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Interaction design focuses on creating interfaces, systems, and devices revolving around user behavior. In this course, author David Hogue sheds light on designing effective interactions for any digital medium. The course explores the interaction design process, explains how interaction designers work and the tools they use, and details the five essential principles of interaction design: consistency, visibility, learnability, predictability, and feedback. The course also introduces basic psychological concepts and examines the roles of context, motivation, and perception in a design; offers navigation best practices; and shows how to design for motivation and behavior and provide feedback to visitors.
How do we work? What are our processes and methods? There are many ways to accomplish our design goals, and different teams, agencies, and companies will have their own methods. Some still work in a traditional waterfall process, where each discipline completes their contribution before the next discipline begins. Others are influenced by the agile approach, and the entire team tackles one component of the project at a time in rapid sprints. And there are also a myriad of hybrid approaches that leverage iteration, collaboration, and testing.
There is no single way to achieve strong designs in the desired outcomes, but at the core, there are some processes in which nearly all interaction designers engage: definition, research, ideation, design, prototyping, observation, and iteration as needed. Let's go through each of these, starting with definition. We must define the project, the product, and the design task at hand, and understand what we are trying to solve or achieve. How we define a problem determines if and how we are able to solve it.
Once we have defined the project, then we begin our research. This occurs in parallel with nearly every step in our process. We need to gather data to help us, define the product or the problem, generate ideas and potential solutions, inform our designs and prototypes, and guide our iterations. We use data to form the foundation of our final product, and our initial research gives us direction, but we should always be seeking more data. Research never really ends.
Once we understand the problem, we need to generate possible solutions through ideation. We think, collaborate, sketch, ponder, wonder, dream, and draw. We generate many possibilities, select a few, and pursue only the best. It has been said that Apple encourages a process where their teams generate 10 viable ideas, select the top three, and refine them, then choose only the best one to pursue. They throw away 90% of their ideas in order to achieve their best.
In design and prototyping, we create models of our possible solutions to test them, ensure they are complete, and that they help people solve problems, complete tasks, and achieve goals. Our designs range from low fidelity sketches, to high fidelity wireframes, and visual comps. And our prototypes vary from simple objects, or click through sequences, to elaborate functional interfaces, and mock devices. But most importantly, we take the time to think through the steps of the interactions, to consider the presentation of the information, and to validate the purpose and value of the product.
No design is perfect the first time it is drawn or modeled. That's where iteration comes in. No matter how carefully we try to consider the needs and perspective of others, we can't anticipate everything. We're not designing for ourselves, and when we observe others interact with our designs and prototypes, we inevitably find opportunities to improve the design, and so we iterate, evolving the design as we gather data, making it better with each round until it is ready. When a product, device, or interface is ready to launch, we are still not finished.
Iteration is more than just refining the design. It also includes monitoring the performance, usability, accessibility, and the success of a product after it's been released. We gather data, speak with and observe users, gather usage and error data, and look for opportunities to modify, improve, and enhance that product. Then the design process continues again, and again.
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