The new dscout Diary launched at the end of 2017. We built a new researcher experience that improves how projects are run in dscout by making research and data analysis faster and easier.
Historically, a researcher created a project that was made out of one or more missions. Often researchers wanted scouts to go through distinct tasks, so they would accomplish this by creating multiple missions. Unfortunately, when researchers wanted to see all of their scouts response data across all missions, they couldn’t. Researchers had to access each mission separately and make sense of it all.
The new Diary allows for breaking up a mission with parts. Now researchers don’t have to create multiple missions because a mission can be divided up into parts. Researchers can access all scout data from their parts inside one mission.
- Allow researchers to see all submissions data from their project contained in one place for easy comprehension and analysis
In the entries viewer, the default is the grid view. The grid view allows researchers to see submissions across all parts of their mission shaped as cards, with a thumbnail and submission details.
You can sort results by scout name, date, part, or group.
Researchers can leave notes as reminders or observations. As part of notes they can highlight text on the text submissions and transcripts. Researchers can access these notes easily on the sidebar.
Researchers can leave comments on entries. Unlike entry notes, comments are seen by research participants—who can reply to them.
A unique and powerful feature dscout’s entries viewer is the capability of filtering participants responses by attributes such as demographics, or by answers to a question.
A researcher can also export data from the viewer. By clicking on the export icon on the sub-navigation, they’re prompted with a modal that lets them pick what kind of export they want, that being all entries media, or a csv of entry data for example.
By navigating to the Summary tab in the Entries viewer, a researcher can see quantifiable data on participants’ demographics and answers to close-ended questions.
By navigating to the Analysis tab, a researcher will see bubble charts that represent word frequency and parts of speech from open-ended scout responses.
Lastly, the Map view is a visual of where scouts from a mission are located.