SKILLAB - documentation

Documentation

Explication and details about our project

explanation

Firstly, we built a mindmap to understand fully our theme: "Provide easy access to learning in-demand skills."

Then, we asked ourselves some questions: what are the issues? What are the needs?

And we finally came up with a project of application that we found interesting and useful

Wireframe

We made a wireframe of the project in order to have an overview of what the app would look like. We used Figma to make our first draft. The idea is to start to think about the architecture and the elements of the app. It is very valuable for the next step : the mockup.

Mockup/Test

We decided to test four students aged from 20 to 24 in order to stay in the scope of the project. Effectively, our first thought was that students needed the most formations that’s why we decided to have feedback from four of them. Besides, the tests confirmed that these four students were willing to benefit from more formation : even students in rich countries where schooling is rife are interested in having more access to formation.
Finally, these interviews helped us settle which points we had to change concerning our interface:

Technologies

Here is an overview of the different technologies we are going to use:

Our project truly began when we found out that people, more specifically students needed more formations. Thus, we decided to facilitate e-learning formations access by creating an app . After having recorded some pieces of information from the client gathered thanks to our substantial quiz, the app gives him a choice of formations that best matches his qualifications. The main technology used is APIs: our app will use APIs to bound our propositions of formations to e-learning formation databases. We will need to be using AI in order to classify all the different data collected and order them according to people's professional aspirations. And then, we will tag every formation in our database so that it could be linked to a certain type of people. Finally, the server will need a program that will link the questionary answers to a certain type of person (category). This same program will now gather every formation that best fits this individual and then send data (the perfect formation) through the API to the user’s interface.