The goal of the project is to take education to the next level by bringing together AI researchers, engineers, data scientists, and educational domain experts to tackle the challenges of education with the power of Artificial Intelligence.
The Journal will be leveraged to broadcast the initiative and to showcase each team member’s contribution.
Update 19th Dec: Oluwafunmilayo Ajayi‘s article is published gathering insights from the market research conducted so far and defining the direction of the MVP. Read more below.
The project members are located in four different countries across Europe and Asia and collaborate remotely.
Purpose: “To bring education to the next level”
- Open Source project:
- Educational domain experts
- Data scientists
- Identify the real problems and challenges of Education
- Apply Artificial Intelligence
- Showcase and promote the initiative and each member’s contribution through AI Time Journal
When the first prototype has been tested in production, data has been gathered, insights have been gained, the first lap of the Build-Measure-Learn loop will be completed.
- Ideas – Brainstorming
- (Market research/experiments)
- Pick one idea (a problem that we want to solve)
- Build the first prototype
- Test it live
- Gather data, gain insights
Nov 4th – Nov 10th
- Project members get to know each other
- Project members brainstorm in 1o1 calls problem/solution ideas for the first MVP
Nov 11th – Nov 17th
- Decide which problem we want to tackle with the first MVP (Build)
- Devise experiment(s): how we are going to test the MVP to gather data (Measure)
- Decide evaluation criteria for the experiment’s result (Learn)
Nov 18th – Dec 2nd
- Decided to focus on how AI can be leveraged to enhance the training of customer service agents
- Market Research on AI applied to customer service agents
Dec 3rd – Present
- Gathering all insights from the market research
- Oluwafunmilayo Ajayi‘s article is published on 19th Dec 2018, gathering insights from the market research conducted so far and defining the direction of the MVP
- Team call to discuss MVP
- Start MVP development
Data scientists and educational domain experts are welcome to collaborate.