Authors: C. Ailie Fraser, Mira Dontcheva, Holger Winnemöller, Sheryl Ehrlich, and Scott Klemmer.
Summary
This paper proposes DiscoverySpace, an extension panel for Adobe Photoshop, to help onboard new users execute tasks and explore the features of the software. DiscoverySpace suggests task-level action macros to apply to photographs based on visual features. These actions are retrieved from an online user community. The findings from user evaluation showed that it helped novices maintain confidence, accomplish tasks and discover features.
Reflection
This paper addresses an important problem that I often encounter while building tools/interfaces for novice users — how do we efficiently handle the onboarding process? While DiscoverySpace, in its current form, is far from being the ideal tool, it still opens the doors for how we can leverage the strengths of recommender engines, NLP and UI designs to build future onboarding tools for complex softwares.
Something we discussed in the last class – DiscoverySpace also demonstrates how need-finding exercises can be translated into design goals, and in doing so, it increases the likelihood of being useful. I wonder, how this process can be scaled up for a general purpose workflow of designing onboarding tools for any software (or maybe it is not necessary).
In one of my previous reflections, I mentioned about how in-app recommendations for using different features helped users explore more, which was a stark contrast to the notion of filter bubbles. This paper also demonstrated a similar finding, which leads me to believe that maybe in-app feature recommendations are useful for exploring the space when the users, by themselves, cannot explore or unaware of the unknown space. I am hoping to see a future study by the RecSys community, if there isn’t one already, to understand the correlation between tool feature recommendations and the user’s expertise level.
This paper certainly made me think a lot more about general purpose applicability i.e. how can we build a toolkit that can work for any software. I really liked the discussion section of the paper as it discussed the topics that would essentially form the pathway to such a toolkit. Building a corpus of actions is certainly not impossible, considering the number of users for a software. Most plugins and themes are user-generated, and that’s possible because of the low barrier to contribution. Similar pathways and incentives can be created for users to build a repository of actions, which can be easily imported into DiscoverySpace, or whatever the future version is called. The AI engine can also learn when to recommend what kind of actions with increasing data. Considering how big the Open Source Community is, that would be a good starting place to deploy such a toolkit.
Questions
- Have you ever had trouble onboarding novice users for your software/tool/interface? What did you wish for, then?
- Do you think a general purpose onboarding toolkit can be built basing off the concepts in DiscoverySpace?
- The paper mentions about the issue of end-user control in DiscoverySpace. What are the challenges of designing DiscoverySpace if we think about extending the user base to expert users (obviously, the purpose will change)?
Using IDE’s, like PyCharm and IntelliJ can be pretty tricky for novice users. According to me, incorporating the onboarding toolkit mentioned in DiscoverySpace can prove helpful in these cases.