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Online Survey on "Exams and Written Papers". Documentation

Author

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  • Marc Höglinger
  • Ben Jann
  • Andreas Diekmann

Abstract

In spring 2011, the students of the University of Bern and ETH Zurich (Swiss Federal Institute of Technology) in Switzerland were invited to participate in an online survey called "Exams and written papers" ("Prüfungen und schriftliche Arbeiten an der Universität Bern" at the University of Bern and "Prüfungen und schriftliche Arbeiten an der ETH Zürich" at the ETH Zurich). The goal of the survey was to estimate the prevalence of various forms of student misconduct such as plagiarizing or cheating in exams. Because students might be reluctant to reveal information on such behaviors, special techniques for sensitive questions were employed in addition to direct questioning. Respondents were randomly assigned to direct questioning or one of five different sensitive question techniques. A comparison of the techniques' results indicates whether direct questioning is affected by social desirability bias and whether students are more inclined to provide honest answers if interviewed by so-called dejeopardizing questioning techniques. Sensitive question techniques evaluated in this survey are three different implementations of the Randomized Response Technique as well as two variants of the recently proposed Crosswise Model. Since the survey was conducted via the internet, special effort was put into developing implementations of the RRT and the CM suitable for self-administered online interviews. This document describes the design of the survey and the questionnaire and provides details on the different implementations of the RRT and the CM, the field work, and the resulting dataset. The appendix contains a codebook of the data and facsimiles of the questionnaire pages and other survey materials.

Suggested Citation

  • Marc Höglinger & Ben Jann & Andreas Diekmann, 2014. "Online Survey on "Exams and Written Papers". Documentation," University of Bern Social Sciences Working Papers 8, University of Bern, Department of Social Sciences, revised 06 Oct 2014.
    • Handle: RePEc:bss:wpaper:8
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    File URL: https://boris.unibe.ch/65040/10/ASQ-ETHBE-2011.pdf
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    References listed on IDEAS

    as
    1. Ben Jann, 2005. "RRLOGIT: Stata module to estimate logistic regression for randomized response data," Statistical Software Components S456203, Boston College Department of Economics, revised 12 May 2011.
    2. Andreas Diekmann, 2012. "Making Use of “Benford’s Law†for the Randomized Response Technique," Sociological Methods & Research, , vol. 41(2), pages 325-334, May.
    3. Elisabeth Coutts & Ben Jann, 2011. "Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT)," Sociological Methods & Research, , vol. 40(1), pages 169-193, February.
    4. Carel F. W. Peeters & Gerty J. L. M. Lensvelt-Mulders & Karin Lasthuizen, 2010. "A Note on a Simple and Practical Randomized Response Framework for Eliciting Sensitive Dichotomous and Quantitative Information," Sociological Methods & Research, , vol. 39(2), pages 283-296, November.
    5. Ben Jann, 2008. "RRREG: Stata module to estimate linear probability model for randomized response data," Statistical Software Components S456962, Boston College Department of Economics, revised 12 May 2011.
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    Cited by:

    1. Marc Höglinger & Ben Jann, 2016. "MTurk Survey on "Mood and Personality". Documentation," University of Bern Social Sciences Working Papers 17, University of Bern, Department of Social Sciences.

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    More about this item

    Keywords

    online survey; sensitive questions; plagiarism; exam cheating; randomized response technique; crosswise model;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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