I like, I wish, What if?
In design, critique is synonymous with improvement. By having a critique from multiple sources, it forces you to look at your work differently and can potentially spark new ideas. In terms of the mechanics of critique, there are many ways to do it, but the one I’m discussing here is the method “I like, I wish, what if”
What is that?
This method, which I’ll dub LWW, structures your critique in an organizational manner. By looking at the name, the three categories are simple. “I like” convey’s what the critique liked, “I wish” addresses direct issues they have, and “what if” presents new ideas the critique has. There’s no specific order the comments have to go in, but it trims the structure down to three main parts.
The reason this method works is that it both organizes your critique, along with framing it in a more useful way. With the critique sectioned off, it won’t be a bunch of scattered “oh I like this, this is alright, fix this, this is cool”. By using LWW, you know which are the compliments, what needs to be improved, and what are some new ideas. In terms of framing the critique, this method makes it both more positive and constructive. First, what is liked about comes up first, boosting the user’s confidence early and letting them know what works. After that comes critique, but since it’s framed as “I wish”, it’s less intense. It turns the conversation into a discussion of different ideas rather than just putting down the designer
A great example of an "I like, I wish, what if" board, as done by Mel Perry in his mobile app design case study
Another benefit of this method is how easy it is to implement. Context-specific things like tools and environments don’t affect this method. Rather, as long as you are critiquing something, this method can help guide you along with that critique, providing better solutions for the overall designs.
Research method examples and how I’ll utilize it
To provide some examples of this method in action, here are a couple of studies
Implementation and Usability Testing of a Cross-platform Moodbased Video Recommender System for Older Adults by Meifang Chen
The title is a mouthful, but in this study, Meifang Chen used the LWW method to help present a system that provides recommendations for videos on a site through the user's mood. To begin, he first got the data he needed by showing a multitude of different participants' videos based on their system. LWW was then used to see what the participants thought of the system starting on page 50. By utilizing the LWW, Chen gets a clear picture of what the users don’t and don’t like. When looking at all the participant's tables, you can see a variety of different feedback, with each participant leaning differently toward the majority liked or disliked.
A look at how the critique is structured in this study
In this study, a variety of different researchers try to discover how the design thinking process can affect doctoral students. To do this, participants take a design thinking workshop, with the differences in their creativity and thought process being analyzed after. While not as big a part as it was in the last study, LWW is used here. It helps the participants show what they thought of the workshop, as well as forcing them to think more like a designer. The main aspect this study showed is how versatile the LWW method is, as it can be placed easily in many studies, greatly enhancing them.
A sample of what the study was asking
As shown with both of these research studies, this method is both easy to implement as well as incredibly useful. For me, I would likely use this method when conducting my user research studies for my site. As it’s a site with many tabs and audiences, I want a lot of critiques that I could easily look at. With this method, all my users will not only have a guide to follow, but my critique will also be automatically organized from the start, expediting the redesign process greatly. This method will also be useful for my own personal evaluations during this redesign. Whether I'm critiquing the old site or analyzing my redesign, using the LWW method will be commonplace for me in this project.
Chen, Meifang, "Implementation and Usability Testing of a Cross-platform Mood-based Video Recommender System for Older Adults" (2020). Creative Components. 481. https://lib.dr.iastate.edu/creativecomponents/481
Interaction Design Foundation. INTERACTION-DESIGN.ORG.
Perry, Mel. “Eat Well | Mobile App Design.” Medium, 30 Dec.2019,medium.com/@melssp/eat-well-mobile-app- design-6fb5171965f4. Accessed 2Nov. 2020.
Ulibarri, N., Cravens, A. E., Cornelius, M., Royalty, A., & Nabergoj, A. S. (2014). Research as design: Developing creative confidence in doctoral students through design thinking. International Journal of Doctoral Studies, 9, 249-270. Retrieved from http://ijds.org/Volume9/IJDSv9p249-270Ulibarri0676.pdf