search

UBC-MDS / mental-health-analysis-and-app

Analysis via shiny app in R investigating the attitudes towards mental health disorders in tech workplace.
MIT License
1 stars 4 forks source link

Peer feedback #11

Open olivia-lin opened 5 years ago

olivia-lin commented 5 years ago

Olivia-Gabriel Group

  1. Some explanations for the relationship between questions and plot
  2. Some explanation for what this plot is for, especially the axises
  3. Point out that the questions are for employers and the axises are for employees
GabrielBogo commented 5 years ago

Olivia-Gabriel Group (cont.)

4 - Add title (maybe in question format) that summarizes the intent of the plot: "How different company policies influence employee's attitude towards overall health?" 5 - Add text box explaining the concepts behind each axes in the radar plot. It's hard to understand what each of the axis is measuring. 6 - Toggle feature between "Yes", "No" and "Don't know" is not evident. Maybe a "Click to toggle" would help the usability. 7 - Scores are fine! We trust the analyst who did, as long as we feel we can always refer back to the source code to understand the calculation. A footnote would suffice. 8 - The dataset seems very hard. Well done framing a very good question!. I think this is one of the most difficult tasks and you guys did it very well. After some minor changes, this visualization could already be valuable to real HR directors! 9 - Facet or overlay radars? Tough. Olivia prefers facetting, Gabriel prefers overlaying.

jielinyu commented 5 years ago

Jessie - Phuntsok group

  1. Create a tab 'summary' to introduce app's background, objective question and how users can get information from the plots.
  2. In the right, add a "click box" to let users choose "Don't know", "No", "Yes".
  3. Add description about what the plots convey. For example, what r and theta in the plots mean to users.
  4. Add description about what area of each question means.
  5. Add description the relationship between "Employer Policy Survey Questions" and plots' questions.
  6. The categorical questions data set are very hard, good challenge!