Adobe Illustrator presents challenges like limited design inspiration and a complex toolset, which create a steep learning curve for beginners and can hinder productivity. AI integration could simplify the process by offering personalized guidance and inspiration, helping users unlock their creative potential.
Help participants get to know each other and gather background information about their experiences and perspectives.
Paper, pens, markers
8 persona cards
Observe responses on different types of instructions to follow and see which ones were preferred.
Paper, pencils, markers, stencils, models
Observed actions, feedbacks
Understand individual preferences in UI layout and identify desired features.
Paper, printed layout, scissors, glue/tape, pens
8 new layouts as well as video walk-throughs of each of them with explanations
Generate a wide range of ideas and perspectives from participants and categorize them.
Sticky notes and pens
We created object/interaction tables to see the key functionalities available to users, the objects in the system, and the details of how users interact with them.
To see more in detail, click here.
This is a radar chart to compare features in our design:
Dimensions for the chart are based on principles introduced by Professors Michel Beaudouin-Lafon and Wendy E. Mackay.
Here is the summary of our design methods:
Click here to view more details and explore the project presentation slides.
Here is a video demonstration of AIDOBE.
Participatory workshop allowed us to observe users behaviors, interactions, and challenges in real time. It helped us to identify their needs and preferences in a natural and collaborative setting.
We also enjoyed applying Generative Interaction theories introduced by Professors Michel Beaudouin-Lafon and Wendy E. Mackay, particularly as we tackled a complex system like Adobe Illustrator. The interaction table was invaluable in our project, allowing us to systematically construct user-system interactions across various features and scenarios. Additionally, drawing a feature space putting several socio-technical principles as dimensions helped us to compare features more constructively, giving a grounded reasoning for each feature we included.