Ryan, R. M. 2008. Self-Determination Theory: A Macrotheory of Human Motivation, Development, and Health. Canadian Psychology, Vol. 49, No. 3, p. 182-185.Google ScholarCross Ref
- Fishbein, M., and Ajzen, I. 1975. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.Google Scholar
- Ajzen, I. 1985. From intentions to actions: A theory of planned behavior. In J. Kuhi & J. Beckmann (Eds.), Action-control: From cognition to behavior (pp. 11ó39). Heidelberg: Springer.Google Scholar
- Ryan, R. M., and Deci, E. L. 2017. Self-determination theory: Basic psychological needs in motivation, development, and wellness. The Guilford Press. https://doi.org/10.1521/978.14625/28806 Google Scholar
- Teixeira PJ, Carraça EV, Markland D, Silva MN, Ryan RM. 2012. Exercise, physical activity, and self-determination theory: a systematic review. Int J Behav Nutr Phys Act. 2012 Jun 22; 9:78. doi: 10.1186/1479-5868-9-78. PMID: 22726453; PMCID: PMC3441783.Google Scholar
- Schwarzer, Ralf. 2003. On the Assessment and Analysis of Variables in the Health Action Process Approach: Conducting an Investigation. http://userpage.fu-berlin.de/gesund/hapa_web.pdfGoogle Scholar
- Chiu, C.Y. 2011. The health action process approach as a motivational model for physical activity self-management for people with multiple sclerosis: a path analysis. Rehabilitation Psychology. Vol.56., p.171-181.Google ScholarCross Ref
- Schwarzer, R. 2008. Modeling health behavior change: How to predict and modify the adoption and maintenance of health behaviors. Applied Psychology: An International Review, 57(1), 1-29.Google ScholarCross Ref
- Schwarzer, R., Lippke, S., and Luszczynska, A. 2011. Mechanisms of health behavior change in persons with chronic illness or disability: The health action process approach (HAPA). Rehabilitation Psychology, 56, 161-170. doi: 10.1037/a0024509Google ScholarCross Ref
- Eberhart, C. 2014. A statistical analysis of the apple app store. http://blog.scottlogic.com/2014/03/20/app-store-analysis.htmlGoogle Scholar
- Erica L. Olmsted-Hawala, Elizabeth D. Murphy, Sam Hawala, and Kathleen T. Ashenfelter. 2010. Think-aloud protocols: a comparison of three think-aloud protocols for use in testing data-dissemination web sites for usability. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). Association for Computing Machinery, New York, NY, USA, 2381–2390. https://doi.org/10.1145/1753326.1753685Google ScholarDigital Library
- Levin, I. P., and Gaeth, G. J. 1988. How consumers are affected by the framing of attribute information before and after consuming the product. Journal of Consumer Research, 15(3), 374–378. https://doi.org/10.1086/209174Google Scholar
- Neff, G., and Nafus, D. 2016. Title of work: Making sense of data. The Self-Tracking. The MIT Press. 70-93.Google Scholar
- Choe, E. K., Lee, B., and Schraefel, M. C. 2015. Characterizing visualization insights from quantified selfers' personal data presentations. IEEE Computer Graphics and Applications. P.28-37.Google Scholar
- Cairo, A. 2013. The functional art: An introduction to information graphics and visualization. New Riders Publishing, CA.Google Scholar
- Azevedo, R., Millar, G. C., Taub, M., Mudrick, N., Bradbury, A. E., and Price, M. J. 2017. Using data visualizations to foster emotion regulation during self-regulated learning with advanced learning technologies: a conceptual framework. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference (LAK '17). Association for Computing Machinery, New York, NY, USA, 444–448. https://doi.org/10.1145/3027385.3027440Google ScholarDigital Library
Index Terms
- Data Visualization Design Strategies for Promoting Exercise Motivation in Self-Tracking Applications
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