Improving success/completion ratio in large surveys: a proposal based on usability and engagement

Abstract

This paper presents a research focused on improving the success/completion ratio in large surveys. In our case, the large survey is a questionnaire produced by the Spanish Observatory for University Employability and Employment (OEEU in the Spanish acronym). This questionnaire is composed by around 32 and 60 questions and between 86 and 181 variables to be measured. The research is based on the previous experience of a past questionnaire proposed by the OEEU composed also by a large amount of questions and variables to be measured (63–92 questions and 176–279 variables). After analyzing the target population of the questionnaire (with the target population of the previous questionnaire as reference) and reviewing the literature, we have designed 11 proposals for changes in the questionnaire that could improve users’ completion and success ratios (changes that could improve the users’ trust in the questionnaire, the questionnaire usability and user experience or the users’ engagement to the questionnaire). These changes are planned to be applied in the questionnaire in two main different experiments based on A/B test methodologies that will allow researchers to measure the effect of the changes in different populations and in an incremental way. The proposed changes have been assessed by five experts through an evaluation questionnaire. In this questionnaire, researchers gathered the score of each expert regarding to the pertinence, relevance and clarity of each change proposed. Regarding the results of this evaluation questionnaire, the reviewers fully supported 8 out of the 11 changes proposals, so they could be introduced in the questionnaire with no variation. On the other hand, 3 of the proposed changes or improvements are not fully supported by the experts (they have not received a score in the top first quartile of the 1–7 Likert scale). These changes will not be discarded immediately, because despite they have not received a Q1 score, they received a score within the second quartile, so could be reviewed to be enhanced to fit the OEEU’s context.

Publication
International Conference on Learning and Collaboration Technologies. HCI International 2017
Date
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Juan Cruz-Benito
Senior Software Engineer @ IBM Research