Web Survey Bibliography
Since the late 1990s theory drawn from the vision sciences and Gestalt psychology has guided the visual design of questionnaires. A considerable amount of research has been conducted that shows that altering questionnaire visual design can change response distributions and data quality (Dillman, Smyth, and Christian 2009; Jenkins and Dillman 1995; Tourangeau, Couper, &
Conrad 2004). However, this research is limited in what it can tell us about how different visual designs influence responses. In other words, the evidence for how visual design matters is largely circumstantial. Eye-tracking technology gives us the opportunity to overcome this challenge. A handful of studies have used eye tracking to better understand how respondents see and process a questionnaire (Galesic et al.2008; Lenzer, Kaczmirek, and Galesic 2011). In this paper, we will explore how visual design in response options assists respondents in processing survey questions. Specifically, we will analyze eye-tracking data to examine the effects of Web survey response option experiments that include symbolic language, grid response options and the use of single and double columns. Preliminary evidence from the lab shows that the addition of smiley faces to a Likert scale cause respondents to slow down when processing the given response options. By observing how respondents actually view the different versions of the questionnaire and visual aids, this study will contribute to our understanding of how and why visual design influences responses and will shed light on best practices for questionnaire design.
Conference Homepage (abstract)
Web survey bibliography (95)
- Virtual reality meets sensory research; 2017; Depoortere, L.
- Methods for Evaluating Respondent Attrition in Web-Based Surveys; 2016; Hochheimer, C. J.; Sabo, R. T.; Krist, A. H.; Day, T.; Cyrus, J.; Woolf, S. H.
- Exploration of Methods for Blending Unconventional Samples with Traditional Probability Samples; 2016; Gellar, J.; Zhou, H.; D.; Sinclair, M. D.
- Ratio of Vector Lengths as an Indicator of Sample Representativeness ; 2016; Shin, H. C.
- Online and Social Media Data As an Imperfect Continuous Panel Survey; 2016; Diaz, F.; Garmon, F.; Hofman, J. K.; Kiciman, E.; Rothschild, D.
- Validating self-reported mobile phone use in adults using a newly developed smartphone application; 2015; Goedhart, G., Kromhout, H., Wiart, J., Vermeulen, R.
- Innovative Uses of Paradata Across Diverse Contexts ; 2015; Cheung, G.; Pennell, B.-E.
- Build your own social network laboratory with Social Lab: a tool for research in social media; 2014; Garaizar, P., Reips, U.-D.
- Picking up the Bread Crumbs: Holistic Insights from Social Media; 2014; Souda, P.
- Survey optimisation considerations for Android, Apple and Windows 8 mobile devices; 2013; Owen, R.
- Second Life as a Survey Lab: Exploring the Randomized Response Technique in a Virtual Setting; 2013; Richards, A., Dean, E.
- Virtual Cognitive Interviewing Using Skype and Second Life; 2013; Dean, E., Head, B., Swicegood, J. E.
- Assessing Nonresponse Bias in the Green Technologies and Practices Survey; 2013; Meekins, B., Sverchkov, M., Stang, S.
- Why Big Data is a Small Idea…and Why You Shouldn’t Worry So Much; 2013; Needel, S.
- Doing real time research: Opportunities and challenges; 2013; Back, L., Lury, C., Zimmer, R.
- Digital technology and data collection; 2013; Henriksen, B., Jewitt, C., Price, S., Sakr, M.
- Effects of Self-Awareness on Disclosure During Skype Survey Interviews; 2013; Feuer, S., Schober, M. F.
- Cognitive Interviewing in Online Modes: a Comparison of Data Collected in Second Life and Skype; 2013; Swicegood, J. E., Head, B., Dean, E., Keating, M.
- Effects of Displaying Videos on Measurement in a Web Survey; 2013; Mendelson, J., Gibson, J. L., Romano Bergstrom, J. C.
- Classifying Mouse Movements to Predict Respondent Difficulty; 2013; Horwitz, R.
- Are You Seeing What I am Seeing? Exploring Response Option Visual Design Effects With Eye-Tracking; 2013; Libman, A., Smyth, J. D., Olson, K.
- Survey Reminder Method Experiment: An Examination of Cost Efficiency and Reminder Mode Salience in the...; 2013; Anderson, M., Rogers, B., CyBulski, K., Hall, J. W., Alderks, C. E., Milazzo-Sayre, L.
- Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds; 2013; Hasler, B. S., Tuchman, P., Friedman, D.
- From mixed-mode to multiple devices. Web surveys, smartphone surveys and apps: has the respondent gone...; 2013; Callegaro, M.
- Internet-Mediated Technologies and Mixed Methods Research; Problems and Prospects; 2012; Hesse-Biber, S.; Griffin, A. J.
- An Introduction to Using Video for Research; 2012; Jewitt, C.
- Online Surveys Aren't Just for Computers Anymore! Exploring Potential Mode Effects between Smartphone...; 2012; Buskirk, T. D., Andrus, C.
- Smartphone Apps and User Engagement: Collecting Data in the Digital Era; 2012; Link, M. W.
- Specific mixed-mode methodology to reach sensory disabled people in quantitative surveys; 2012; Fontaine, S.
- Facing The Future Webcams as a survey tool in China; 2012; Gordon, A., Llewellyn, T., Gu, E.
- Comfortable in the new medium: How online qual can benefit from our share-happy culture ; 2012; Rubenstein, P.
- Using Collaborative Web Technology to Construct the Health Information National Trends Survey; 2012; Moser, R. P., Beckjord, E. B., Finney Rutten, L. J., Blake, K., Hesse, B. W.
- The Representativity of Web Surveys of the General Population compared to Traditional Modes and Mixed...; 2012; Klausch, L. T., Schouten, B., Hox, J.
- Time use data collection using Smartphones: Results of a pilot study among experienced and inexperienced...; 2012; Scherpenzeel, A., Sonck, N., Fernee, H., Morren, Me.
- Using Webinar Polls to Collect Online Survey Data: The Case of a Behavioral Finance Problem; 2012; Sahu, C.
- The Game Experiments: Researching how gaming techniques can be used to improve the quality of feedback...; 2011; Sleep, D., Puleston, J.
- The benefits and constraints of e-mail interviews and discussions as methods of accessing valid data; 2011; Roberts, An.
- Facial imaging: The new face of online survey research; 2011; Gordon, A., McCallum, D., Sorci, M., Llewellyn, T.
- On Affordances and Technological Intersubjectivity; 2011; Vatrapu, R.
- Building online communities; 2011; Mlačić, B., Milas, G., Mikloušić, I.
- Eye Tracking in testing questionnaires: What’s the added value?; 2011; Tries, S.
- Video enhanced web survey; 2011; Fuchs, M., Kunz, T., Gebhard, F.
- Engagement, Consistency, Reach – why the Technology Landscape Precludes All Three; 2011; Johnson, A., Rolfe, G.
- Twitter mood predicts the stock market.; 2011; Bollen, J., Mao, H., Zeng, X.-J.
- Web based CATI on Amazon Elastic Compute Cloud and VirtualBox using queXS; 2011; Zammit, A.
- Web/Cloud Based CATI Using queXS; 2011; Zammit, A.
- Partnership-Driven Resources to Improve and Enhance Research (PRIMER): A Survey of Community-Engaged...; 2011; Dolor, R. J., Greene, S. M., Thompson, E., Baldwin, L.-M., Neale, A. V.
- Weaving the Web into Personal Communication Networks: A Mobile Phone Based Study of Smartphone Users; 2011; Kobayashi, T., Boase, J.
- Different functioning of rating scale formats – results from psychometric and physiological experiments...; 2011; Koller, M., Salzberger, T.
- Measurement invariance in training evaluation: Old question, new context; 2011; P., Gissel, A., Stoughton, J. W., Whelan, T. J.Clark, A. P.