Web Survey Bibliography
Due to the increasing complexity of survey work, tablets can provide a strong support system for data enumerators during collection. Software can be written to assist in reminding enumerators
when to skip questions, what kinds of prompts are acceptable to use, or when to abort a survey due to responses provided. It can also ensure that crucial questions are not accidentally skipped
during collection. For survey administrators, the benefits are even more far reaching: Instant access to data, metrics on enumerator pacing, instant data entry with no additional wait time, GPS mapping of dwelling and more. Tangerine, an open source data entry interface developed by RTI International, is the first tablet based data collection software custom-created to record student responses on early grade reading or mathematics assessments, yet flexible enough to capture common survey formats in a range of languages and scripts without requiring programming expertise. Surveys can be collaboratively designed using a simple Web-based tool, the Tangerine wizard, similar to Survey Monkey or Google Forms. Tangerine does not require connectivity during data collection to be usable in low-resource and low-bandwidth environments. At the same time, where connectivity, e.g. via mobile networks is available, the software allows for regular back-up of the data to the central server which in turn allows for immediate review and monitoring of data collection progress.
Conference Homepage (abstract)
Web survey bibliography (4086)
- Use of Smart Phones/Text Messaging to Increase Response Rates; 2013; DuBray, P.
- Designing Surveys for Tablets and Smartphones; 2013; Lakhe, S., Nichols, E. M., Olmsted, M. G., King, T.
- Tablets as Data Entry Interfaces – Solving Data Cleaning and Transcription Issues During Data...; 2013; Costall, A.
- Effects of Response Format on Measurement of Readership; 2013; Thomas, R. K., Cobb, C. L., Baim, J.
- Potential Impact of Modifying the Fielding Time of a Web-Based Survey; 2013; Baum, H. M., Chandonnet, A.
- How Representative are Google Consumer Surveys?: Results From an Analysis of a Google Consumer Survey...; 2013; Krishnamurty, P., Tanenbaum, E., Stern, M. J.
- One Drink or Two: Does Quantity Depicted in an Image Affect Web Survey Responses?; 2013; Charoenruk, N., Stange, M.
- A Comparison Between Screen/Follow Item Format and Yes/No Item Format on a Multi-Mode Federal Survey; 2013; Hernandez,S. J., Arakelyan, S. N., Welch, V. E.
- Using Multiple Modes in Follow-Up Contacts in Random-Digit Dialing Surveys; 2013; Chowdhury, P. P.
- Tablets and Smartphones and Netbooks, Oh My! Effects of Device Type on Respondent Behavior; 2013; Ross, H., Mendelson, J., Lackey, M.
- Impacts of Unit Nonresponse in a Recontact Study of Youth; 2013; Mendelson, J., Viera Jr., L.
- Multi-Mode Survey Administration: Does Offering Multiple Modes at Once Depress Response Rates?; 2013; Newsome, J., Levin, K., Langetieg, P., Vigil, M., Sebastiani, M.
- Responsive Design for Web Panel Data Collection; 2013; Bianchi, A., Biffignandi, S.
- Utilizing the Web in a Multi-Mode Survey; 2013; Venkataraman, L.
- Changing to a Mixed-Mode Design: The Role of Mode in Respondents' Decisions About Participation...; 2013; Collins, D., Mitchell, Ma., Toomes, M.
- Comparing the Effects of Mode Design on Response Rate, Representativeness, and Cost Per Complete in...; 2013; Tully, R.
- Internet Response for the Decennial Census – 2012 National Census Test; 2013; Reiser, C.
- The Effects of Pushing Web in a Mixed-Mode Establishment Data Collection; 2013; Ellis, C.
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Using Paradata to Study Response to Within-Survey Requests; 2013; Sakshaug, J. W.
- Paradata for Coverage Research ; 2013; Eckman, S.
- The smart(phone) way to collect survey data; 2013; Stapleton, C.
- Online Fundraising Essentials, Second Edition; 2013; Stevenson, S. C.
- Tips for Evaluating Online Effectiveness; 2013; Stevenson, S. C.
- The Digital Divide: The internet and social inequality in international perspective; 2013; Ragnedda, M., Muschert, G.
- Survey quality prediction system 2.0; 2013
- Speed (necessarily) doesn't kill: A new way to detect survey satisficing; 2013; Garland, P., Chen, K., Epstein, J., Suh, A.
- Practical tools for designing and weighting survey samples; 2013; Valliant, R. L., Daver, J. A., Kreuter, F.
- Paradata in web surveys; 2013; Callegaro, M.
- Incentive effects; 2013; Goeritz, A.
- A nationwide web-based freight data collection; 2013; Samimi, A., Mohammadian, A., Kawamura, K.
- The E-Interview in Qualitative Research; 2013; Bampton, R., Cowton, C., Downs, Y.
- Methodological Considerations of Qualitative Email Interviews; 2013; Nehls, K.
- Best Practice in Online Survey Research with Sensitive Topics; 2013; Kays, K., Keith, T. L., Broughal, M. T.
- Reducing Response Burden for Enterprises Combining Methods for Data Collection on the Internet; 2013; Vik, T.
- Advancing Research Methods with New Technologies; 2013; Sappleton, N.
- Data Quality in PC and Mobile Web Surveys; 2013; Mavletova, A. M.
- PDAs in socio-economic surveys: instrument bias, surveyor bias or both?; 2013; Escobal, J., Benites, S.
- Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds; 2013; Hasler, B. S., Tuchman, P., Friedman, D.
- Compared to a small, supervised lab experiment, a large, unsupervised web-based experiment on a previously...; 2013; Ryan, R. S., Wilde, M., Crist, S.
- From mixed-mode to multiple devices. Web surveys, smartphone surveys and apps: has the respondent gone...; 2013; Callegaro, M.
- Moving an established survey online – or not?; 2013; Barber, T., Chilvers, D., Kaul, S.
- An approach to selecting online respondents; 2013; Terhanian, G.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Cyborgs vs. Monsters: Assembling Modular Surveys to Create Complete Datasets; 2013; Johnson, E. P., Siluk, L., Tarraf, S.
- Shorter Isn't Always Better; 2013; Burdein, I.
- Internet-Based Recruitment to a Depression Prevention Intervention: Lessons From the Mood Memos Study...; 2013; Morgan, A. J., Jorm, A. F., Mackinnon, A. J.
- Computer science security research and human subjects: Emerging considerations for research ethics boards...; 2013; Buchanan, E. A., Aycock, J., Dexter, S., Dittrich, D., Hvizdak, E. E.
- A standard for test reliability in group research; 2013; Ellis, J. L.
- Addressing Survey Nonresponse Issues: Implications for ATE Principal Investigators, Evaluators, and...; 2013; Welch, W. W., Barlau, A. N.