Survey Sidekick: Structuring Scientifically Sound Surveys

I-Han Hsiao, Shuguang Han, Manav Malhotra, Hui Soo Chae, Gary Natriello

Online surveys are becoming more popular as a means of information gathering in both academia and industry because of their relatively low cost and delivery. However, there are increasing debates on data quality in online surveys. We present a novel survey prototyping tool that integrates embedded learning resources to facilitate the survey prototyping process and encourage creating scientifically sound surveys. Results from a controlled pilot study confirmed that survey structure follows three guided principles: simple-first, structure-coherent and gradual-difficulty-increase, revealing positive effects on survey structures under learning resources influences.

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