I want to ask the consortium of readability experts about the feedback we received about information density and typography.
I'll be sharing this deck.
Followed by open discussion.
Description
Description
| Status | Subtype | Assigned | Task | ||
|---|---|---|---|---|---|
| Resolved | ovasileva | T341631 [EPIC] Q1 Main hypothesis: Typographical and palette customizations | |||
| Resolved | ovasileva | T313828 [EPIC] Typography: improve typography and allow for variable typography settings | |||
| Resolved | BUG REPORT | ovasileva | T349303 Implement initial CSS Custom properties for font-size in Minerva Neue | ||
| Resolved | ovasileva | T357770 Evaluate rationale for line height changes in Minerva | |||
| Resolved | ovasileva | T358591 Ask Readability consortium about ASD, information density, and typography |
Event Timeline
Comment Actions
link to the consortium
Notes:
- The consortium members agreed that ASD, typography, and readability are understudied.
- We are going to book a follow-up meeting to discuss future research opportunities
- I got some more anecdotal feedback that the fact that Wikipedia's text is more cluttered with links, citations, snd special formatting than typical long form reading experiences makes it relatively more information dense than typical reading experiences online. This, coupled with an increase in typographic density, created feelings of overwhelm for some readers on the spectrum. This supports our decision to revert the line-height change.
Comment Actions
What do you folks think?
I think the decision to revert makes a lot of sense.
What other research is out there on ASD and reading interfaces?
I know very little about accessibility.
What should we have done?
As mentioned before, I believe you should conduct user testing whenever doing major changes that might affect readability. The main argument is that wikipedia (and more specifically the mobile version) is the most read text-based webpage in the world.
If user testing has not been done before, I believe there is a LOT that can be learned. Its important with theory and science but , in my experience, nothing beats having done your own research and having your own data.
What should we do next time?
In addition to user testing I believe AB-testing could be leveraged to accumulate quantitative data. I know this can be a controversial subject and setting it up an running experiments does take a a lot of time and effort, but the payback is grand. Talk to your analytics/data science people regarding this.
Happy to help out with both suggestions above, just reach out.