Web Survey Bibliography
Background: Measuring the student experience is becoming increasingly important in higher education in the UK. Student experience surveys are used as indicators of quality and form the basis of rankings of higher education institutions. They are also used by them as tools to assist their quality enhancement initiatives. However, these surveys frequently suffer from low response rates, which can reduce the reliability and usefulness of their data. The UK Postgraduate Taught Experience Survey (PTES) is a relatively new survey and suffers from a low response rate. As this survey is new, little is known about why students do not respond to it. Purpose: This study aimed to explore the reasons why postgraduate students do not respond to the PTES. Sample: Three hundred and fifty-five postgraduate taught students from four health faculties in one UK higher education institution completed an online survey. Of these, seven participated in one of two focus groups. Design and methods: The online survey was completed both by students who completed the PTES in 2011 and those who did not. This provided us with cross-sectional data to compare both groups' knowledge of PTES and their reasons for completing or not completing it. We used multivariate regression analysis to explore which variables were associated with response to PTES. We led two focus groups to explore the themes that emerged from the survey in more depth. This data was analysed by two researchers using thematic analysis. Results: The cross-sectional data found that students who were not clear about the purpose of PTES were less likely to respond, independent of other potential predictor variables. Focus group data indicated that if postgraduate students felt a stronger connection to the university community they may be more likely to respond to PTES. Conclusions: This study suggests that higher education institutions may wish to review their strategies for advertising student experience surveys to focus more on the purpose rather than their impact.
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Web survey bibliography - 2013 (465)
- The role of gamification in better accessing reality and hence increasing data validity ; 2015; Bailey, P.; Kernohan, H.; Pritchard, G.
- Rewarding the Truth; 2015; Puleston, J.
- Tailored fieldwork design to increase representative household survey response: an experiment in the...; 2015; Luiten, A.; Schouten, B.
- Challenges with Online Research for Couples and Families: Evaluating Nonrespondents and the Differential...; 2015; Busby, D. M.; Yoshida, Ke.
- Do Incentives Commoditize Surveys Or Reinforce The Relationship Economy?; 2014; Murphy, L.
- Is it what you say, or how you say It? An experimental analysis of the effects of invitation wording...; 2014; Fazekas, Z., Wall, M. T., Krouwel, A.
- Asking Sensitive Questions: An Evaluation of the Randomized Response Technique Versus Direct Questioning...; 2013; Wolter, F.; Preisendoerfer, P.
- Developing an Inclusive Web Survey Design for Respondents with Disabilities; 2013; Jagger, J.; Schaad, A.; Davis, As.; Falcone, A. E.
- The Impact of Survey Communications on Response Rates and Response Quality; 2013; Barlas, F. M.; Falcone, A. E.; Bellamy, N. D.; Mack, A. R.
- The Smartphone Way to Collect Survey Data; 2013; Stapleton, C.
- A Glimpse Inside the Mind of a Respondent: Using Paradata to Improve Online Surveys; 2013; Pape, T.; Barron, S.
- Respondent Choice of Survey Mode; 2013; Fuchs, M.
- Mobile-Mostly Internet Users and Noncoverage in Traditional Web Surveys ; 2013; Antoun, C.; Couper, M. P.
- Pret met panels [Fun online]; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- Leuker kunnen wij het wel maken. Online vragenlijst design: standaard matrix of scrollmatrix (We can...; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- Development and validation of a single- item scale for the relative assessment of physical attractiveness...; 2013; Lutz, J.; Kemper, C. J.; Beierlein, C.; etc.
- Accounting for the Effects of Data Collection Method Application to the International Tobacco Control...; 2013; Thompson, M. E.; Huang, Y. C.; Boudreau, C.; Fong, G. T.; van den Putte, B.; Nagelhout, G. E.; Willemsen...
- A dual-frame sampling methodology to address landline replacement in tobacco control research..; 2013; McMillen, R. C.; Winickoff, J. P.; Wilson, K.; Tanski, S.; Klein, J. D.
- User Modeling via Machine Learning and Rule-Based Reasoning to Understand and Predict Errors in Survey...; 2013; Stuart, L. C.
- Measuring Mobile Phone Use: Self-Report Versus Log Data; 2013; Boase, J., Ling, R.
- How Sliders Bias Survey Data; 2013; Sellers, R.
- Does the first impression count? Examining the effect of the welcome screen design on the response rate...; 2013; Haer, R., Meidert, N.
- Survey Research Response Rates: Internet Technology vs. Snail Mail ; 2013; Lanier, P. A., Tanner, J. R., Totaro, M. W., Gradnigo, G.
- The impact of New Zealand's 2008 prohibition of piperazine-based party pills on young people'...; 2013; Sheridan, J., Dong, C. Y., Butler, R., Barnes, J.
- PRM144 – An adaptable methodology for the design, implementation and conduct of a web-based survey...; 2013; Yeomans, K., Kawata, A. K., Bassel, M., Burk, C. T., Daniels, S. R., Wilcox, T. K.
- The relationships among nurses' job characteristics and attitudes toward web-based continuing learning...; 2013; Chiu, Y.-L., Tsai, C.-C., Fan Chiang, C.-Y.
- Surveillance of patients post-endovascular abdominal aortic aneurysm repair (EVAR). A web-based survey...; 2013; Patel, A., Edwards, R., Chandramohan, S.
- How well do volunteer web panel surveys measure sensitive behaviours in the general population, and...; 2013; Erens, B., Burkill, S., Copas, A., Couper, M. P., Conrad, F.
- Tailoring mode of data collection in longitudinal studies; 2013; Kaminska, O., Lynn, P.
- Comparison of Three Modes for a Crime Victimization Survey; 2013; Laaksonen, S., Heiskanen, M.
- Community Life Survey: Summary of web experiment findings; 2013
- Does Stress Increase the Risk of Atopic Dermatitis in Adolescents? Results of the Korea Youth Risk Behavior...; 2013; Kwon, J. A., Lee, M., Park, E.-C., Park, S., Yoo, K.-B.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Understanding Society Innovation Panel Wave 5: results from methodological experiments; 2013; Auspurg, K., Burton, J., Cullinane, C., Delavande, A., Fumagalli, L., Iacovou, M., Jaeckle, A., Kaminska...
- Bringing usability to pretesting of Business Survey Web Forms in Statistics Finland; 2013; Rouhunkoski, J.
- How do we Know Cognitive Interviewing is Any Good?; 2013; Willis, G. B.
- Survey optimisation considerations for Android, Apple and Windows 8 mobile devices; 2013; Owen, R.
- Speeding in Web Surveys: The tendency to answer very fast and its association with straightlining; 2013; Conrad, F. G.; Zhang, Che.
- About the Institute of Public Health - Data aspect; 2013; Zaletel, M.
- Analyzing Paradata to Investigate Measurement Error; 2013; Yan, T., Olson, K.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- Can timestamp analyses show the bottlenecks in web surveys?; 2013; Andreadis, I.
- Timing in a web based survey: an influential factor of the response rate; 2013; Paraschiv, D.-C.
- Achieving Synergy Across Survey Modes: Mail Contact and Web Responses from Address-Based Samples; 2013; Dillman, D. A.
- The Future of Social Media, Sociality, and Survey Research; 2013; Hill, C., Dever, J. A.
- Collecting Diary Data on Twitter; 2013; Richards, A., Dean, E., Cook, S.
- 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.
- Sentiment Analysis: Providing Categorical Insight into Unstructured Textual Data; 2013; Haney, C.
- Social Media, Sociality, and Survey Research; 2013; Hill, C., Dean, E., Murphy, J.