Coney: a conversational approach to enhance engagement in surveys

Citizens’ participation to research activities is a key element in bridging the gap between science and society. Researchers need to collect data from participants and, usually, questionnaires are the primary employed means. In this respect, research is focusing on improving the user experience to facilitate data collection.

Coney is an innovative survey instrument to enhance user engagement. It exploits a conversational approach, by administering questionnaires mimicking a chat. On the one hand, Coney enables researchers to model a conversational survey with an intuitive graphical editor; on the other hand, Coney allows publishing and submitting surveys through a conversational interface.

Coney relies on a graph-based data model for surveys. Coney allows defining an arbitrary acyclic graph of interaction flows, in which the following question depends on the previous answer provided by the user. This offers a high degree of flexibility to survey designers that can simulate a human-to-human interaction, with a storytelling approach that enables different personalized paths.

Coney adopts a quantitative research method: survey questions are internally associated with a set of latent variables and each possible answer option is internally coded to allow for the numerical interpretation of the collected answer. To this end, Coney also offers a dashboard to support the statistical analysis of results.

To implement FAIR principles, to pave the way for the adoption of Coney within Open Science and to promote responsible and reproducible research, we offer the graph-based model of Coney as an open ontological model; this allows to publish and to share on the web both the surveys and their collected answers as linked data research objects.