| Author: | Javed Khan |
| Learning Line: | Digital Transformation |
| Course: | DT4: Data-driven Design |
| Week: | 5 |
| Competencies: | Knows how to prototype alternatives for an AI & Data Science product. |
| BoKS: | 4K4, Knows how to prototype alternatives for an AI & Data Science product. |
| Learning Goals: | Understand the importance of prototyping alternatives and know how to rapidly prototype alternatives for an AI & Data Science product. |
Introduction
This week is a continuation of previous week. We extend the previous week by focusing on hi-fidelity prototyping. Some other names of hi-fidelity prototyping are: interactive prototype and clickable prototype. Essentially you want after you have explored several ideas through low-fi prototyping to now create a digital prototype in which you solidify most of your choices and which you can share with a larger crowd. However, you still want to test ideas and therefore create alternatives that you will evaluate with users; only those alternatives are much more focused and not on a conceptual level. A great article for more details on the fidelity of prototypes is from the Nielsen-Norman group, titled: UX Prototypes: Low Fidelity vs. High Fidelity.
Exercise: develop a hi-fi prototype
There is a plethora of hi-fi prototyping tools which have their strengths and weaknesses that you can choose from.
Given the (current) cross-platform features and popularity, here are some videos to get you started with:
Invision:
Adobe XD:
Figma: