Web Survey Bibliography
Relevance & Research Question:
Previous research found that the current motivational state of subjects represents an important predictor for the quality of online surveys (e.g. Harper, Raban, Rafaeli & Konstan, 2008). Thus, measuring the motivation in real-time while subjects work on a survey could enable us to provide adaptive motivational cues and improve answer quality. Moreover, automated labelling of answers with motivation measures could help analysing data quality. However, previous methods of measuring current motivation are limited to self-reports or indirect measures like cognitive association tasks (see Touré-Tillery & Fishbach, 2014 for a review) – those methods tend to be biased and time-consuming. As surveys often contain open text answers, we propose to use indices of typing behaviour (e.g. speed, pauses, corrections) as a source of information about current motivation. This study investigates whether analysing the typing behaviour in surveys can help to explain variance of the motivational state and the quality of open text answers.
Methods & Data:
Data acquisition is still in progress. 50 subjects will take part in a correlation study. As a cover story, subjects are asked to evaluate an online learning environment about website programming for about one hour. This includes four open answer tasks (e.g. “How would you change the page design?”) at different time intervals. Before each task, the depending variable current motivation is assessed with 5 items (e.g. “I think, this task is fun”). The answer quality is rated manually including length, content variance and number of propositions. Typing behaviour is recorded by a JavaScript framework. Multiple regression models are used to check for relations between typing indices and motivational states.
Results:
As data acquisition is still in progress, results are not yet available. However, an explorative pre-study revealed medium correlations between typing speed and answer quality (r = -.369, p<.01) as well as between the number of corrections and motivational state (r = .540, p<.01).
Added Value:
Analysing typing behaviour is an unobtrusive, non-reactive, low-cost and objective method that could help predicting motivation and labelling answers in online surveys. This study investigates the practical applicability and theoretical validity of this idea.
Web survey bibliography (4086)
- Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated...; 2016; Lee, S.; McClain, C.; Webster, N.; Han, S.
- Are Final Comments in Web Survey Panels Associated with Next-Wave Attrition?; 2016; McLauchlan, C.; Schonlau, M.
- Estimation and Adjustment of Self-Selection Bias in Volunteer Panel Web Surveys ; 2016; Niu, Ch.
- Facebook, Twitter, & Qr codes: An exploratory trial examining the feasibility of social media mechanisms...; 2016; Gu, L. L.; Skierkowski, D.; Florin, P.; Friend, K.; Ye, Y.
- Sensitive Questions in Online Surveys: An Experimental Evaluation of Different Implementations of the...; 2016; Hoglinger, M.; Jann, B.; Diekmann, A.
- Design and test of a web-survey for collecting observer’s ratings on dairy goats’ behavioural...; 2016; Vieira, A.; Oliveira, M. D.; Nunes, T.; Stilwell, G.
- Análisis de herramientas gratuitas para el diseño de cuestionarios on-line; 2016; Montoya, L. S.; Farran, C. X.; Catala, C. M.
- Participation in an Intensive Longitudinal Study with Weekly Web Surveys Over 2.5 Years; 2016; Barber, J. S.; Kusunoki, Y.; Gatny, H. H.; Schulz, P.
- Helping respondents provide good answers in Web surveys; 2016; Couper, M. P.; Zhang, C.
- Geht’s auch mit der Maus? – Eine Methodenstudie zu Online-Befragungen in der Jugendforschung...; 2016; Heim, R.; Konowalczyk, S.; Grgic, M.; Seyda, M.; Burrmann, U.; Rauschenbach, T.
- Shorter Interviews, Longer Surveys: Optimising the survey participant experience whilst accommodating...; 2016; Halder, A.; Bansal, H. S.; Knowles, R.; Eldridge, J.; Murray, Mi.
- Gamifying. Not all fun and games; 2016; Stubington, P.; Crichton, C.
- Are interviews costing £0.08 a waste of money? Reviewing Google Surveys for Wisdom of the Crowd...; 2016; Roughton, G.; MacKay, I.
- Observations from Twelve Years of an Annual Market Research Technology Survey; 2016; Macer, T.; Wilson, S.
- FocusVision 2015 Annual MR Technology Report; 2016; Macer, T., Wilson, S.
- Last Year Your Answer Was … The Impact of Dependent Interviewing Wording and Survey Factors on...; 2016; Al Baghal, T.
- The Effects of a Delayed Incentive on Response Rates, Response Mode, Data Quality, and Sample Bias in...; 2016; McGonagle, K., Freedman, V. A.
- Can Student Populations in Developing Countries Be Reached by Online Surveys? The Case of the National...; 2016; Langer, A., Meuleman, B., Oshodi, A.-G. T., Schroyens, M.
- The Effects of Vignette Placement on Attitudes Toward Supporting Family Members; 2016; Lau, C. Q., Seltzer, J. A., Bianchi, S. M.
- Comparisons of Online Recruitment Strategies for Convenience Samples: Craigslist, Google AdWords, Facebook...; 2016; Antoun, C., Zhang, C., Conrad, F. G., Schober, M. F.
- Comparing Cognitive Interviewing and Online Probing: Do They Find Similar Results?; 2016; Meitinger, K., Behr, D.
- A new model for concept evaluation; 2016; Allen, D. R.
- Feature phones no barrier to conducting an effective conjoint study ; 2016; de Rooij, R.; Dossin, R.
- A look at the unique data-gathering process behind the Harvard Impact Study; 2016; Vitale, J.
- Are sliders too slick for surveys?; 2016; Buskirk, T. D.
- Research gamification for quality pharmaceutical stakeholder insights; 2016; Mondry, B.; Fink, L.
- The impact of survey duration on completion rates among Millennial respondents ; 2016; Coates, D.; Bliss, M.; Vivar, X.
- SurveyTester from Knowledge Navigators ; 2016; Macer, T.
- Marrying passive and custom data for effective mobile targeting; 2016; King, K.; Stevens, N.
- Simplifying your mobile solution; 2016; Berry, K.
- How to maximize survey response rates ; 2016; DeVall, R.; Colby, C.
- Participation rates of childhood cancer survivors to self-administered questionnaires: a systematic...; 2016; Kilsdonk, E.; Wendel, E.; van Dulmen-den Broeder, E.; van Leeuwen, F.E.; Van Den Berg, M. H.; Jaspers...
- Google's MIDAS Touch: Predicting UK Unemployment with Internet Search Data; 2016; Smith, Pau.
- Patient preference: a comparison of electronic patient-completed questionnaires with paper among cancer...; 2016; Martin, P.; Brown, M.C.; Espin‐Garcia, O.; Cuffe, S.; Pringle, D.; Mahler, M.; Villeneuve, J.;...
- Mixed Mode Research: Issues in Design and Analysis; 2016; Hox, J.; De Leeuw, E. D.; Klausch, L. T.
- Does the Use of Smartphones to Participate in Web Surveys Affect the Survey Experience when Sensitive...; 2016; Toninelli, D.; Revilla, M.
- Device use in web surveys: The effect of differential incentives; 2016; Mavletova, A. M.; Couper, M. P.
- Device Effects - How different screen sizes affect answers in online surveys; 2016; Fisher, B.; Bernet, F.
- Effects of motivating question types with graphical support in multi channel design studies; 2016; Luetters, H.; Friedrich-Freksa, M.; Vitt, SGoldstein, D. G.
- Analyzing Cognitive Burden of Survey Questions with Paradata: A Web Survey Experiment; 2016; Hoehne, J. K.; Schlosser, S.; Krebs, D.
- Why Do Web Surveys Take Longer on Smartphones?; 2016; Couper, M. P.; J. J.Peterson, G. J.
- Do Initial Respondents Differ From Callback Respondents? Lessons From a Mobile CATI Survey; 2016; Vicente, P.; Marques, C.
- Secondary Respondent Consent in the German Family Panel; 2016; Schmiedeberg, C.; Castiglioni, L.; Schroeder, J.
- Online Focus Group Discussion is a Valid and Feasible Mode When Investigating Sensitive Topics Among...; 2016; Wettergren, L.; Eriksson, L. E.; Nilsson, J.; Jarvaeus, A.; Lampic, C.
- A look into the challenges of mixed-mode surveys; 2016; Klausch, L. T.
- The use of online social networks as a promotional tool for self-administered internet surveys; 2016; de Rada, V. D.; Arino, L. V. C; Blasco, M. G
- Optimizing Self-response for the 2020 Census ; 2016; Bentley, M.
- Improving Data Quality in a Web Survey of Youth and Teens ; 2016; Horton, V. M.; Branson, R.; Phillips, B. T.; Fowlkes, E.
- Impact of Field Period Length and Contact Attempts on Representativeness for Web Survey ; 2016; Bertoni, N.; Turakhia, C.; Magaw, R.; Ackermann, A.
- Have You Taken Your Survey Yet? Optimum Interval for Reminders in Web Panel Surveys ; 2016; Kanitkar, K. N.; Liu, D.