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.
The final publication is available at Springer via https://doi.org/10.1007/978-3-319-07221-0_65.