March 09, 2020: FLOE infrastructure Continuation

Present: Cindy, Justin, Jutta, Michelle, Ned, Philip, Ted,

Video Recording

Google Doc

Agenda

1. Jutta continues the talk she didn’t finish in the last meeting
2. Discussion of a draft diagram of the high level implementation structure

Notes:

Requirement challenges:

• Learners can control 3 parts to influence the matching: 

1. Learning goals
2. Configure the preprocessor generated summary of learning needs/preferences
3. Feedback on matching results

Are these enough for the matching engine to be non-black box?

• Large data sets to train algorithms
• What other exploration tools can learners use to discover their learning needs?
• Where to search OER material? Wild web?

Technical Challenges:

• Preprocessor algorithm
• Matching algorithm
• How to identify each learner across all exploration tools and platforms

3 main direction of WeCount:

1. Address data gaps through co-design, challenge workshops that data related problems are not addressed
2. Identify accessibility issues of existing data science tools. Address these through co-design.
3. Explore the possibilities of moving against the bias, especially deep learning / big data based systems.

Floe infrastructure is the Floe match within WeCount

Issues with the diagram:

1. Instead of letting learners config a set of preferences, machine learning should be applied to understand how learners learn better
2. Instead of watching learners to discover their preferences, learners should be given a tool to track and record their preferences

The actual understanding of how learners learn better, such as kids learning math thru dinosaurs 

Next meeting: Tomorrow 1-2PM