Web Survey Bibliography
Title Non-response in evaluation of teaching
Author Brinkmoeller, B.; Forthmann, B.; Thielsch, M.
Year 2016
Access date 29.04.2016
Presentation PDF (527KB)
Abstract
Relevance & Research Question
Student evaluations of teaching (SET) gain more and more importance for university teaching, especially web-based SETs. To guarantee the validity of SET and to avoid sample-errors high response rates are necessary – which cannot always be reached. This study investigates different factors, which might give some explanations for nonresponse in SETs. We examined the social exchange-theory, salience, opportunity costs, survey fatigue and the survey mode (online vs. paper-pencil).
Methods and data
We contacted student representatives of 48 universities, additional student groups in social media, and sent approx. 900 invitations via the online-panel PsyWeb. The web-based survey was available for about four months. Participants provided reasons for non-response, information about response behavior, and attitudes. A total of 490 participants (69.59 % female; age: M = 24.10, SD = 4.07) were included in the final sample.
Results
First, our results show a significant influence of social exchange on responding in SET (Δ R²=.069, p < .001). Also the influence of salience (ΔR²=.201, p < .001) and survey fatigue (ΔR²= .078, p < .001) show significant influences on the participation in SETs. No significant effects were found for opportunity costs (ΔR² = .005, p = .166) as well as for the survey mode (ΔR²= .004, p = .209).
Added value
The results of our study can be helpful for online researchers and evaluation managers in reducing non-response. Notably, our findings stress the importance of communication between students: It influences a student’s evaluation behavior if a fellow student evaluates all of his or her lectures and courses. Thus, universities should indicate how many students take part in a current SET to motivate even more students. Furthermore, it is helpful to increase the students’ identification with their own university and SET, for example with special events or university-games. In addition, the consequences of the SET should be public for the students so they become aware of how they can influence the quality of teaching in their faculty. Finally, we could find no evidence for the often made assumption that an online administration of questionnaires leads to a non-response-problem in SETs.
Student evaluations of teaching (SET) gain more and more importance for university teaching, especially web-based SETs. To guarantee the validity of SET and to avoid sample-errors high response rates are necessary – which cannot always be reached. This study investigates different factors, which might give some explanations for nonresponse in SETs. We examined the social exchange-theory, salience, opportunity costs, survey fatigue and the survey mode (online vs. paper-pencil).
Methods and data
We contacted student representatives of 48 universities, additional student groups in social media, and sent approx. 900 invitations via the online-panel PsyWeb. The web-based survey was available for about four months. Participants provided reasons for non-response, information about response behavior, and attitudes. A total of 490 participants (69.59 % female; age: M = 24.10, SD = 4.07) were included in the final sample.
Results
First, our results show a significant influence of social exchange on responding in SET (Δ R²=.069, p < .001). Also the influence of salience (ΔR²=.201, p < .001) and survey fatigue (ΔR²= .078, p < .001) show significant influences on the participation in SETs. No significant effects were found for opportunity costs (ΔR² = .005, p = .166) as well as for the survey mode (ΔR²= .004, p = .209).
Added value
The results of our study can be helpful for online researchers and evaluation managers in reducing non-response. Notably, our findings stress the importance of communication between students: It influences a student’s evaluation behavior if a fellow student evaluates all of his or her lectures and courses. Thus, universities should indicate how many students take part in a current SET to motivate even more students. Furthermore, it is helpful to increase the students’ identification with their own university and SET, for example with special events or university-games. In addition, the consequences of the SET should be public for the students so they become aware of how they can influence the quality of teaching in their faculty. Finally, we could find no evidence for the often made assumption that an online administration of questionnaires leads to a non-response-problem in SETs.
Access/Direct link Conference Homepage (presentation)
Year of publication2016
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Germany (361)
- Does the Use of Mobile Devices (Tablets and Smartphones) Affect Survey Quality and Choice Behaviour...; 2015; Glenk, K.; Liebe, U.; Oehlmann, M.
- Does Personalized Feedback Increase Respondent Motivation?; 2015; Kroh, M.; Kuhne, S.
- Direction of Response Format in Web and Paper & Pencil Surveys; 2015
- Nonresponse and Measurement Bias in Web surveys ; 2015; Metzler, A.; Fuchs, M.
- Deep impact or no impact, evaluating opportunities for a new question type: Statement allocation on...; 2015; Schmidt, S.
- Approaches for Evaluating Online Survey Response Quality; 2015; Gluck, N.
- Positioning of Clarification Features in Open Frequency and Open Narrative Questions; 2015; Fuchs, M.; Metzler, A.
- A Systematic Generation of an Email Pool for Web Surveys; 2015; Silber, H.; Leibold, J.; Lischewski, J.; Schlosser, S.
- 640 Current trends in management of high-risk prostate cancer in Europe: Results of a web-based survey...; 2014; Briganti, A., Isbarn, H., Ost, P., Ploussard, G., Sooriakumaran, P., Van Den Bergh, R.C.N., Van Oort...
- Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis; 2014; Gnambs, T., Kaspar, K.
- Open-ended questions in Web Surveys-Using visual and adaptive questionnaire design to improve narrative...; 2014; Emde, M.
- Query on Data Collection for Social Surveys; 2014; Blanke, K., Luiten, A.
- Why Do Respondents Break Off Web Surveys and Does It Matter? Results From Four Follow-up Surveys; 2014; Rossmann, J., Blumenstiel, J. E., Steinbrecher, M.
- The Effectiveness of Mailed Invitations for Web Surveys and the Representativeness of Mixed-Mode versus...; 2014; Bandilla, W., Couper, M. P., Kaczmirek, L.
- Post-endodontic treatment of incisors and premolars among dental practitioners in Saarland: an interactive...; 2014; Mitov, G., Doerr, M., Nothdurft, F. P., Draenert, F., Pospiech, P. R.
- Mixed-Mode Designs bei Erhebungen mit sensitiven Fragen: Einfluss auf das Teilnahme- und Antwortverhalten...; 2014; Krug, G., Kriwy, P., Carstensen, J.
- Mining “Big Data” using Big Data Services ; 2014; Reips, U.-D., Matzat, U.
- Instant Interactive Feedback in Grid Questions: Reminding Web Survey; 2014; Kunz, T., Fuchs, M.
- What Does the Satisfaction with Democracy Measure Mean to Respondents in Different Countries? How Cross...; 2014; Behr, D., Braun, M.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- The Influence of the Answer Box Size on Item Nonresponse to Open-Ended Questions in a Web Survey; 2014; Zuell, C., Menold, N., Koerber, S.
- Does the Choice of Header Images influence Responses? Findings from a Web Survey on Students’...; 2014; Barth, A.
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- Offline Households in the German Internet Panel; 2014; Bossert, D., Holthausen, A., Krieger, U.
- Which fieldwork method for what target group? How to improve response rate and data quality; 2014; Wulfert, T., Woppmann, A.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Improving cheater detection in web-based randomized response using client-side paradata; 2014; Dombrowski, K., Becker, C.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Increasing data quality in online surveys 4.1; 2014; Hoeckel, H.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information...; 2014; Schweiger, S., Oeberst, A., Cress, U.
- Undisclosed Privacy: The Effect of Privacy Rights Design on Response Rates; 2014; Haer, R., Meidert, N.
- The Effect of Benefit Wording on Consent to Link Survey and Administrative Records in a Web Survey; 2014; Sakshaug, J. W., Kreuter, F.
- GESIS Panel: Sample and Recruitment; 2014
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Incentives on demand in a probability-based online panel: redemption and the choice between pay-out...; 2014; Schaurer, I., Struminskaya, B., Kaczmirek, L.
- Responsive designed web surveys; 2014; Dreyer, M., Reich, M., Schwarzkopf, K.
- Extra incentives for extra efforts – impact of incentives for burdensome tasks within an incentivized...; 2014; Schreier, J. H., Biethahn, N., Drewes, F.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Asking Sensitive Questions: An Evaluation of the Randomized Response Technique Versus Direct Questioning...; 2013; Wolter, F.; Preisendoerfer, P.
- Respondent Choice of Survey Mode; 2013; Fuchs, M.
- 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...
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- The Digital Divide in Europe; 2013; Zillien, N.; Marr, M.
- The Recruitment of the Access Panel of German Official Statistics from a Large Survey in 2006: Empirical...; 2013; Amarov, B.; Rendtel, U.
- Online, face-to-face and telephone surveys—Comparing different sampling methods in wine consumer...; 2013; Szolnoki, G., Hoffmann, D.
- Where does the Fair Trade price premium go? Confronting consumers' request with reality; 2013; Langen, N., Adenaeuer, L.