Web Survey Bibliography
In survey research, computer assisted forms of data collection are rapidly replacing paper and pencil methods. At the same time children are becoming important respondents in many large-scale surveys. However, children possess distinctive cognitive and social developmental characteristics, what must be taken into consideration in the research design. There are many problems to be solved when the respondents are children, including problems of language use, literacy and different stages of cognitive development (Scott 2001).
In order to examine data quality collected with computer assisted self administered questionnaires (CASQ) a study among 9 and 10 years old children was conducted. Within the study two hypotheses were tested:
1. “Cognitive skills do have an impact on reliability of data collected by CASQ, but reliability is not lower than in paper and pencil collection mode.”
2. “Computer skills do not have a significant influence on quality of data in CSAQ.”
In order to answer research questions three different databases were used – PIRLS 2001 (Progress in International Reading Literacy Study) (n=3118); TIMSS 2003 (Trends in International Mathematics and Science Study) (n=3126) – both paper and pencil self administered studies, and computer assisted self administered study where several questions from paper and pencil studies were repeated with the intention to compare the results (n=150). All three studies were conducted in a school setting.
Four constructs were analyzed in relation to the following variables: mode of data collection, index of cognitive level, gender and index of computer skills.
The results show that cognitively more sophisticated children give somehow more reliable results, although further analysis showed the differences between groups are not statistically significant.
Reliability analyses were performed to compare data quality of groups of respondents with high and low index of computer use. Although Cronbach’s α is higher for group of respondents who use computers rarely, the difference between two groups is not statistically significant. Missing value analyses also shows, that respondents who use computers more rarely produced less item nonresponse compared to respondents who use computers more often, meaning that children with lower index of computer skills do not produce lower quality data.
General online research (GOR) 2008 (abstract)
Web Survey Bibliography - Conference proceedings (240)
- Unintentional mobile respondents; 2012; Peterson, G.
- Sensitive topics in PC Web and mobile web surveys: Is there a difference?; 2012; Mavletova, A. M., Couper, M. P.
- Metering mobile usage. Insights from global Arbitron mobile trends panel; 2012; Verkasalo, H.
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- An experimental investigation of the effects of noncontingent and contingent incentives in recruiting...; 2012; Lavrakas, P. J., Dennis, J. M., Peugh, J., Shand-Lubbers, J., Lee, E., Peugh, J., Charlebois, O., Murakami...
- The smart(phone) way to collect survey data; 2011; Stapleton, C.
- The next CAPI evolution - completing web surveys on cell-enabled iPads; 2011; Dayton, J., Driscoll, H.
- Self-administered mobile surveys; 2011; Bosnjak, M.
- Online survey research: Findings, Best practices, and future research; 2011
- Moving forward, building an ethics community (Panel statement); 2011; Kenneally, E. et al.
- In search of a new approach to measure newspaper audiences in Canada: The journey continues; 2011; Crassweller, A., Rogers, J., Graves, F., Gauthier, E., Charlebois, O.
- Effects of response format on requalification for recontact studies; 2011; Thomas, R. K.
- A meta-analysis of experiments manipulating progress indicators in Web surveys; 2011; Callegaro, M., Villar, A., Yang, Y.
- Blend, balance, and stabilize respondent sources; 2011; Eggers, M., Drake, E.
- Mode Effect or Question Wording? Measurement Error in Mixed Mode Surveys; 2011; de Leeuw, E. D., Hox, J., Scherpenzeel, A.
- Using a fillable PDF together with SAS ® for questionnaire data; 2010; Donald, E.
- There is an app for that! A review of smartphone apps for marketing research; 2010; Michelson, M.
- The state of online research in the U.S.; 2010; Miller, J.
- Function follows form: Effects of response format on self-reported individuals and household disability...; 2010; Falcone, A. E., Thomas, R. K.
- Address-based sampling. Merits, design & implementation, and review of field statistics; 2010; Fahimi, M.
- A framework for understanding and applying ethical principles in network and security research; 2010; Kenneally, E., Bailey, M., Maughan, D.
- Restructuring and innovations on the survey “capacity of collective tourist accommodation”...; 2010; Santoro, M. T., Staffieri, S.
- An Analyze of the Zero Price Effect on Online Business Performance - An Research Based on the Mobile...; 2010; Liu, Y., Yuan, P.
- Dealing with Nonresponse in Survey Sampling: an Item Response Modeling Approach; 2010; Matei, A.
- Web survey design and usability; 2010; Karakoyun, F., Kurt, A. A.
- Response format effects on measurement of employment; 2009; Thomas, R. K., Dillman, D. A., Smyth, J. D.
- Getting data for (business) statistics: What's new? What's next?; 2009; Snijkers, G.
- Response Mode and Bias Analysis in the IRS’ Individual Taxpayer Burden Survey; 2009; Brick, J. M., Contos, G.,Masken, K.,Nord, R.
- Survey Mode Effects in Two Military Surveys; 2009; Yang, M., Falcone, A. E., Milan, L. M.
- Web based macroseismic survey: fast information exchange and elaboration of seismic intensity effects...; 2009; De Rubeis, V., Sbarra P., Sorrentino, D., Tosi, P.
- The representativeness of the LISS panel ; 2009; Knoef, M., de Vos, K.
- Sample factors that influence data quality; 2008; Gailey, R., Teal, D., Haechrel, E.
- An online panel as a platform for multi-disciplinary research; 2008; Scherpenzeel, A.
- Visual Design Effects on on Respondents Behaviour in Web-Surveys. A Design Experiment; 2008; Greinöcker, A.
- Effects of Privacy Assurances on the Online Measurement of Psychological Constructs; 2008; Witzki, A., Kramer, J.
- Effects of AJAX Technology in Online Questionnaires; 2008; Lütters, H., Westphal, D., Heublein, F.
- How Web 2.0 Technologies Can Become a Valuable Part of Online Research; 2008; Jaron, R.
- Respondent Authenticity - A biometrical approach to authenticate panelists; 2008; Wachter, B., Bender, C.
- Visual Analogue Scales Versus Categorical Scales: Respondent Burden, Cognitive Depth, and Data Quality...; 2008; Funke, F.,Reips, U. -D.
- Not Mixed-Mode but Switch-Mode; 2008; Höglinger, M., Abraham, M., Arpagaus, J.
- The Impact of Cognitive and Computer Skills on Data Quality in Computer Assisted Self Administered Questionnaires...; 2008; Brecko, B. N., Vehovar, V.
- Optimal Contact Strategy in a Mail-and-Web Mixed Mode Survey; 2008; Holmberg, A., Lorenc, B., Werner, P.
- 10 Years of Meinungsplatz.de: Success in the Collection of Data for Targeted Audiences, Such as the...; 2008; Weyergraf, O.
- Self-selection in Online Access Panels: No “Little Difference” in the Recruiting Process...; 2008; Wirth, T.
- Selectivity or Usefulness of Online-Surveys? A Comparison with Data from a Local Population Survey; 2008; Kroll, S., Hüfken, V., Reuband, K.H.
- Mobile Market Research; 2008; Maxl, E.
- Flexible and High-Speed Market Research through Mobile Data Collection & Online Reporting Tool; 2008; Haag, J., Volkmer, H.P.
- Online vs. Offline in Mobile Surveys; 2008; Neubarth, W., Maier, U.
- Gender-of-Interviewer Effects in Video-Enhanced Web Surveys. Results from a Randomized Field-Experiment...; 2008; Fuchs, M.
- The Online Use of Randomized Response Measurements; 2008; Snijders, C., Weesie, J.